Episodes
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What makes multidisciplinary collaboration the key to health and life sciences research and innovation? What is the impact of bundled, integrated solutions on the patient experience? And how can we invest in what matters most in research while streamlining the entire process? We will learn all that and more in this episode of Research in Action with Frank Baitman, Digital Health, Data, and Technology Executive; and former Chief Information Officer of the US Department of Health and Human Services. http://www.oracle.com/health http://www.oracle.com/life
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Why is the confluence of healthcare and life sciences happening? What are the two biggest mistakes of technology in healthcare? And how can research insights be embedded into every care decision? We will find out all that and more with our guest Dr. David Feinberg, a medical professional and healthcare industry executive and current Chairman of Oracle Health. http://www.oracle.com/health http://www.oracle.com/life
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Episodes manquant?
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How can shifting mindsets fuel the next wave of innovation in the pharmaceutical and life sciences industry? In what ways can we ensure the vast amounts of health data are utilized securely and effectively to foster groundbreaking medical advancements? And how is Oracle's new Health Data Intelligence poised to transform the industry in an unprecedented manner? You’ll learn all that and more with our guest Michael Fronstin, Vice President and Chief Commercial Officer at Oracle Life Sciences, who has worked across nearly every area of the industry from positions at Merck to J&J to Kantar Health and now at Oracle. -------------------------------------------------------- Episode Transcript: 00;00;00;04 - 00;00;26;25
In what ways do the mindsets in the pharma industry need to change? How can we make sure massive amounts of health data is applied to practical effect? And how might Oracle's new Health Data Intelligence platform be an unprecedented game changer? We'll find all that out and more on Research in Action. Hello, welcome to Research in Action, brought to you by Oracle Life Sciences.
00;00;26;25 - 00;00;49;15
I'm Mike Stiles. And today we've got a guest who's been a veteran in the life sciences industry and who knows Oracle Life Sciences quite intimately because the guest is Michael Fronstin, vice president and chief commercial officer at Oracle Life Sciences. He's worked across nearly every area of life sciences, from positions at Merck to J&J to Kantar Health and now at Oracle.
00;00;49;15 - 00;01;11;25
So, Michael, thanks for being here. Thanks, Mike. Happy to be here and thank you so much for hosting this session. Really appreciate it. Great. Well, you know, you're the perfect person to talk to about what I want to talk about, which is changing people's minds and changing how we even approach and think about life sciences. So you've got that to look forward to.
00;01;11;25 - 00;01;34;28
But first, let's learn a little bit more about you. How did your interests and opportunities in life take you down the path that led you to where you are now? Yeah, thanks for that question. That's that's a great question to start out with. I'll tell you that as human beings, we all have something going on in terms of health care, whether it's impacting ourselves or friends or family, everyone's going through something.
00;01;34;28 - 00;01;56;25
At some point. You just don't know what the magnitude is or how long lasting, right? So having patience and empathy is so important. And of course myself, I've gone through things and unfortunately starting at a very early age of 12, I lost my best friend to the brain cancer and from the time I was 12 to the time I was 21, unfortunately, I lost a lot of people to different health ailments.
00;01;57;11 - 00;02;17;10
I guess, climaxing with losing my father when I was 21 years old. During that time, I always thought about health care and how it was impacting the people around me and wondering what could I do? And I felt pretty helpless, to be honest with you during those times, because some young boy don't there and there really wasn't anything I can do.
00;02;17;10 - 00;02;35;01
But as I got older and I went into college, I realized I could make a difference in health care. And that was going to be the industry that I was going to focus on. So I went into social sciences, became a sociologist with a business math background, and went to graduate school for an MBA in health care arbitration.
00;02;35;10 - 00;02;56;07
And that's when really things opened up to me where I started saying, okay, what aspect do I like? Where can I make a scalable impact? And I ended up joining Humana A down in Florida for a year or so, realizing that I can make a difference there and get people enrolled, help them get claims processed and paid. And from there my career took off.
00;02;56;07 - 00;03;21;02
I end up going to Merck, carried the bag and really experience the in office experience back in the days of the early nineties in terms of what patients were experiencing, seeing doctors who were really, really good and so much good at diagnosing patients and treating them in a time where most of the chronic conditions didn't have treatments available and new ones were coming out.
00;03;21;16 - 00;03;53;06
And I'll tell you, it was pretty exciting during these times being at Merck and seeing all these innovations. But I'll tell you, during that time I was really able to focus on one therapeutic area and it wasn't very scalable. It wasn't really having the impact it wanted. And it wasn't until I came to the consulting side of the business, you know, working with dozens of customers and maybe hundreds of brands over the past 20 plus years where I really felt like maybe a direct and indirect impact on people's lives around the globe.
00;03;53;28 - 00;04;16;02
So that's that brings me to today. And now I'm with Oracle Life Sciences, where I feel like it's even bigger and broader and better. So I'm excited about the present. I'm excited about the future. Yeah. You mentioned you kept repeating a phrase that kind of struck stuck with me, which is that you wanted to make a difference. Is that hard to do in the health care space?
00;04;16;02 - 00;04;39;12
I mean, have you been gratified by your ability to do that or has it always been a push and pull? Oh, interesting question. Definitely a push. And so, you know, sometimes you can you can make decisions and get them executed very quickly. Other times, it takes a while to do. You know, you have regulatory bodies that you have to deal with different types of payers around the world.
00;04;39;22 - 00;05;04;19
Decisions are always made quickly. And if it's the right decision because of various reasons, whether it's bureaucracy or internal or external, or you need to generate real world evidence modeling or even publications, we have more than 2000, maybe 3000 publications, and you develop the evidence, you submit the publication. It could take, you know, six months, a year, two years to get it published right?
00;05;04;19 - 00;05;24;14
So things just take time, unfortunately. But yeah, you can make a difference. I feel like I've made a difference. I feel pretty gratified about what I've done. And in the areas of the impact that I've made. So and a lot of it is just make an impact within your world and hoping that you can expand it beyond to make a broader impact.
00;05;24;14 - 00;05;59;11
You were at Kantar Health for like 17 years or so. How did what Kantar does align with Oracle Life Sciences and the idea behind just leveraging technology to benefit customers and partners? I'm actually coming on 19 years since we think about it and you mention it. So when I step back and think about my time at Bert or Change in Merck and the broader industry, life science clients need to accomplish three things in order to get their compound, whether new or existing compound, really the new compounds into the hands of the appropriate patients.
00;05;59;11 - 00;06;24;18
They need to get their drugs approved right by some regulatory authority. They need to get them reimbursed and they need to have a strong launch to drive awareness. Otherwise no one's going to prescribe it or patients. People aren't going to request it, right. So those three things need to need to occur. Kanter Health is really focused on the second and third in terms of the research services and expertise.
00;06;25;00 - 00;07;10;02
So the types of people are. Kanter Help are methodologies, social scientists like epidemiologists, psycho nutrition, these these are the folks that know how to design and conduct research, how to consult on the research from a Real-World evidence perspective and driving insights, evidence from a commercial planning perspective, prioritization, things like that. Where is the Oracle Life Sciences group? The other side of the group is really all about technology and applications predominantly focused on driving clinical trials for regulatory approval, of course, and in the area of pharmacovigilance during those trials and tracking them when those products are in the real world.
00;07;10;06 - 00;07;38;08
Right. Post-marketing authorization. So when you bring these two groups together and these types of people together, the technology, the medical intelligence, the scientific, methodological experience of the cancer health folks, have you got the best of all worlds, right? Technology, data experience combined. You take these wraparound services with the technology in and now our clients are able to see a much higher level of value, if you will.
00;07;38;23 - 00;08;02;25
Well, you've actually been anything but shy in the past about saying how the mindsets in the pharma industry really need to change. So what is the current mindset? And in what ways is it limiting? I'll tell you, the health care industry, including life sciences, has always been a little bit of a laggard in terms of of our movement.
00;08;03;11 - 00;08;30;15
Part of that issue is that we we operate in silos, right? And even within our life science clients or customers, the different cross-functional teams don't always come together. They don't know each other. Sometimes they buy the same data, right? So the inefficiencies of spending more budget than they need to, we're not leveraging the same data for different purposes, and we really need to break down the silos.
00;08;30;29 - 00;08;53;15
I think that from a mindset perspective, individuals on every side of the business really need to step back and pick up their heads and look around, see the big picture, understand where are we going? The data is critically important. Big data was becoming the buzzword ten, 15 years ago, but no one really knew what that B meant. Well, now it's here.
00;08;53;22 - 00;09;14;06
We could do something with big data, right? Is sort of on the fringe. Some people are using it, some people aren't, there hasn't. So this is a time where you could either bury your head in the sand because you don't understand it or you're afraid of it, or you can lean in and figure it out. And if you don't lean in, you're going to be left behind.
00;09;14;06 - 00;09;45;01
So I think we need to break down the silos. People need to step back and see the big picture. And I think they need to take risks and and lean in and it Oracle, that's what we're doing. We're committed to helping, you know, through creating open ecosystems, to breaking down barriers across teams, using our teams. And, you know, hopefully everybody will wind up picking your head up and looking at the big picture and caring more about collaboration and how these things can improve so that innovation moves forward faster.
00;09;45;17 - 00;10;06;25
Is that a realistic ask? I mean, I assume researchers are very busy with their heads down working on what they're working on. Can they can they expand and broaden their view? They have that luxury, Absolutely. It's like anything else, you just have to make the time. You got to take the time to make the time, invest the time to figure it out.
00;10;06;25 - 00;10;26;26
It's not easy. And I'm not saying it's easy by any means, but it's worth it to do. And I remember when I was a rep with Merck, you know, moving to Pennsylvania, the Home Office, the analysis, one of my problems that you get there and if you want pieces of advice when you get there, keep your head up.
00;10;27;13 - 00;10;51;11
And I said, I'm always positive. He said, that's not what he said. Look around, understand what's around you, incorporate it, immerse yourself in things you don't understand. You know, be comfortable being uncomfortable and again, new job, new new house placeholders. How do we find the time, how to figure it out? Right. And I see the people around me and our clients.
00;10;51;11 - 00;11;18;18
I see the people around me at Oracle Life Sciences. The ones who are doing that are the ones that are being most successful. Yeah, I love that. Get, get comfortable being uncomfortable. That's not something people dive into, as is uncomfortableness. But, you know, I don't care if it's industry, politics or even favorite flavor of ice cream. Getting anyone these days to change their mind or change their mindset is really hard.
00;11;18;18 - 00;11;49;09
So getting an industry to collectively think differently, that can't be easy. So what do you see as the biggest challenges to that? And is it that there needs to be some driving force for that? And is that the role Oracle's trying to play? Yeah, it's not easy for sure. All right. So some of the biggest challenges are really the cultures that are existing within and across the industry where people are so busy, right?
00;11;49;11 - 00;12;16;11
They're not set up to work. Cross-functionally The siloed nature that's that's occurring across our industry, even in between clinical care and clinical research, there are gaps. So I think all these different places are causing, you know, challenges in terms of making a difference, getting immersed and taking those risks. People aren't always rewarded for taking risks. So let's say it happens.
00;12;16;11 - 00;12;40;29
Let's say there's a shift in mindset and we're thinking more about leading with knowledge and information and looking at that big picture. What opportunities does that present for both the industry and for me when I get sick? Yeah, no, that's a great question as well. So for the industry, I think we'll be able to actually bring compounds to the to the marketplace more quickly.
00;12;41;10 - 00;13;30;00
Right. For you as an individual or us as individuals, all of us will be able to have more options, both clinical research as a care option. Right? Right now, only 3% of eligible patients participate in a clinical trial. Right. If we're able to take information and put it back in the electronic health record or h.r. System so that doctors can look at it at the point of care and make decisions whether it's about what is your care that they want to prescribe or it's about how are these products impacting you as a patient from a pharmacovigilance or really a tolerability or safety perspective, they're able to adjust very quickly right there on the fly, right?
00;13;30;00 - 00;13;51;29
They'll have more data at their fingertips, as we put it in. And that also could be recruiting patients into clinical trials. Right. So they don't know what's the inclusion exclusion criteria. Look it up. So how can you at their fingertips and knowing that this patient can just walk in the door for these patients scheduled to walk in this week, they're eligible.
00;13;52;00 - 00;14;12;02
Let me make sure that I talk to them about that so that they have other options that will help them get well. Yeah, So it's a good payoff. Your answer to this can be Mike, why don't you just mind your own business, but ask Oracle recently combined their Oracle Health and their Oracle Life Sciences divisions. Why did they do that?
00;14;12;11 - 00;14;37;06
Well, I'll tell you, I won't tell you to mind your own business. This is sort of the the biggest payoff I think we're seeing is movement that we've seen in health care. So the acquisition of Cerner by Oracle was just enormous. And it Cerner, these are your cancer health group is part of it really also was a big deal, right?
00;14;37;12 - 00;15;06;10
Because now we can take what's happening in health, in the clinic, in the hospital, in the offices and combine it with life sciences. Everybody has the same goal, which is to save lives or to increase quality of life of patients. But both of these groups, the hospital systems around the world and the life science companies around the world, they're not connected, right?
00;15;06;10 - 00;15;40;22
They want to be connected. They want to intersect, but they're working in silos, trying to influence each other when they both have the same goals, which is to save lives or help people. And now with Oracle Health and Oracle Life Sciences being under not only the same umbrella of Oracle, but under the same leadership in terms of team of firms, we're able to break down the silos so that we're able to share the appropriate data and information in an open equal ecosystem in bi directional way.
00;15;41;11 - 00;16;09;04
And while these two groups are deeply intertwined, yet this distinct, if you will, there are innovations there that we're looking at that will help everybody that some of the migrations celebrate recruitment, sharing of data, point of care decisions, things of that nature. So it's about turning data into information, that information into insights with some kind of open, intelligent, cloud based platform.
00;16;09;27 - 00;16;39;24
There is the problem, though, of drowning in data, but starving for insight that's applicable to so many businesses across so many industries. How would the ecosystem that you just described keep life sciences customers from drowning in data that is never used for practical effect? They're absolutely drowning in data. There are more data sources existing secondary data sources in the industry and across the world today.
00;16;40;05 - 00;17;12;02
The majority of these like probably 98% of them are not unified, they're not connected, and interoperability is lacking. Credit card companies figured it out a long time ago when healthcare has and we're starting to get there. Training unified platform of data Health data intelligence platform is what we call it in Oracle, backed by the Oracle cloud infrastructure. So you have data that's very sensitive sovereignty of nations, you're using it.
00;17;13;04 - 00;17;58;11
And of course OCI, Oracle Cloud Infrastructure affords the opportunity for security and speed and all these other benefits. So the more of tokenization we could do to connect the charged with other h.r. Claims with patient reported outcomes survey. The more we can do that in standardized ways with the right governance will help our clients sort through this sea of information so that we can and will help them, of course, you know, focus on what's important, you know, and use A.I. to define the trends in predictive analysis, what predicts better or worse outcomes.
00;17;59;01 - 00;18;21;22
So it's going to take time. We're getting there. We're already making a lot of progress, but I think that's now how we're going to help our clients get there. Well, I did ask about the obstacles of changing overall mindsets, but what are the remaining obstacles to actually building and implementing this eco system that you're talking about? Are there remaining tech obstacles?
00;18;21;22 - 00;18;50;01
Are there privacy issues? I mean, what's what's there that's making this a tough job? Not only we drowning in data, we're drowning in obstacles like that. So certainly you know, that's an obstacle of legalities around the world. Cultural changes and mindsets. Like we mentioned, there's governance. Who owns the data? We get data right to the data technology. Then we go back to that for a second.
00;18;50;11 - 00;19;13;28
You know, how do we connect from one system to the other? I do believe there's still 300 EHR systems out there. The interoperability, governance image. I mean, we're just not sure about. Also, we got to kick them off one at a time. And you know what we're doing at Oracle and Oracle Life Sciences is we're partnering with a lot of different organizing that's out there.
00;19;14;06 - 00;19;50;17
You might have seen our partnerships with the video code here. Johnson Labs, from algorithms, Perspectives. We're partnering with a lot of other organizations to help chip away at these obstacles and get to this ecosystem that we're talking about, where everybody wants. Yeah, you know, when you when you list those obstacles, one thing that's not there is resistance by patients, because I think most of us, you know, it's kind of a joke amongst everybody how every time you go to the doctor, you fill out the same forms again and again and again and again.
00;19;50;27 - 00;20;14;15
Clearly, there's not any kind of centralized clearinghouse for data on me as a patient. And I think most of the public kind of What's that? What's your view on meeting patient expectations where that's concerned? You know, isn't that the most important thing right of the whole conversation is putting the patient at the center of meeting their expectations. Okay.
00;20;14;15 - 00;20;41;03
There are a couple of countries where this is already occurring with the patients. The is all in one place. The patient just pulls up their app and they go and it doesn't matter which doctor or hospital you're walking into or what country they're visiting when they're traveling, they have their medical records in their pocket. One of the articles of issues is around privacy, and you might have mentioned this.
00;20;41;16 - 00;21;12;16
So in the US we have hip in Europe yard and this is trying to protect the patient for the right reasons. But we have to and we have to work within these systems to make sure we're able to operate together for the patients. There's nothing more annoying walking at your doctor's office and filling out the same or complaint or consent form or insurance form or whatever it is, you know, and it's certainly something that we need to do.
00;21;13;04 - 00;21;46;07
I think from a cohort perspective, the older populations and I'm not sure where that likes it's at 40 or 50 or 60, I think they're a little bit more protective and reticent about their privacy and their information. Whereas I see the younger generations, they're like, it makes sense to share it all the time. I wanted out less concerned about privacy, and maybe it's because of how they've grown up with the apps, social media, you know, everything's out there, you know?
00;21;46;08 - 00;22;09;17
So I think the trend is here and the tide is turning. You know, we have to find ways to continue to meet the patients and people where they are. Well, I'm sticking with that patient theme. There's how patients are involved or not in research. And we are hearing more about patient centered outcomes in research. It's another kind of mind shift that needs to happen.
00;22;09;17 - 00;22;35;04
How are we moving toward that where we're listening to the patient more and involving them more in clinical research than we used to? And that's that's the next great question. You threw that statistic out there that what, there's like 30% participation? I mean, there's clearly an issue. Yeah, Yeah, for sure. So patient reporting outcomes are typically subjective nature, right?
00;22;35;04 - 00;23;06;29
So by developing different instruments and scales that derive or predict something in might predict undiagnosed insomnia or anxiety, depression might predict of control of asthma, things of that nature. But there's typically surveys that have been validated through different types of behavioral science, a cognitive interviewing techniques, things of that nature, and then putting them out there. Right. And there's pros and there's observables, which are caregivers, right?
00;23;06;29 - 00;23;33;29
So someone caring for an adult relative, they're scales like that around caregiver burden, these sorts of things. And I'll tell you that the FDA has made a concerted effort to focus on patient focused drug development, and they've put these guidelines out there in terms of what they expect as websites companies are going through their clinical trial or clinical development programs.
00;23;34;00 - 00;24;01;17
Right. So I think that was a really great step to say not only open to this, we want it, we expect it. Right. So we've seen some of that, too. Now get your question. How do you do it right. Well, you can go with it. You charge it claims and look at information about the patient. But you also need to go directly to the patient and get their voice so you can do qualitative types of exercises.
00;24;02;04 - 00;24;22;21
For us at Oracle, I think this live of voices two trials where we go out to cohorts of patients who are eligible and we run through issue friendly terms the inclusion exclusion criteria. What do you think? Would you participate or not? What do we need to change here? And there's a whole bunch of other things to expose them to.
00;24;23;04 - 00;24;46;07
And then they tell us just no way, and this is impacting them. Phone calls of various clinical trials that our clients are working on, and they're taking it back to the EMA, the FDA, and say, here's the patient's voice and this is why we're making the decisions so that we're representing what these patients want in our trials. And often it's different.
00;24;46;23 - 00;25;13;08
So that that's one way We're also seeing more decentralized clinical trials. So over the past four years, with all the challenges of leaving one out and going to a site DCT decentralize, some trials have really accelerated in terms of the volume of trials. So so no longer just a patient have to drive an hour or 4 hours or however far to a site.
00;25;13;21 - 00;25;41;10
Now you bring the trial to them. You bring the phlebotomists to their house, you send them the wearable technologies or whatever it is they might need. So you're meeting the patients where they are so that you could increase participation and be more efficient, more productive, and really get it done in a better way. And the last thing I might mention is some natural history of disease registries.
00;25;41;21 - 00;26;07;25
These are registries that occur usually before the product goes into phase two or phase three clinical trial. And this is where you really start to understand what is the natural history of the disease. Most important, rare diseases where it could take years and years to get a count out in development compounded through or me to diagnose the patients.
00;26;08;04 - 00;26;33;01
And it takes too long to do that. So understanding the natural history of disease is critical. Right now we're running a global registry called Guardian, which is in Gauci Disease type two and Type three, and this registry is the Guardian Registry Registries one. We're collecting patient and caregiver information. We're actually developing a new approach and a new ops or so.
00;26;33;01 - 00;27;04;27
We'll have the patients voice. There are no products indicated for type two or Type three. So all the information is being fed back to the clients who have compounds in development for consideration in their clinical trials. And we're working with the International Gaucher Alliance, which is the global patient advocacy group on this registry. So it's a great partnership and it's getting that patient's voice, you know, where it needs to be, which is in the hands of of the compound development.
00;27;04;27 - 00;27;29;14
You mentioned A.I., you touched on that a little bit at AEI has certainly become part of the conversation, thinking about how it is or has the potential to impact therapeutic research and development. What, in your view, is and isn't overhyped about A.I. and the different stages of research and getting drugs to market so much? I make a lot of a lot of hype.
00;27;29;20 - 00;28;10;01
But also there's there's a lot of there's a lot of sizzle and there's a lot of sauce, right this. So you have to look for it and find it. So reading articles about organizations like Genentech and Janssen who are doing what's called Lab in the Loop, right. And a lot of a lot of life science, pharma companies and biotechs are doing this now where they're doing a and they're crossing their existing and other contacts with biological databases to uncover where might there be a match where some combination of a compound or multiple compounds could actually influence some disease?
00;28;10;01 - 00;28;47;05
Right. And then they tested they put it back in. So that's one area where we're seeing a lot of activity with with a for sure, critical trial designs, just looking at feasibility and protocol optimization and to understand where are the patients, how we are and how they're helping with patient recruitment. Where is indentify sites identifying the patients and incorporating dashboards back at the sites to help doctors identify and quickly recruit those eligible patients, or at least to have the conversations to see if they're interested.
00;28;47;14 - 00;29;28;22
Understand diversity of disease using various databases that have social determinants of health to make sure that we're diverse. Once the FDA is draft guidances, which which looked at everything from social determinants and ethnicity to co-morbidities, other demographics, transplantation, patients, etc., etc., etc. real world evidence teams are using it for their literature reviews. Unfortunately, sometimes they come across hallucinations or some false references, you know, show up and therefore you're always going to need this human collaboration to make sure your data is reliable.
00;29;29;03 - 00;29;55;07
And I'd say the last thing my head is pharmacovigilance, where we can go into existing databases, e charts, claims, both structured or unstructured notes, I should say, you know, and pull out information to identify patients who are having issues and report it in some sort of rapid or real time reporting and not wait. So out a major issue?
00;29;55;19 - 00;30;18;15
Well, since the listeners have been interested enough to still be listening, let's reward them by diving deeper into some of those specific technologies for clinical trials. What is Oracle's role in helping with randomization and trial supply management, which I think is also known as interact of response technology? Again, the work being done to that to get to therapeutic breakthroughs faster.
00;30;18;27 - 00;31;04;00
Yeah. Or TSM randomization, trial or supply management and ERP. It used to be called priority and now it's our TSM. This is an area where we've been playing for a long time. Continue to look at our tools for our clients so that they're able to do things that are quicker, faster, more efficiently. And certainly we've invested in a number of new people around the organization in our data product team, which is made up of some phenomenal engineers, you know, and they're investing we're investing significantly in our technologies to bring it to the next level and clients are responding appropriately, which is which is great.
00;31;04;03 - 00;31;30;08
And it's in a scenario where it's going to help clinical trials more quickly and more efficiently. So amazing things are happening. But, you know, I'm never satisfied. So I'm always curious about what the future could hold. I mean, we already touched on A.I., but what trends and technologies are you seeing out on the horizon that are most likely to bring us the kind of health care revolution that we think is possible?
00;31;31;11 - 00;31;55;06
Well, we've talked about some of them, this change in thinking culture for sure. Some of the policy and privacy types of things that we need to to get through. But this is what's not only on the horizon, but is here, right? It's here right now. I'm excited about the things that we're doing with Oracle Life Sciences to get there faster.
00;31;55;18 - 00;32;30;27
You're combining the data, our medical intelligence for our clients, just seeing it all in one place so that our customers are able to leverage it in a way, giving back to a future for physicians to close that gap between clinical research and clinical care. I think that's what I'm most excited about, I suppose. Oracle recently, very recently announced Oracle Health Data Intelligence, which is being called an open intelligence ecosystem or innovation.
00;32;31;09 - 00;32;57;21
Talk about what is that and how that helps life sciences. And researchers love to do so. So first of all, the Oracle Health Data Intelligence platform, it's open. It's open to anyone, meaning that anybody could tap into it, regardless of what industry, what part of the health care industry or working life sciences, whichever system, electronic health record system you're you're using.
00;32;58;06 - 00;33;32;24
So it's really flexible from that perspective that anybody can tap into it. And the data is research ready, meaning it's usable, right? We're form forming it, we're standardizing, and we're harmonizing it in a way that you can go and do the research that you need to do and get the insights and generate the evidence that you need. And this will help in such a tremendous way with the challenges that I mentioned earlier, breaking down silos, connecting disparate data sources, being structured and data that's now usable.
00;33;32;24 - 00;33;59;14
Right? That is that is not usable currently and it's in many formats. So customers will be able to or anyone really can tap into usable data sets from thousands of sources. So that's the other thing anyone can participate, contribute data. We're going to pull in data from a number of different places and again, turn that data into information and that information into insights and that insight those insights into evidence.
00;33;59;26 - 00;34;23;25
So and this will include longitudinal health data, real world data. I didn't define real world data, so real world data is basically any data that is not clinical trial data. It's in the real world, right? So you see that the care that's occurring within the physician's office or hospital that's not part of a clinical trial is considered real world data.
00;34;23;25 - 00;34;48;01
So that's longitudinal health data, electronic health records, patient registries, whether it's natural history or safety, product registries, all that is considered real world data. And all of that will be part of the health data intelligence platform. And this is an API driven ecosystem, which means anyone could access it. As I mentioned before, whether you use an Oracle clinical application or not.
00;34;48;27 - 00;35;16;18
And you can rest assured knowing it's running securely and safely on the Oracle Cloud infrastructure and as you know, OCI Oracle cloud infrastructure, not only is it safe and secure, but it's a military grade infrastructure and it's being used by the Department of Defense. So you could trust it is reliable, scalable, and it's getting the job done. And the health data intelligence platform, as you know, we have it, we're building it, improving.
00;35;16;18 - 00;35;36;17
This is really a big part of our future here in Oracle Life Sciences at Oracle and quite frankly, in the broader industry. Well, great. You know, I got my answers. Thanks for being our guest today, Michael. We'll be watching those, watching for those shifting mindsets and the changes coming to life sciences. Certainly, Oracle seems to be leading the way in that area.
00;35;36;28 - 00;35;53;25
If our listeners want to learn more, though, about what Oracle's initiatives are or if they want to get in touch with you, is there a way for them to do that? You know, first, my thanks for having me on. I really enjoyed the conversation and pretty good and a couple tough questions in there. So thank you for that to join it.
00;35;54;04 - 00;36;20;28
Everyone is welcome to go to my page and connect with me. I try to post relevant things on occasion. So Michael from set of enforcing the Oracle dot com and find the Oracle Health Sub page of the Oracle Life Sciences of the Explosive Alexa Science Stage Armageddon Sounds good. That got it. Thanks again, Michael. And to our listeners, we don't want you to miss any episodes of research and action.
00;36;20;28 - 00;36;49;01
So please subscribe to the show. And if you want to learn more about how Oracle can accelerate your own life sciences research, you can just go to Oracle dot com slash life dash sciences and we'll see you next time. -
What are the best ways to set up public, private, and academic clinical research partnerships? How do we get these public-private partnerships (PPP) to work most effectively? And who should be in charge of what in multistakeholder research collaborations? We will get those answers in more in this episode of Research in Action with our guests Rob King, President and CEO of FHI Clinical; and Dr. Kristen Lewis, Head of Clinical Operations at the Center for Vaccine Innovation and Access at PATH. --------------------------------------------------------- Episode Transcript: 00;00;00;01 - 00;00;22;22
What are the best ways to set up public-private clinical research projects? Where does and should the money for such research come from and who should be in charge of what? We'll get those answers and more on this episode of Research in Action. Hello and welcome to Research in Action, brought to you by Oracle Life Sciences.
00;00;22;22 - 00;00;50;05
I'm Mike Stiles. And today we're just trying to outdo ourselves by talking to not one, but two very interesting people. First is Rob King, president and CEO of FHI Clinical. FHI uses Oracle's clinical trial software for their clinical operations and partner with public entities like PATH, which brings me to Dr. Kristen Lewis, who is Head of Clinical Operations at the Center for Vaccine Innovation and Access at PATH.
00;00;50;26 - 00;01;29;23
I could go through what each of these organizations do just to hear myself talk, But why do that when I have both of you here? So, Rob, tell us what FHI Clinical does. Yeah, I think Mike, so clinical in a contract, they were actually for profit and hearing of a large nonprofit called F8 had three ethically and while we are for profit empathy, our mission is to address unmet research needs and maximum social impact pouring into development of medical treatment around the world.
00;01;30;04 - 00;01;58;20
While we work globally, we tend to focus on the low and middle income country on the whole pharma and biotech client are also include nonprofits and government. Empathy. Well with biotech receive public funding and path having him be one of our client. Appreciate Kristen being here arguing that four years ago and I'm currently the CEO and I'm happy to be here.
00;01;58;20 - 00;02;22;19
Well great. Kristen what about PATH? Yeah, thanks for the introduction, Mike. It's a pleasure to speak with you and Rob today and have the opportunity to contribute to this discussion. So most people listening to this podcast may not be familiar with PATH. We're a nonprofit global public health organization with approximately 1600 employees worldwide. Our headquarters are in Seattle, Washington, and we have offices across the African and Asian continents and Europe.
00;02;22;19 - 00;02;53;00
Some of the locations we have offices in include Kenya, Ethiopia, Senegal, Uganda, Zambia, India, Vietnam, Ukraine. And I could go on, but I'll I'll hold hold it there. Our mission is to advance health equity through innovation and partnerships. We do this with the help of local and global partners by generating evidence, advancing innovation and strengthening local capacity to improve health in countries and communities that are experiencing disproportionate burdens of disease and barriers to well-being, specifically in low and middle income countries.
00;02;53;11 - 00;03;26;01
This includes working in over 70 countries across the African, Asian, Latin American, European and North American regions. Within Paths Center for Vaccine Innovation and Access, we drive the mission of achieving health equity using a three-pronged approach, including developing, facilitating and implementing global market and policy solutions to ensure sustainable supply and equitable access to vaccines. Supporting country led efforts to advance national health equity priorities, and to strengthen immunization system resilience and driving innovation and technological advances.
00;03;26;01 - 00;03;50;20
To accelerate and optimize access to vaccines. Now, this last point is where my work is focus. Thus, during today's discussion, I'll be speaking with the lens of developing vaccines for disease indications benefiting low and middle income countries, and the importance of public private partnerships in achieving that goal. And just to note, you'll note a common thread there in the introductions from both Rob and myself, and that's the low and middle income country focus.
00;03;50;20 - 00;04;15;17
And I think that you'll start to hear some commonalities come into play as we go further into this session. Great. Well, I think what I want to get into here is kind of what you talked about is the value of public private partnerships in clinical research. Rob, give me the honest first reaction that a lot of private companies have when it is suggested that they partner with a public or a government organization.
00;04;15;17 - 00;04;45;18
Is that something that they jump at with open arms or is there any hesitancy? How does that go down? You know, with recently reading an article about one of the first public private partnerships and it was how mail really hit home, like, you know, for most of our listener, what most people won't be familiar with are the initiative around vaccination for diseases like polio and Spanish flu, MENA and rubella.
00;04;46;00 - 00;05;33;19
And we tend to have short memories. And they and the devastating impact they've had on society prior to vaccination and treatment options or with also that treatment developed over HIV and AIDS and then most recently the COVID pandemic. So with that said, you know, private companies maintain the shy away from what we call the triple P public private partnership in the funding limitations that my, you know, government based funding required a lot of compliance when the whole myriad of regulations and public kind of activity may have restricting how and where or how and when fund your, you know, without experience are now horsepower in the public private partnership.
00;05;34;07 - 00;06;09;21
It creates see private companies to engage and may see growth for example will not serve as a prime contractor on government funding work because when you're in the accounting and you're when the regulatory compliance and you'll only see those of normal commercial contracts, therefore they can turn them and be overly burdensome for those companies to pay. And public private partnerships, you have to have an operational model that meets the unique need of that partnership.
00;06;10;03 - 00;06;36;15
And at the end of the day, you really can't you can't get value for society that public private partnerships have contributed to. And Kristen, from the nonprofit or public side, what what is the benefit of partnering with private companies? Yeah, that's a great question. And I think to answer that, I'd first like to highlight some of the major successes when these partnerships have come together.
00;06;37;04 - 00;07;05;23
PATH has played through public private partnerships. PATH has played a critical role in some of immunizations, created successes over the past 30 years in lmics low and middle income countries. This includes developing the world's first malaria vaccine, which has now reached more than 2 million children, eliminating meningitis epidemics in Africa following introduction of the A4 backed vaccine protecting over 300 million children from Japanese encephalitis, vaccinating millions of girls against HPV.
00;07;06;06 - 00;07;33;20
And I could go on. But those are some some highlights. Path has not achieved these accomplishments in isolation. These successes have been catalyzed via public private partnerships models, and they're examples of which the private sector alone may not have been interested in developing these indications. These vaccine indications for low and middle income country use due to financing or budget considerations or constraints or some of the points that Rob made earlier.
00;07;34;00 - 00;08;03;13
However, with partnerships between PATH and private entities, including finance mechanisms for rollout and use of the vaccines in the regions following development, we've been able to champion development and introduction of vaccines that might not usually have generated sufficient interest for the investment that's required for full development. So in a nutshell, public private partnerships are the bread and butter of our work and integral to the goal of achieving improvements in global public health among populations facing economic challenges worldwide.
00;08;03;24 - 00;08;43;19
Well, so it feels like these partnerships would automatically create multiple stakeholders. So, Rob, how hard is it to make sure that the goals and priorities are aligned amongst all these people and stay aligned? First, I think I have a, you know, expectation and the goals are higher for public private partnership and for commercial initiative. You know, eight you public five, there is an expectation that you're going to achieve the goal or outcome and you're held accountable for how those on her spent.
00;08;44;11 - 00;09;27;10
You're not accountable to a or stockholder, but general public. And you know, public funds are unlimited and there are every dollar may account for whatever goal they're trying to achieve. And we're spending public funds a buying or accounting of how this on her being spent and her limitation on this on and how there may not be extra funds or reserve goes back to if those funds start to run low and usually the public entity defines the impact and the work that has to be completed in ensuring that the funding is in place.
00;09;28;01 - 00;09;53;24
And they then tracking the work that the private company may have contractually in their you mean clear terms on what's being delivered and the restrictions that may or may not be around the funding for that deliverable. So I you agree that saying, though, priorities are paramount because of the fact that we're accountable to the end of the day, to the general public.
00;09;54;09 - 00;10;29;01
And Kristen, is there anything on the public or nonprofit side that's done to kind of make sure that projects aren't subjected to red tape or bureaucracies? I mean, I guess there's always going to be some of that, but to the extent that would might slow things down. Yeah, it's a great question, an interesting and insightful one. So Path we work as a clinical development partner and hold sponsor sponsor roles to implement clinical trials and generate evidence to support vaccine licensure, W.H.O., Prequalification and decision making for vaccine Introduction.
00;10;29;11 - 00;10;51;09
And our work spans the entire vaccine development and delivery lifecycle. And with this broad set of objectives, in order to achieve the aforementioned successes, we have worked with the same urgencies and efficiencies as our private counterparts. From a private lens, there seems to be a perception that the public sector does not come with the same development pressures as the private sector.
00;10;51;19 - 00;11;22;13
In other words, there seems to be a perception that the public sector works slow due to many policies or rules or paperwork, or is generally lacking a sense of urgency, if you will. Now, I don't have that experience working in government, so I can't comment on that side of things. However, in my experience working in vaccine development with a non governmental nonprofit for the majority of my career as well as a few years working for a for profit entity, I can comment that the intensity of work at a nonprofit has been similar to the intensity at a private entity.
00;11;22;26 - 00;11;46;09
While the root of the development pressures may be slightly different. The goal is to develop products as efficiently as possible, while also retaining high quality remain in both sectors. For private entities, I believe the term may be, quote, time as money and quote as a driving consideration. While for my work in the nonprofit space, what drives us is, quote, time is lives, unquote.
00;11;46;14 - 00;12;17;20
And that is really the driving consideration. But regardless of those driving considerations, there's still urgency and sense that we need to be as efficient as possible and ensure that we aren't were removing blockages, red tape, bureaucracy as much as possible. So, Kristen, I'm curious, just from your point of view, when the pandemic came down, that was an entirely different animal in terms and the need to get something done and get something done rapidly.
00;12;17;25 - 00;12;48;23
Just how different a process was that? Yes. So I wouldn't say that the process was necessarily different between the public and private side. I would say that we did things across both sectors in a a new way. So the COVID pandemic really brought home how there are many similarities between the public and the private sectors. Not everything differs according to operating model.
00;12;49;01 - 00;13;14;16
In fact, during the pandemic, the global public health and product development safe spaces, regardless of the type of sector, were going through the same waves of initial shock and uncertainty and how to continue the trials during the very initial stages of the pandemic considerations in terms of the risk benefit tradeoffs of operating non-covid interventional trials during that time, and depending on the type of trial availability of remote technologies and a product's importance to saving lives.
00;13;14;27 - 00;13;38;24
We had to take into consideration different ways and methods for making sure that those Non-covid interventional trials were completed. We also were involved with needing to identify new ways of getting the work done, which included catalyzing a more definitive shift towards identification of local partners that were in close proximity to the trial locations for ease and trial oversight and management.
00;13;38;24 - 00;14;04;12
Implementing remote solution for activities such as source, document verification, remote training, remote site assessments and other types of remote activities, identifying how to get supplies or equipment to the sites ahead of study. Start with supply chains being disrupted and finally determining how to maintain the trials and keep them running once up and going while continuing to deliver with with high quality and ensuring participant safety.
00;14;04;24 - 00;14;30;10
So from Passent, given our work is primarily focused in low and middle income countries, many of the challenges faced in the private sector high income market were further exacerbated due to the relatively slower adoption or uptake of technology surgical clinical trial advances. And this experience was important as it pushed for adoption of technologies that had been previously questioned due to fear of loss of data or other concerns, as with other areas of our lives.
00;14;30;11 - 00;14;56;28
COVID really helped to push the envelope in terms of finding new efficiencies and ways of getting things done. Rob When a partnership like this comes together, I guess this goes along with the expectation setting side that you touched on earlier. How are the roles and responsibilities assigned? I say that in the triple P or public private partnership it really different in that respect as compared to commercial partnership.
00;14;57;25 - 00;15;41;11
You know, the earlier the public finds an objective and a private is to execute that. Now the public entity may only outsource part of the work because they already have the skills and knowledge and the resources themselves. And then they will only outsource the pieces that they can't do themselves. But I think the main thing to keep in mind when a public private partnership is that the public entity, a steward of the public interest and liability and accountability for that public interest lies with them regardless of whether they outsource or not to a private company.
00;15;41;11 - 00;16;05;12
So I feel bad for Kristin and the pressure that they have on them as a public entity compared to myself and her private empathy, where I don't necessarily feel the same pressure we have. Some people might think that the role of public funding is just to get the project more money. You know, we tell you what we need, you go get it for us, and that's your role.
00;16;05;12 - 00;16;28;04
How true or not true is that, Kristin? Yeah. You point out an important consideration for pairing public funding with private resources. There is the potential that private entities may believe that we, the nonprofit, will help bring in key funder resources to augment a development program regardless of their development goals, in alignment with the use of the product in low and middle income countries.
00;16;28;13 - 00;16;54;25
However, in order to mitigate the potential for this misalignment within PATH, we focus on partnering with private entities. When there's clear alignment between Path's mission and the mission of the private entity. Additionally, this alignment has to be in writing agreed to via contract. It includes global access agreements for product availability and use. And so in summary, my experience has been that it's not true that the goal of public funding is to get the project more money.
00;16;54;25 - 00;17;16;10
The goal of public funding is to achieve an outcome that might not otherwise be achievable, given lack of private interest without the public funding to come in and co-fund an objective that benefits low and middle income countries. So we've got public and private represented on this episode with the two of you. What we don't have is someone representing the academic side.
00;17;16;10 - 00;17;45;27
Rob, do you have any thoughts on the role that that third leg of the stool plays or should play? Yeah, you know, there are academic institutions that also have private public anything in and out where I have a lot of admiration for the role of peer academia, Both public and private institutions rely on academia being a catalyst for innovation and providing health very specific areas of research.
00;17;46;24 - 00;18;13;00
There are a lot of academics out there. They're doing very research and I never know when that point of time in in hand. So at every level we rely on our advisory or academic consultant to keep us informed on very specific events or therapeutic topics. And this plays into whether the research into them or not that we intend to do.
00;18;13;10 - 00;18;51;08
And there's a large portion of investigator and key opinion leaders involved in research actually come from academia. On the flip side, academia also relies on public private partnership to bring their ideas into the research environment because they lack the funding to paint the vision or the technical knowledge on how to bring that idea to the next step. You know, I think the example that perhaps a lot of people have heard of are the bar industry days and Loreal, which is the Biomedical Advanced Research and Development Authority.
00;18;51;24 - 00;19;35;13
They host annually this event where people come in for ideas, for collaboration in partnership with US funding, and so they have it. So for them, the novel idea that aligns with the interests of the US government and they get the opportunity to collaborate with other companies that can bring that into fruition as well with funding behind it. So I think there are a lot of opportunities out there for academics to bring the right into fruition, but we have a great job of sort of pulling them in the right direction.
00;19;35;28 - 00;19;58;14
Kristen, I have to tell you, as a as a layperson, I kind of picture this three way partnership, and the first thing that comes to mind is that's a lot of cooks in the kitchen. So it's kind of amazing to me that anything gets done or gets done in kind of a timely manner. What are the essential ingredients of a truly successful collaboration in your mind?
00;19;58;26 - 00;20;34;24
Yeah, it's a very good point. And I will add on to Rob's comments regarding academia that academia is a very important partner in this setup. Academia generally is part of these partnerships. And so there are I would, as you put it, a lot of cooks in the kitchen when we're bringing these projects together. And the short answer and how we make these successful is to never underestimate the value of careful pre-planning and preparation and setting up the partnerships, including mission alignment, alignment in the partners scopes of work and roles and responsibilities.
00;20;34;25 - 00;21;11;19
I think Rob alluded to that earlier. And the Seven Seas of collaborations jump to mind, clarity of purpose, concurrency of mission strategy and values, creation of value, connection with purpose and people, communication between partners, continually learning or a growth mindset and commitment to the partnership. In addition, it's also important to lay a solid foundation underlying all of that of respect, trust and finding a balance between humility and confidence across the partners to make sure that everybody is partnering fairly and with trust and in good faith.
00;21;12;01 - 00;21;37;07
Yeah, you know, I don't want to start a fight, but who is largely responsible for big innovations in clinical health? I think the public gets the impression there are private scientists huddled together in one lab, and then government scientists huddle together in another lab, probably in D.C. That's not really the way it is, is it, Rob? I mean, how are the big, impactful innovations truly getting developed?
00;21;37;17 - 00;22;07;29
Yeah, I'm one I answer that question in the obvious here. I mean, there when we all work together and leverage the strength of all of our partners. I honestly do think that commercial or private things are faster innovation, but they have a feel and reward system. They're always our innovation, a profit making endeavor. I mean, why not? You have a good eye and you want to be recognized and rewarded for it.
00;22;08;12 - 00;22;36;24
But bringing innovation in areas where the opportunity for regular recognition and reward is not so great. And that's where public private partnership come into play. You know, as a global community, it's in our interest to innovate in low reward scenarios because the knock on effect is that the problem is not spread and that it allows a particular community to or region to prosper.
00;22;37;13 - 00;23;00;15
And so therefore, if people prosper, they're less likely to mean in the future and we can maximize their contribution for the greater good. Yeah, but Rob, when it comes to public health, people do seem to put the bulk of that responsibility on government. Like people didn't demand an answer to COVID from Pfizer. They demanded it from the White House.
00;23;00;15 - 00;23;29;27
So is that fair? I think fair and yet a moral issue that we can do a whole nother podcast around. So, yeah, but, you know, human empathy and theoretically the government are there to serve the public and the public good through taxation and donations. We expect the instinct to step up when the need arises. You know, the public can't hold a private company like Pfizer accountable in a crisis.
00;23;30;13 - 00;23;58;14
And then the obvious thing here is they hold the public entity responsible. The only problem is we pan who fund our public entity with a little support if possible, or we lose the funding that's already there with a whole myriad of special interests. We don't leave a whole lot left in crisis. We're also very bad at funding the future, whether it's for crisis or innovation.
00;23;58;27 - 00;24;25;25
We're not people that really think ahead, sometimes have public empathy, have to scramble to reallocate funds, and they usually can't staff up or get resources in place quick enough. And they turn to commercial companies that really have no restriction on growth and simply eat the money and make it happen. Rob What's the most gratifying thing that's come from working with Path from your perspective?
00;24;26;17 - 00;24;57;14
Well, I'll make this short with Sweet. We know toward the beginning of our path and we'll have similar missions now. Path being a public entity, hailing here for the greater good and not really for a reward or profit. Who? I don't know. But I feel I feel better about myself and my company associating and working with Light Path.
00;24;58;00 - 00;25;22;15
And Kristen, what keeps you bought into the whole public private partnership model? Well, it's it's that it's a factor that the model is effective in bringing new life saving interventions to low and middle income countries. So for me, it's the advancement of the public health mission and being able to efficiently facilitate implementation of health interventions for low and middle income income countries that wouldn't otherwise be available.
00;25;22;16 - 00;25;42;26
It's the ability to have a true impact to save lives. And this partnership model is is critical in making that happen. Yeah, but it can't all be gumdrops and rainbows. So what are some of the challenges as or wish list items that you both feel still kind of need to be addressed when it comes to the partnerships around clinical research?
00;25;42;26 - 00;26;18;16
First Rob, then Kristen how I think we can do a better job of building trust and sharing intelligence even in public private partnership. There in Singapore. If trust and holding on the information that can be of mutual benefit. And I personally would like to break down some of the barriers, you know, a key concept in public private partnership in the best value and in most cases that require public entity get like three quotes for some of activity or contract.
00;26;19;02 - 00;26;44;17
And then you have to justify why you can go with it. So we all know that paper is not always better, and I would like to see us define value in more ways than just cost. Also think they're alive and healthy. It can be shared around best practices of Kristin and I belong to a group that's publicly funded that share best practices.
00;26;45;07 - 00;27;25;20
But you know that sharing of best practice has been limited with sort of all that culture of caution. So I'd like to see more sharing and the assumption of positive impact on our party. And I think we held out a lot during the COVID pandemic, and I applaud that. I hadn't felt the call center for a large government project, and we had to do it time and when I reached out to a technology company to help me fill up that call center, the question was, how much are you going to pay me or what kind of, yeah, how quickly you need it.
00;27;26;12 - 00;28;06;15
And then we literally are without contract, without much, especially around term. And they phone up in record time and we work the other stuff out on the back end to mutual benefit. And I know that we can't always do that, but it shows you what possible. And Kristen, what gets your goat? Yeah, I guess there's two points that jump to mind in the first is that we have some more work to do and in terms of sustainable capacity development to ensure that the ground that we gain in facilitating research in low and middle income countries continues to be built without the loss of human or material resources that are built out for trials.
00;28;06;27 - 00;28;26;16
How do we do a better job of sustaining capacity that's been built following the completion of a trial or a set of trials at sites that we've invested in? That's an area that many folks are putting thought into these days, But I think we have yet to identify a solution to that. And I think that's that's something that we can do, do better at.
00;28;26;16 - 00;28;56;00
And I know we will. It's it's a work in progress. And then the second thing is the concept of equitable partnerships that needs additional consideration and support. And I think back to Rob's comment about assuming positive intent and working in good faith, there's a focus now on on transferring leadership and ownership of much of our clinical development work to the regions that are participating in the work so that they're really co-creating and co owning the development work in the development space.
00;28;56;08 - 00;29;17;00
While COVID helped to catalyze that shift, there's still some more push that we need to do within the global public health and development community to make this shift really, really be adopted and occur. And we have a bit of a way to go in terms of fully embracing the models that are led out of the regions that our products serve.
00;29;17;16 - 00;29;38;27
And I believe that the public private model and partnership is an area where we can help to facilitate this in the future. You know, I'd probably be remiss if I didn't ask about the role that you see technology playing and being maybe that fourth partner in clinical trials. Rob, I know you use Oracle's clinical trial Solutions. What does that bring to the table?
00;29;38;27 - 00;30;25;07
So I think, you know, you're in the COVID pandemic. Technology was really a shining star and allowed some things that we probably couldn't done earlier by embracing technology that people were perhaps hesitant to use before. So I think that certainly around Oracle, we were able to use many of the Oracle platform during the COVID pandemic. I think my favorite story, and people probably heard it before, I apologize to anyone hearing me repeat, is that I think how clinical it have at home, even you're a platform without join and so joined right before the pandemic and you're all now on my whiteboard.
00;30;25;16 - 00;30;50;07
My ideal platform for data collection analysis and sharing with other and a former colleague of mine who we recently joined Oracle dropped by the office and we were hanging out my office and he looked at my whiteboard and he said, What's the Oracle Product Development Plan doing on your whiteboard? I said, Well, that's not the Oracle product development plan, that's my plan.
00;30;50;18 - 00;31;21;25
And he said, Well, that exactly met what we're doing right now. And that was in of our use of clinical one. And, you know, just hearing differently, you know, what I had in mind and what the Oracle developer had in mind were the same. I don't think anybody with smart irony when they coming in the gene at that time drove innovation and all the partners on that, and it came at just the right time.
00;31;22;12 - 00;31;53;20
And Kristin, are you surprised by or frustrated by the technology capabilities that are available for your endeavors and what you're trying to get done today? Yeah, I'm excited for trial platforms in low and middle income countries to have the chance to further adopt technologies that have been utilized in other regions. I would say there's been some reluctance in adoption of the technologies that have been commonly utilized in high income country settings for some time, but that COVID has really catalyzed adoption of many of those.
00;31;54;22 - 00;32;16;19
There has also been some backsliding in use of those technologies since COVID. The urgency of the COVID vaccine development cycle more or less ended. And so what I'm excited for is that there was a push during COVID. We've seen it work in the past and that there's the potential for continued adoption of these solutions, such as these saucy diaries Pro ET cetera.
00;32;16;28 - 00;32;44;20
As we work through the challenges with implementation of those technologies outside of high income country settings. So there's there's a little bit of work to do in terms of adoption. But I think we're we're getting there and I'm excited to see the field further embrace those technologies. Well, it's great to hear about partnerships like this and what's increasingly becoming an accepted model for how we can get better results for people faster and for more people.
00;32;45;00 - 00;33;08;13
A lot of our listeners may want to learn more about what you've been talking about and what you do. So do each of you have a way they can do that or even contact you? How about you? Rob Yeah, so feel free to reach out to me quote unquote dot com. And I'm also only in and happy to sort of brainstorm with anybody.
00;33;08;21 - 00;33;39;20
We sort of can move the idea of public private partnership even farther and Kristen yeah our websites available WW w path dawg and it provides additional information on path and what we do and I'm also on LinkedIn then can be reached via that platform Perfect well if you want to see how Oracle is accelerating life sciences research and how it might be able to do that for your work as well, check out Oracle.com/lifesciences
00;33;40;00 - 00;33;58;18
Also be sure to subscribe to this show and we'll be back next time for Research in Action. -
How can patients and their families become more integral in the clinical research process? How can patient-led research become more accepted in the scientific community? How are inspiring groups forging new, collaborative paths for science and medicine, and reshaping how medical research is conducted? We will tackle those questions and much more in this episode with Amy Dockser Marcus, a Pulitzer Prize-winning journalist and author of the recently published book, “We the Scientists: How a daring team of parents and doctors forged a new path for medicine.” Amy is a veteran reporter at the Wall Street Journal and won her Pulitzer Prize for Beat Reporting in 2005 for her series of stories about cancer survivors and the social, economic, and health challenges they faced living with the disease. She has covered science and health at the Journal for years, and she also earned a Masters of Bioethics from Harvard Medical School.
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Episode Transcript:
00;00;00;00 - 00;00;24;19
How can patients and their families become the centers of research? What is open science and who are citizen scientists? We'll explore those questions and more on this episode of Research and Action in the lead in. Hello and welcome back to Research and Action, brought to you by Oracle Life Sciences. I'm your host, Mike Stiles, and our guest is Amy.
00;00;24;19 - 00;00;48;22
Dr. Marcus That's right, that Amy Marcus, the Pulitzer Prize winning journalist, reporter at the Wall Street Journal, a Pulitzer Prize, was won for her series of stories in 2005 about cancer survivors and the social and financial challenges of living with cancer. Her beat, as you would imagine, has long been science and health. And she holds a master's of bioethics from Harvard Medical School, and she's an author.
00;00;48;22 - 00;01;04;26
Her book is We The Scientists How a Daring Team of Parents and Doctors Forged a New Path for Medicine. So this should be interesting as we talk about collaborative, open science and the rise of citizen scientists and patient led research. So thanks for being with us, Amy.
00;01;05;01 - 00;01;06;22
I'm happy to speak with you today.
00;01;06;22 - 00;01;26;29
Great to have you. In your new book, you take readers through some really, frankly, heart wrenching experiences that patients and their families have gone through with a rare and devastating disease called Niemann-pick. Hopefully I'm pronouncing that correctly. Tell us about the book and that disease and what fascinated you about this story.
00;01;27;14 - 00;02;01;21
The origin of the book really is a personal story, which is my mother got diagnosed with a rare type of cancer. And when I tried to do research on her behalf, I started to learn how challenging it is to develop drugs for rare diseases. After she passed away, I took some time off from the Journal. I had a research grant from the Robert Wood Johnson Foundation and I started traveling around the country looking to see if there were new models that might accelerate drug discovery.
00;02;01;29 - 00;02;25;21
And during the course of that research, I was introduced to a group of parents whose children have this rare and fatal genetic disorder, NIEMANN-PICK type C disease. It's a cholesterol metabolism disorder, so the cholesterol doesn't get out of the lysosome and that compartment in the cell and it starts to build up and it causes all kinds of problems.
00;02;25;21 - 00;02;52;12
And the children eventually lose the ability to walk and to talk and to feed themselves. But the parents that I met wanted to do something novel. They had found a group of scientists and researchers and clinicians and even some policymakers in the government that wanted to work together as partners and to see if they could accelerate the search for a cure or an effective therapy for an epic disease.
00;02;52;19 - 00;02;58;11
And they let me follow along during the course of that partnership for over ten years.
00;02;58;24 - 00;03;05;24
That's amazing that you got that kind of insight. And what did you learn over the course of that ten years?
00;03;06;22 - 00;03;34;15
Well, I was really interested in how they saw the production of science in a different way. They all wanted to try to save or extend the children's lives The disagreements lay in. How do you go about prioritizing drugs? What amount of risk is a patient or a patient's family willing to take compared to the level of risk that a doctor or scientist wants the patients to take?
00;03;34;15 - 00;03;54;14
These sorts of tensions arose, I think, in part because they were modeling a new method of where the patients expertise was considered as valuable or even at the center of this of this project. And that's not usually how it is.
00;03;54;14 - 00;04;09;09
But that's rare, right? I mean, in our in the culture of our health care system, it's not really common that the patients input or the patients families input is invited at all.
00;04;09;19 - 00;04;34;11
Yeah, I think that that you're right about that. I mean, the traditional way of setting things up is that the scientists devise the hypotheses and they then construct trials in conjunction with clinicians and sometimes with pharmaceutical companies, of course. But in this particular collaboration that I was describing, the drug was not in the hands of a pharmaceutical company.
00;04;34;11 - 00;04;59;06
It was widely available. And so the partnership was truly about, you know, going to be conducted at the NIH. And therefore it gave the parent and the families, I think, more leeway to do this experimental idea. What if we all recognized each other's expertise? What if we all saw each other as equal partners? What if we got to weigh in?
00;04;59;13 - 00;05;20;24
Not in once. You've already set up the clinical trial, but at the very, very outset, when you're simply going through the scientific literature to come up with potential compounds, when you're thinking about what might work, when you're trying to prioritize what to do first, second and third, all of those things where patients don't always have a voice. But in this case they really did.
00;05;21;07 - 00;05;43;16
You know, we just had Hilary Hannah Ho on the show. She's secretary general of the Research Data Alliance, and we talked about open science and open data and how important all that is to getting the scientific breakthroughs that will actually help people and get to those breakthroughs faster. But open science can kind of be polarizing. There's some confusion around what exactly it means.
00;05;43;23 - 00;05;48;14
How would you define or describe open science and citizen scientists?
00;05;48;27 - 00;06;34;22
Yeah, I think that's a really good point, that there isn't one sort of accepted name and that there are many names and people use different phrases when they're thinking about different things. For me, I used the term patient LED research and I often use the term citizen science. And what I meant by that was, again, what we've been talking about from the outset, which is a recognition that the patient, the patient experience should be at the center of everything, a recognition that the patient and the families are experts, that they have the ability not only to be beneficiaries of scientific knowledge, but also creators of scientific knowledge.
00;06;34;27 - 00;06;46;15
And to me, that shift the idea that you can be a creator of scientific knowledge is the fundamental one that needs to happen if we're going to really reach the goals that I think we all want to reach.
00;06;46;29 - 00;07;11;10
So here's something we highlighted in your book. Quoting here Science is inherently a social enterprise. Yet too often scientists operate behind closed doors, removed from the very people they intend to help. That's struck me as kind of a mike drop statement with a lot of truth to it. But did the pandemic change anything? Was the work still removed from those patients on ventilators and ICU?
00;07;11;20 - 00;07;52;04
So I do make a point in the book to draw some parallels between the various patient led research movement experiences that I describe and the COVID 19 pandemic, and in particular the group of patients that call themselves long COVID patients, where they're suffering symptoms for many, many months. I argue that COVID allowed us in real time to to recognize that anyone can be an expert and that now that is something that it was easier to see during the pandemic because there was a novel virus, there weren't established experts yet.
00;07;52;14 - 00;08;25;28
And so while doctors and scientists and the government were scrambling to try to help patients, I think they also saw themselves for the first time as part of this effort to understand the disease. Together, there wasn't already an understanding of COVID 19. And so what I say in the book is that we can draw from from that experience and sort of take that part of it forward where we say patients should be at the center of things.
00;08;26;06 - 00;09;07;01
Patients are experts. Patients are able to identify things that many scientists or doctors didn't have time to recognize because they were they had to focus on trying to save lives and, you know, working in a vacuum at that point. So there also was a sense of urgency. Like one of the things that I was struck by during the pandemic as a as a science reporter was that scientists were able to put their papers online right away on these websites before it had gone through the full peer review process because it was recognized is so essential to get this information out there as quickly as possible.
00;09;07;09 - 00;09;29;16
And everyone understood that maybe there were going to be some mistakes. It wasn't fully vetted, but it was out there. Not only was it publicly available to the doctors and scientists who are also studying it, it was publicly available to patients and people who are simply interested. And long COVID patients organized themselves, did research on themselves, and they also published their papers on these websites.
00;09;29;16 - 00;09;43;22
I think those types of models where patient researchers can be contributors and can benefit from the information to fuel their own research, I think that should move forward and is it shouldn't be just a relic of the COVID 19 pandemic.
00;09;44;07 - 00;10;05;03
But what isn't there a risk of chaos a little bit? Because we're always told, hey, whatever condition you have, don't go Googling it on the Internet. You'll just go down a rabbit hole and, you know, worry about all these conditions that you may or may not have. So what is the risk of, like you said, mistakes and wrong information being published?
00;10;05;13 - 00;10;27;11
Well, even the traditional peer review process in science publishes papers that turn out to have mistakes in them. Papers are retracted all the time. And there is a well-known phenomenon that peer reviewed papers sometimes the results can't be replicated. I mean, that's the problem for science. I don't think that's a problem just for having patient researchers get involved.
00;10;27;28 - 00;10;54;27
I also think that the advice not to Google something is both old fashioned at this point and probably unrealistic given that almost all of us are connected in some way through the Internet. My sort of idea, rather, is that let's use the Internet and other methods to become better partners. Let's share good quality information online that people have access to.
00;10;55;06 - 00;11;20;20
Let's form partnerships where we can collaborate, where among experts, the people that I was talking to and interviewing and spending time with the parents, they weren't saying, Hey, we're trying to go it alone. We know everything. No, the opposite. What they were saying is we have very relevant and valuable information. We are experts because we live with this disease and we know what level of risk we're willing to tolerate.
00;11;20;20 - 00;11;43;28
And we do our own research. But we need partners who can also help us fill the gaps where we don't have knowledge. We want to collaborate with scientists, we want to collaborate with clinicians treating our children. We want to collaborate with government scientists who have access to data and and robots and things that we're not going to have in lab equipment that we don't have access to.
00;11;44;06 - 00;12;02;19
So no one's saying, go down a rabbit hole by yourself. What people are arguing is let's find ways to pool information, and by pooling everyone's information, we can sort through more quickly what's good, what we think is good, but might turn out not to be good later. And what can benefit all of us.
00;12;03;04 - 00;12;20;02
Yeah, and from a technology standpoint, gathering that data and organizing it and working with it is becoming more possible than ever. COVID should have scared our health system out of its mind. Did it? And is that leading to any systemic changes in science and health?
00;12;20;15 - 00;12;46;19
Well, I'd like to focus on what my book was focusing on, which is can a group of patient activists and scientists and clinicians and government policymakers working together make changes to the system? And I think the answer is yes. You can make changes to the system. The patient researchers that I was talking to and the families I was talking to, they built on activist patient work that had gone before.
00;12;46;19 - 00;13;10;06
And there have been responses in the past. HIV activists were able to influence the FDA to pass the accelerated approval rule that now allows drugs to be approved more quickly. And I think that, you know, compassionate use program that FDA has the patients in my family, the patients in my book and the families benefited from that as well.
00;13;10;17 - 00;13;48;01
So there have been changes along the way. But I think what my book is arguing for, and I think this message came out of the COVID 19 pandemic as well, is that even with all the changes that have been made in the past, the patient experience is still not at the heart of the system. And I think that's the message that all of these families are saying put the patient experience at the heart of things, and then you will see that the system, when you configure the system around the patient centric experience, you'll see that it will work in a different way and an I think, a better way.
00;13;48;02 - 00;13;50;02
But we need to run that experiment.
00;13;50;17 - 00;14;12;20
So we mentioned the concept of citizen scientists. That's what we've been talking about. These are people that pursue what they pursue, driven by mostly love and urgency for their kids, which is just a whole different level of motivation than most researchers have. I think you have a few stories about, you know, people like Chris and Hugh Hempel and and some others that went through this experience.
00;14;13;02 - 00;14;34;21
I want to make a point here that I think also is really important for people to understand who are listening to this. The parents in my book and you know, you cited Chris and Hugh, they were definitely among the pioneers who did this. And there was Phil and Andrea Morella, and there were also Darrel and Mark Poppea who are who are part of this, too.
00;14;34;21 - 00;14;57;29
And many, many other parents. I mean, the Parseghian Research Foundation and the National Niemann-pick Disease Foundation, all family driven. The people who are doing this. Yes, they are driven by their love of their children. They are driven by a sense of urgency. But they're not going to the FDA and saying, Hey, please pass and approve a drug because we love our children.
00;14;58;05 - 00;15;24;05
Please pass and approve a drug based on our emotion. No, not at all. They want to give effective drugs to their children. What they are saying is we are creating scientific knowledge and we think that that should be part of this approval process, that should be part of the drug development process. I just want to give some examples that I cite in the book where the parents were creators of scientific knowledge.
00;15;24;24 - 00;16;07;11
You had parents who read the scientific literature, published scientific literature, called up. The scientists interviewed the scientists came up with hypotheses themselves that they proposed to scientists, contributed to the two scientific experiments, coauthored papers that were published in the peer reviewed scientific literature. You know, went to the NIH regularly to have meetings where they helped contribute to assessing and prioritizing which compounds should go first in terms of advancing them into clinical trials, contributed their thoughts on the risk benefit analysis in devising the clinical trials.
00;16;07;22 - 00;16;34;28
One of the parents went to an FDA sponsored workshop for how to file an orphan drug designation, which is part of the approval process and the long process to getting approval for rare disease drugs. And went to the workshop, participated in the workshop, presented scientific data to the regulators, met with the regulators, and earned an orphan drug designation for one of the compound Cyclodextrin that got moved forward.
00;16;35;07 - 00;16;46;24
So yeah, they have a sense of urgency and yes, they love their children and want to save their lives, but they're producing real scientific knowledge and I really hope that that people take that message away from reading the book.
00;16;47;10 - 00;17;08;15
So those are great examples of exactly what citizen scientists do that sets them apart from just patients who are not doing that level of research, that depth of research. You talk about Chris Austin and the book, and I'm going to read another quick excerpt here, The Promise of Genetics to Deliver new interventions, new drugs and new treatments for patients is not going to happen.
00;17;08;15 - 00;17;27;28
Chris told his boss, unless there's some way to get through the valley of death. Francis gave Chris a green light to pursue his vision. So the boss in that excerpt is former National Institutes of Health director Francis Collins. What is the Valley of Death and Chris's role in citizen led research?
00;17;28;06 - 00;17;54;21
Great. No, that's a great question. So Chris Austin is a Harvard Medical School trained neurologist, also with a background in genetics who worked at pharmaceutical companies as well, and then found his way to the niche where he worked for Dr. Collins and became also a director of one of the institutes at NIH called Ed Katz, the National Center for Advancing Translational Science.
00;17;55;06 - 00;18;23;29
And one of the sort of green lights he got from Dr. Collins was to set up a lab that would have robots that were sort of at the same type of robots that pharmaceutical companies have that would work around the clock and could rapidly screen drugs to try to find compounds that might work for diseases. And what Chris Austin's idea was is that let's screen these vast libraries.
00;18;24;04 - 00;18;50;06
Let's find some drugs that might be promising, and let's also find patient partners. Let's find scientist partners, and let's then try to take all this data and move it forward together. One of the hypotheses that Chris Austin said he had as a scientist was can drug development go faster if patients and families are part of that process from the very beginning?
00;18;50;18 - 00;19;17;02
And one of the things that Chris Austin was trying to get around is this valley of death, which is this, you know, where compounds kind of go to die. You have a great idea as a scientist. But how do you get that idea from the bench to the clinic and to a patient's bedside? And the Valley of Death is just all the various obstacles that end up making it hard to develop a drug.
00;19;17;13 - 00;19;39;21
Some of it can be scientific. You know, you test it in a in a mouse or an animal, you test it in the lab and it turns out to be toxic for the cells or the amount of drug that you need to give to a person is so high it's not realistic or a drug company decides they want they don't want to put any money into it anymore or it gets or a drug company gets bought and they don't want to pursue it anymore.
00;19;39;21 - 00;20;02;08
And there's a million things that happen in the Valley of Death. But Chris Austin's vision was if we can involve patients and families as partners, along with scientists and drug developers and government officials from the beginning, maybe we can get things out of the Valley of Death, or maybe we can fail faster and find the successful compounds more quickly.
00;20;02;25 - 00;20;22;23
Yeah, a big takeaway from your book is the need to build bridges between science and citizens. But and we talked touched on this a little bit. You can't sacrifice scientific rigor or safety. So what are the challenges to building these bridges? What's holding that process back, especially when it does come to drug discovery and clinical trials?
00;20;23;09 - 00;20;47;05
So I think that there is a variety of issues that make it challenging to build bridges. For one thing, there's often a tension between, you know, people who are sick or are advocating on behalf of people who are sick, who really want to focus on the here and now. They they really need something to help their loved one right now.
00;20;47;19 - 00;21;22;19
And often, you know, clinical trials are an experiment. And when you enroll in a clinical trial, you're told this is not designed for the benefit of you. This is designed to benefit future patients. And therefore, it's not a treatment and it's not the equivalent of clinical care. And that can be a source of frustration and tension. And often also when research crews are doing research, they weigh the risk benefit assessment of moving drugs forward differently than people who are trying to you know, solve a problem now.
00;21;23;00 - 00;21;48;14
So I think that and that came up in this partnership in my book. It came up in this partnership in my book a lot. And yet I think each side was able to get a sense of what the points were, what the what the tensions were. But again, in my opinion, one of the ways that they overcame this divide was by both sides saying patient centric medicine is the way to go.
00;21;48;15 - 00;22;16;29
Patient centric science is the way to go. There are ways to collect data in a rigorous manner that can both benefit patients now and also not stop you from insights that will lead to benefits in the future. There are ways to come to terms with that. Some people have a higher acceptance of risk than others. I mean, we see movement towards that already right now.
00;22;17;01 - 00;22;23;01
I think that one of the messages of my book is to try to accelerate that even further.
00;22;23;25 - 00;22;37;19
Well, to that point, you say in the book, government and agencies like the FDA and NIH have a vested interest in helping these science and citizen partnerships succeed. Do they understand that? And what role should government be playing to move this forward?
00;22;38;01 - 00;22;57;01
Well, government is not one person. You know, so but I think that the book shows that there are people in the government who were partners with the patients and the families and the scientists and the clinicians. I mean, this whole book is about a partnership. And Chris Austin, although he's no longer in the government, he left the government.
00;22;57;10 - 00;23;28;05
He was in the government at the time, and he was a partner with these people. So I think that the government has shown in the book that, you know, and outside of my book, obviously interest in investing in new ways to do science, interest in investing in new ways to accelerate science, the government is supposed to represent the interests of the people, and the people's interest is in being healthy and in and trying to find solutions for drugs.
00;23;28;14 - 00;23;56;15
So in the book, I do talk about how the patients and the families in my book were able to directly talk to FDA regulators. Some of the parents went to workshops that the FDA was sponsoring. They had conversations with FDA regulators. I think those types of workshops are really novel and they really are fruitful because they allow the families and the patients to really think like scientists and to produce science as they can and should do.
00;23;56;16 - 00;24;21;16
They want to produce science. And I think also one of the messages that Chris Austin gave at representing the NIH was that the NIH is here to be your partner, and we're open to coming up with novel ways of accelerating science. So I think that there's there's openness to doing this, but of course, always more can be done.
00;24;21;17 - 00;24;51;16
I mean, patients have a sense of urgency, and that's the message that they bring to the government all the time. I mean, in the book, I, I describe FDA advisory committee hearings that are held when the FDA isn't sure about the data and they want to have a public hearing about it. And many of the parents and families showed up and gave testimony not just about their thoughts and their opinions, but about the data that they had gathered, the science that they were generating, that they wanted to share with the FDA and be heard.
00;24;52;00 - 00;25;16;13
What role does Rules Framework's guidelines play and what we're talking about here? I think you even your former advisor, was part of a group of scientists that worked on this framework. And the platform for patient led research, I think was spearheaded by that advisor, former advisor and a group of scientists. What's the infrastructure that needs to be put in place for this to work?
00;25;17;08 - 00;25;46;03
So, yes, So the advisor that you were referring to, Effie Diana was my advisor in my bioethics program and she does a lot of pioneering research on patient led research movements. And she and a group of collaborators, scientists and, and social scientists and clinicians and, and policymakers got together and tried to devise what they called a new social contract.
00;25;46;13 - 00;26;14;17
What they argued is, is that patient led research is a novel form of research that doesn't fit into the traditional regulatory standards that have guided, you know, clinical trials and human subjects research up until now. And that's because the traditional methods of regulation are based on the idea that scientists are going to be leading the research and doctors are going to be leading the research.
00;26;14;26 - 00;26;42;04
And that still is the traditional model. And they usually are leading the research. And in those cases, they often have more information and more power than the traditional patient or human subject. So Effie and her collaborators weren't arguing. We're arguing that the traditional rules should be thrown out because obviously patients do need protection and human subject research does need regulatory guidance.
00;26;42;11 - 00;27;17;26
But what she and the others were saying is let's also think about these new ways of doing research and how we can get scientists and clinicians to accept the results. That patient led research arrives at. And one of the ways she and the others said is let's come up with ways that patient researchers can seek ethical guidance. Let's put tools online that they can use so that they can devise experiments in ways that approach the rigor that traditional scientific experience experiments do.
00;27;18;06 - 00;27;52;04
Let's generate research that's of benefit to the people now, but also can be useful in guiding treatments in the future. Let's make a path towards publishing their data in peer reviewed journals. Let's make them part of the peer review process. I mean, you do have journals now that have patient researchers participating in peer review of scientific papers. And you have groups like Pachauri that ask scientists and patients to collaborate together on experiments.
00;27;52;13 - 00;28;24;24
So I think I think what she and the others were getting at is the current contract that we have may still be fine in certain circumstances, but isn't set up to address this new kind of research that's being done. And if we want it to be generalizable, scientific knowledge, which is always the gold standard, then we need to work together to help all of the partners to do better research that meets the standards that we can all except.
00;28;25;09 - 00;28;40;27
When you kind of make the promise of patient led research obvious. But, you know, how many times do we see things with great promise get tied up in knots? Is a paradigm shift likely? And if so, how long of a runway is that going to need?
00;28;41;15 - 00;29;01;11
I mean, I don't know how long it's going to take, but if there is a message in my book, if there is a message from the people that I focused on in my book, I mean, they've been working together for more than ten years. They've made a lot of progress, but they're not where they want to be yet.
00;29;01;20 - 00;29;23;29
So that's a long time. And I think that they want to go faster. I think the message of long COVID patients is we need to go faster. I think the message of HIV activists and breast cancer activists and disability activists is we need to go faster. And I don't think that you need to change a paradigm in a day.
00;29;24;12 - 00;29;53;19
Paradigms, by definition, take time to change, and they involve a lot of debate and discussion, dissension. And that's what happens in a society. People have different, different views. But I think what we're getting at here as a society is that patients need to be at the center of any paradigm that exists and that if everyone works together towards that goal, they may not agree how to get to that.
00;29;53;24 - 00;30;14;21
They may have different ideas on how to ensure that the science is rigorous and works. But if they keep this notion always at the center that the purpose is, is patient centered science, then I do think that you can end up with a paradigm that works better for more people.
00;30;15;16 - 00;30;27;10
One of the chapters in your book is Cathedral of Science, and in it a professor at Harvard. Had you read the story Cathedral by Raymond Carver. Why did they have you read that? And how does that relate to what we've been talking about?
00;30;28;04 - 00;30;55;26
Yeah, I mean, I say in the book that when we were told to read Cathedral by Raymond Carver, I was really surprised because usually in in my bioethics classes when we talk about stories and narrative bioethics, many of them involve sort of cases drawn from real life and cathedrals, really a quiet story that involves a married couple that seems to be drifting apart.
00;30;56;06 - 00;31;16;24
And the wife invites a friend who happens to be a blind man to come and stay with her and her husband. And the husband's a little bit jealous of the relationship that this person has with his wife and he doesn't really know what to say to him. And the wife goes to sleep and leaves these two men alone watching TV together.
00;31;17;00 - 00;31;38;19
And they start to watch a program about the building of a cathedral. And the narrator says to the blind man, Have you ever seen a cathedral? Do you know how to build a cathedral? And the blind man says, Let's draw one together. And the two of them construct a cathedral together. The man places his hand on the husband's hand, and they draw that cathedral.
00;31;38;27 - 00;32;01;23
And at the end of creating this cathedral, it's the blind man who says, Let's put some people inside, inside the cathedral. What's a cathedral without people? And I thought about this story all the time as I was spending time with the families and the scientists, because so many of the scientists were products of the Cathy trial of science.
00;32;01;23 - 00;32;34;13
They were the products of the best medical schools. They worked at the NIH. They I mean, they they really were, you know, part of this edifice that's been constructed and that has benefited so many people. And one of the things I kept thinking about is how do we put more people in this cathedral? I mean, that's really one of the messages that came through in this partnership that the parents and families and scientists and doctors and government officials were constructing a cathedral without people isn't really what you're looking for.
00;32;34;20 - 00;32;52;05
You're you're looking to use the power of science and research to help people. That's should be the goal of everything. And that's really the message I took from this story, that it touched me in just such a fundamental way. And it wasn't even a story about science.
00;32;53;27 - 00;32;57;18
As literature often does. That inspires us in many different ways.
00;32;57;21 - 00;32;58;20
Absolutely.
00;32;58;27 - 00;33;20;02
What did I miss? I mean, what is it that our listeners should know that you cover in the book that's important for them to know or some way that they can help or participate in this kind of effort? Or is there something that a follow up book might cover, something that you think needs additional exploration?
00;33;20;11 - 00;33;53;25
Well, I mean, I think that the message of the book is that we can all be scientists, right? I mean, it's in the title. We, the scientists, and I chose a title that echoes We the People, because I wanted people to think about the fact that what works best is a partnership. What works best is when we all come together and try to bring our different visions forward and to come up with something that will benefit all of us.
00;33;54;07 - 00;34;15;25
I think, you know, one of the things that I was struck by during during the research, not only for this book, but also when I, you know, covering health and science as a reporter is that all of us really are patients. We're either patients now or we were in the past or we will be in the future, or we love people who are patients.
00;34;16;04 - 00;34;50;28
We're advocates for those people, even if we're a doctor or a scientist, we're often on the other side of the table either trying to advocate for people we love or because we're patients. And so I think we all have a vested interest in creating a system that works well for all of us that remembers that we need treatments and that we that we need science and that all of us are experts in our own lives and that we can do research in a way that can contribute to advancing health and wellness for us all.
00;34;50;29 - 00;34;56;00
So I feel like that's the message that I hope is the takeaway of the book.
00;34;56;12 - 00;35;03;10
Well, I'm pretty sure there are listeners who are interested in the book and getting it or getting in touch with you. How can they do that?
00;35;04;00 - 00;35;26;00
So there are a variety of ways to get in touch with me. My email is publicly available. It's Amy Marcus at WSJ dot com. I'm on Twitter at Amy D Marcus. You can go into the bookstore and get the book, you know, in person, or you can order it online. You can get it from bookshop. You can get it from Powells.
00;35;26;00 - 00;35;32;18
You can get it from Amazon, Barnes and Noble. I mean, they're, you know, any, any, any place online. You can order the book.
00;35;32;26 - 00;36;03;05
Great. We appreciate that. And we want to thank you for being faithful listeners to Oracle Life Sciences, Research and Action. As always, we invite you to subscribe so you don't miss a single episode. And also maybe tell your friends and colleagues about the show as well. And we'll be back next time with more research and action.
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How can an extensive collection of real-world data help find more diverse and better participants for clinical trials? How do we create a continuously learning ecosystem that helps bridge the gap between clinical research and clinical care? And what are the biggest challenges to patient record standardization and personalized healthcare? We will learn that and more in this episode with Dr. Lu de Souza, Vice President and Executive Medical Officer of the Learning Health Network, which is a division of Oracle. Dr. de Souza leads a team that seeks to help health organizations integrate clinical research into everyday care. That means addressing clinical discovery cost, time, and patient inequities. She’s also a huge advocate for real-world data and bringing technology to bear for true healthcare advancements. Dr. de Souza has years of experience in health informatics and was the most recent CMO of Cerner in North America. She practiced pediatric hospital and emergency medicine until 2020 and has held multiple leadership and teaching positions.
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Episode Transcript:
00;00;00;01 - 00;00;25;21
How can an extensive collection of real-world data help find diverse participants for clinical trials? Are some organizations already using the concepts of a continuously learning ecosystem. And what are the biggest remaining challenges to patient record standardization and personalized health care? We'll find all that out and more on today's Research in Action episode.
00;00;27;05 - 00;00;47;23
Hello and welcome to Research in Action, brought to you by Oracle Life Sciences. I'm Mike Stiles and our guest today is Dr. Lu de Souza, vice president and executive medical officer of the Learning Health Network, which is a division of Oracle Life Sciences. In a nutshell, Dr. de Souza leads a team that seeks to help health organizations integrate clinical research into everyday care.
00;00;48;03 - 00;01;11;28
That means addressing clinical discovery, cost time and patient inequities. She's also a huge advocate for real-world data, bringing technology to bear for true healthcare advancements. Dr. de Souza has years of experience in health informatics and was the most recent CMO of Cerner in North America. She practiced pediatric hospital and emergency medicine until 2020 and has held multiple leadership and teaching positions.
00;01;12;12 - 00;01;16;03
Dr. de 'Souza, thank you so much for taking the time to be our guest today.
00;01;16;14 - 00;01;20;12
Now Thank you, Mike. It's really a pleasure to be here. And please feel free to call me Lu.
00;01;21;02 - 00;01;29;21
There's a lot of ground to cover here. But first, let's just find out about you. What was the life path that brought you to where you are today and doing what you're doing today?
00;01;30;15 - 00;01;55;05
You know, as you mentioned, I am a pediatrician who focused on taking care of sick kids in the hospital and the emergency department. And I really loved my job. But like many doctors, I felt frustrated by the inefficiencies of health care. And I felt very frustrated with the limitations of time and data that we suffer both of those things are super essential to make the fast decisions that we need to make.
00;01;55;23 - 00;02;16;20
So I started thinking about technology and the role that it could play in solving some of these foundational issues. And also, you know, we always want to see how many more patients we can help. So I felt like the pivot would allow me to take care of patients in a different way, but at higher numbers. It was not easy decision.
00;02;16;20 - 00;02;41;20
It was very hard for me to leave full time pediatrics, so much so that I stubbornly continue to practice for the first ten years that I was full time at Cerner. But at the time that I was considering joining Cerner, my mother's breast cancer was misdiagnosed and that happened because of inequities, fragmentation in care and a lack of standardization that exists today.
00;02;42;00 - 00;03;08;03
Eventually, she turned out okay with that. But these missteps and delays in diagnosis led to a much more aggressive course of treatment and the complications that came with it. But this experience really sealed the deal for me. I felt like there was a lot of work that I could contribute to so that led me to my career in informatics that started with EMR implementations and technology enabled process improvement.
00;03;08;28 - 00;03;30;25
Then ten years later, my cancer warrior mom was diagnosed with a different cancer. This one was rather rare and aggressive, and we quickly found that there was not enough research to support any specific type of treatment for her and that the survival rate for anything that they could try was pretty low. And that was not good enough for her.
00;03;31;07 - 00;03;57;05
She decided to forego treatment and instead focus on having better quality of life for the remainder of the year that she was with us all of nine months. In stories like that, Mike, are super common. Many of our listeners, I'm sure, have gone through something like it and as devastating as it is, these life experiences also help shape us and they bring these opportunities that we hadn't considered.
00;03;57;19 - 00;04;25;17
And sure enough, only a few months after her passing, the Learning Health Network was founded and I was asked to help out and I was immediately drawn to its mission and vision and the impact that it could have in cases like my mom's. So it took a little bit of time to get here. But last year I was able to take on a full time role with Learning Health Network, and I'm just super excited to be a part of this awesome team that brings transformation to research.
00;04;26;07 - 00;04;29;03
Okay. And tell us what the Learning Health Network is.
00;04;29;09 - 00;05;01;06
All right. So I'm going to start with the why and why it was created and paint this picture for for everyone to understand how important this is today. Clinical discovery. So how we get to medicines and treatments and different diagnostics is still a major challenge for life sciences and health care organizations. And because these two sectors of our industry are mostly siloed from one another, it's a very onerous process for patients and providers to participate in clinical trials.
00;05;02;01 - 00;05;27;13
Even myself as a doctor who understands the language of medicine had a really hard time finding out what types of trials were available to my mom, just as an example. So for context here, when we're bringing a new drug to market, it takes approximately 17 years and it costs an average of $2.5 billion. That those are crazy numbers, right?
00;05;27;22 - 00;05;59;13
And the biggest driver of that time and cost is getting to the patients, identifying the right patients, recruiting them and enrolling them into these trials. And about 20% of these clinical trials fail because they cannot recruit enough patients. And overall, only 3% of our population participates in these studies. Of course, 3% of the population cannot be representative of the diversity that we have here in United States or across the globe.
00;06;00;02 - 00;06;30;04
So the Learning Health Network was created to help solve these problems with the concept of these patients are in everyday care, and that's where trials need to go. We need to bring research into everyday practice. The Learning Health Support Network is a partnership between Oracle and health systems that we serve, and these organizations contribute their de-identified data to serve as the fuel for research and clinical discovery.
00;06;30;18 - 00;06;59;09
So this data set is called the Oracle Real World Data, and I'll call it our RWD from now on to to make it easier. And it's one of the largest datasets in the world like this in exchange for that data contribution, which we're immensely grateful for, Oracle provides these organizations the access to the data set so that they conduct they can conduct their own research, and we provide that at no cost.
00;06;59;21 - 00;07;22;05
We also do all of the heavy lifting for them, so it doesn't take any effort on their side to get the data there to make it de-identified and normalized. We do all of that work and then we offer a variety of benefits for them depending on where they are in the course of doing research, whether it's data science or clinical trials and so on.
00;07;22;22 - 00;07;58;05
So the Oracle Real World Data is home of about 108 million active longitudinal records from all over the United States, covering about 2600 facilities. And this membership comes from a variety of organizations. These whole systems can be large, multistate and academic centers all the way down to critical access hospitals. And this combination, this this composition of membership is intentionally done and balanced by us.
00;07;58;05 - 00;08;37;11
So they're very similar in numbers. And that becomes our superpower by having data from such a wide range of facilities and such diverse communities, and means that people who never had access to clinical research near their homes can now be represented in this dataset and represented in a lot of research that gets done. And it also means that this research, a big data set, matches fairly well to the US Census and brings that much needed diversity that we're lacking in clinical trials today, and that helps decrease the the health and research inequities.
00;08;38;01 - 00;09;03;26
How we do this is again, by using the dataset to find the patients. So we find patients that are good matches for trials, and then we find trials that are good matches for those sites and for that community. And the data can also be leveraged like I said before, by organizations to drive or derive clinical insights by using data science and the tools that Oracle provides.
00;09;03;26 - 00;09;05;10
That is us in a nutshell.
00;09;05;28 - 00;09;28;17
I think there's a lot of people listening that would be really surprised to find out the thing that slows down getting new drugs and new treatments to market isn't necessarily like bureaucracy or red tape or lack of scientific knowledge. I think people would be surprised to find out the real problem is being able to find and get people and a diverse group of people to participate in these clinical trials.
00;09;28;17 - 00;09;32;09
So that's probably what adds great value to this dataset, right?
00;09;32;29 - 00;09;54;27
Yeah, I mean, the things that you mentioned definitely are barriers that we have to cross as well. But it was surprising to me as well as I entered into this space. Just as an aside. One of the reasons it's so important for clinical research to be embedded into care is because we people, patients, we trust our health care providers.
00;09;55;10 - 00;10;09;15
You know, these are the people that we listen to and take advice from. So the studies have shown that the majority of patients that enter clinical trials or accept to participate are because those trials were discussed by their providers.
00;10;10;05 - 00;10;15;00
And what's your role in it? What what constitutes a really good week or a month for you?
00;10;15;15 - 00;10;47;21
As the executive medical director, my main responsibility is really to the health system. Members. I have a team, a super awesome team of clinical researchers that ensures these members gain value from their incredible data contribution and also know how to leverage it. We provide programing around them so that they can learn, collaborate, network and so on, and I also lead our clinical research strategy and operations, which is focused on two major components.
00;10;48;03 - 00;11;26;12
One is bringing the funded research opportunities to the members that want to have clinical research research programs, funded opportunities, meaning they come from life sciences organizations and cross, and also helping these organizations that are smaller to become research ready. So these are organizations that don't today have a program or are beginning and they need more support. The second major focus is breaking down the silos that exist today between clinical research and care delivery, and that will help drive the awareness, the efficiencies, the safety.
00;11;26;21 - 00;11;46;12
It will help us improve that patient recruitment into trials and so on. Now, boy, my my day to day changes quite a bit. So a good week or a month is hard to describe, but I would tell you that a really good day is when one of our community, Rural Health Hospitals, is awarded a study that we facilitated.
00;11;46;23 - 00;12;10;29
And because we know that those patients will be represented, that community will be represented in research and they will gain access to cutting edge medical interventions. It feels really good to know that we played a part in that and another really good day is also when our members use this data set to gain insights that lead to positive patient outcomes and that we're blessed to hear about that quite often.
00;12;11;01 - 00;12;19;04
Our Learning Health Network members have published over 500 peer review articles using this data set.
00;12;19;17 - 00;12;32;11
Best case scenario if the Learning Health Network gets its job right, how can that change how health care data, The gathering and use of real world data is used to improve patient outcomes and health care policy?
00;12;32;23 - 00;13;19;26
Yeah, I would just reiterate a couple of things. With the Learning Health Network and its real world data, we'll have real data in real time deriving insights to lead to better care and better outcomes in the continuously learning ecosystem. We'll be able to quickly restudy and improve upon those longstanding medical practices we have today. So the word restudy is really important because we do have a lot of medical practices today that are gold standard and they're based on old research or based on research that didn't include certain populations, didn't include the necessary diversity or, you know, certainly the composition of us as human beings has changed.
00;13;19;26 - 00;13;43;22
So it is very important to ensure that we're still providing the best care and we can use the data for that. And that also will decrease these existing disparities and drive us closer to personalized care. The future also would look like we no longer will take so many years to complete clinical trials because we're going to know where the patients are for specific studies.
00;13;44;01 - 00;14;11;18
We're all going to know what those studies are more important to take to specific communities and patient populations. And and I think that is going to alleviate a lot of that, not just the time, but also the cost, because these costs are, you know, also what driving the cost of medications for our patients or interventions. Let's see, we'll be able to get to a more predictive and prescriptive models of care.
00;14;12;04 - 00;14;37;24
So understanding not just what happens with an individual now and how to take care of that problem, but also understanding what's likely to happen to Mike based on data points that we have on you today and behaviors. And this way we're able to intervene in the product in a proactive way. Imagine being able to predict and prevent a heart attack from happening three years from now.
00;14;38;05 - 00;15;10;24
All of these things are in our reach today. And the good news is that we're not too far from them. In fact, our our member organizations, the ones that are using the the real world data, are already experiencing practice and research transformation. But we certainly need to scale this up, scale this approach, and hopefully we'll get to a point in which the medical community will trust more on approaching research in this way and it becomes more the standard of care of how we discover and apply changes.
00;15;11;11 - 00;15;18;04
And I also think there is going to be a lot of other possibilities of this data set brings that we haven't necessarily conceptualized yet.
00;15;18;23 - 00;15;23;23
So follow up question You mentioned that organizations are already doing this. Can you give us an example or two?
00;15;24;19 - 00;15;50;12
Sure, sure. I'll give you two of my favorite examples, not just because I'm a pediatrician, but also because less than 20% of all U.S. research funding is dedicated to children. This is a highly underrepresented population in research, just by sheer numbers, which means that patient recruitment in trials is even harder. And conducting those trials in the traditional way is much more challenging.
00;15;50;28 - 00;16;24;20
So these two examples come from very proliferates users of real world data. And in these are pediatric hospitals. The first example comes from children's health of Orange County in California, where they have used RWD and machine learning to create what is the first published pediatric readmissions algorithm. So it's an algorithm that gives us a risk of readmissions for patients that were in the hospital or presented to the hospital, and they were able to accomplish that in the matter of months.
00;16;25;03 - 00;16;51;14
They then incorporated this risk score into the clinical workflows. They put it right inside of their Oracle, Cerner EMR, and they saw a 10% decrease in readmissions in the first two years, which is just commendable. You know, it doesn't just improve the quality of of these kids, but in today's healthcare, this change also amounted to $2.7 million in cost avoidance.
00;16;51;28 - 00;17;18;23
Everyone knows how expensive it is for hospitals when a patient is readmitted. The other example is Children's Mercy Hospital. Their research team leverages the rural data for a lot of projects, and this one is really near and dear to me because I worked in the E.R. with children. They looked at adolescents with migraine headaches that were presenting to the emergency department with these headaches and how they were being treated.
00;17;19;03 - 00;17;44;29
And what they found is that 23% of these kids across 180 AEDs were receiving opioids. I want to repeat that because that's really important to us. 23% of these children were repeating were receiving opioids as the first line of treatment, and that is not necessarily the best treatment for them. It is a misuse of the medication. And it's very aggressive.
00;17;44;29 - 00;18;23;20
And, you know, we're having already opioid crisis in this country. So then they they took that learning. They created a new clinical protocol and a clinical decision support tool that they incorporated into their Oracle, Cerner EMR, and were able to decrease the use of opioids for this condition to almost zero in their emergency departments. They had several in Kansas and Kansas City, Missouri, and just like, you know, a true learning health network, they they took this knowledge and the new clinical protocol and they presented that at headache conferences around the country.
00;18;23;20 - 00;18;39;13
And they know and and they're helping improve care for kids everywhere. So as you can see, the Learning Health Network is really a game changer for these organizations. They're now able to do research in a fraction of what it would be a typical research time.
00;18;40;01 - 00;19;07;20
That's really exciting and inspiring because you listen to every opioid addiction horror story and they all start out with an accident or a headache or a quote unquote, legitimate use for opioids that then turned into something worse later. So that's a particularly incredible impact you're having, but I'm assuming it's not that easy. So what are the biggest challenges to making the dreams you just outlined come true for society?
00;19;07;27 - 00;19;35;27
Yeah, you're absolutely right. We come across many barriers. But the cool thing about this team is we we don't find them discouraging. We're truly motivated to look for solutions in innovative ways, and we find partners that can help us as well. One of the biggest challenges of community based research is the lack of resources and infrastructure today that would allow these providers to offer trials and to conduct trials as a care option for their patients.
00;19;37;03 - 00;20;13;25
You have heard this in many other ways from other people of just how burned out providers and clinicians nurses are today. They're overwhelmed by the numbers. They don't have the time and support to then take on something else like research. So we try to overcome that in a few ways. Obviously, as a software company, we're continuously looking for ways that technology can support these gaps, but we also work with outside partners who can provide the actual resources or boots on the ground and expertise for these community providers to do research.
00;20;14;15 - 00;21;01;03
Another challenge is on the data and technology side, and that is that big data requires significant compute power, know it needs specialized tools, and you need specialized training. So it all can sound easy, but it's not easy. Fortunately, Oracle is the leading provider of cloud infrastructure and services. This continuous pursuit that we have for autonomous databases and low or no code applications, I always struggle with saying that these tools, it really lends itself nicely to the work that we're doing with RWD and I think it's going to allow us to challenge the market with the new generations of these data sets and tools.
00;21;02;00 - 00;21;38;13
And then lastly, I want to touch on on cybersecurity, because that is a constant challenge across healthcare and obviously our entire business is data. So we have to be very aware and cognizant and careful of it and again, I think the unique to Oracle is this ability to leverage other data security experiences that Oracle has. So, you know, Oracle has been protecting the data of the financial and banking sectors for many years, and we're able to leverage that and bring that into Oracle Life Sciences as well.
00;21;38;23 - 00;21;46;21
It's it's a level of security and governance to healthcare data that, you know, is really important to have and it feels good to have it.
00;21;47;08 - 00;22;02;10
Well, none of this happens without tech knowledge is that have come onto the scene. So first, let's talk about how far we've come. What is today's state of electronic health records and data analytics where patient care and health care delivery are concerned?
00;22;03;04 - 00;22;28;24
Yes, this is every doctors favorite subject to the notorious electronic health record in the life that I've that I've led for the last 12 years. You know, my as much as the patient records are still fragmented and EMR is are still considered clunky tools, I do think it's important to recognize the progress that we've made and the effect that it's had for us as a society.
00;22;29;08 - 00;22;54;04
You know, most people's records are digitized today. You know, there are many children that are born across the world that will never have a paper record, will have their entire record available electronically. And that means that their data is available to us and it gives us this ability to understand health care like we've never had before. But of course, our industry is challenged.
00;22;54;15 - 00;23;19;25
We still suffer from a lack of standardization in various areas and that makes data extraction and its use challenging in various ways. The way that I think about it, the simplistic way I think about it, is that old ATM cards, you know, remember how they only function in a specific bank and then years later you could use them within a network as long as you went to that particular symbol in the back of your card.
00;23;20;13 - 00;23;39;19
And then now here we are being able to access our banking information and our money everywhere in the world. And when you are anywhere and you swipe that credit card, the transaction is seamless. I mean, it's seconds there and they're doing a lot with those seconds. You know, they're checking, do you have the right funds? Are you the right person?
00;23;39;20 - 00;24;03;22
Because, you know, could this be fraud and then authorize that? So it's very impressive, their journey. And I'm sure that getting there was not easy nor fast. So similar to that. Our struggles with patient records are similar, but we've made good strides in interoperability. I think that right now we have the right direction and the right tools to get there.
00;24;04;13 - 00;24;33;29
And also, you know, we have the experience from from from these other industries that will accelerate our progress. I think, you know, one of the things that impressed me when we joined Oracle is the number of the number and the variety of industries that this company supports and partners with. And I've seen this constant pursuit of working across the verticals, looking for opportunities to learn and collaborate and understanding that we're better, faster together.
00;24;34;09 - 00;24;57;01
That's really important for us in health care because we do have this reputation of wanting to work alone and being difficult to work with. But, you know, when you look back over time, I don't think that we would be as well positioned as we are today with patient safety, for instance, if we hadn't leveraged, you know, the learnings and the experience of the aeronautics industry.
00;24;57;01 - 00;25;09;19
Right? So flight safety and those concepts were applied to to medical safety, and that's really propelled us ahead. And so I'm looking forward to continue to work across these different industries.
00;25;10;02 - 00;25;34;16
Yeah. You know, when I've asked other guests who are engaged in clinical research and recruiting for clinical research, one of the things they seem least impressed with is how spread out varied, disconnected patient records are. What's the ideal state, and can existing tech get us there, or do we need something more or is it more of a policy and bureaucracy problem?
00;25;34;16 - 00;26;10;03
I think the answer is yes. You know, expanding a little bit more on that fragmentation of of record of patient record health it’s still, like I said, struggles with standardization and that's the piping and the backbone that supports good technology. So we're talking about standards for health data elements, meaning having the same names, the same codes, the same ontologies, and also standards for quality in health care data is still not universal, which is, which is a big challenge.
00;26;10;04 - 00;26;46;15
So I have this colleague that works in data quality and runs a company in data quality, and he always says, you know, garbage in means garbage out. So when data is not captured appropriately, it's output is harder to use. Another big challenge is getting to a single longitudinal health record, because we do in this country suffer from a lack of a universal patient ID So interoperability is extremely important, but it's still, you know, having some difficulties getting there to a seamless in a seamless way.
00;26;46;26 - 00;27;07;15
But once again, we have made a lot of progress. You know, I think that we're going to be in the place where, you know, you walk into any facility and you can scan your card or maybe you're going to have a chip on your on your arm there. Mike, I don't know. And those health care workers are going to know who you are and they're going to know how to take care of you.
00;27;07;24 - 00;27;32;22
So I do believe that we are going to get there on the policy side and, well, both research and health delivery are super highly regulated and rightfully so. We want them to be, but they're not always congruent. And there's definitely increased recognition that some of the policies, regulations that we have in place are outdated. We have evolved since then and they need to be reconsidered.
00;27;32;22 - 00;27;59;08
And we're seeing movement across federal sectors, like in I like the NIH and the White House to try to help some of these regulatory burdens. So we absolutely fully believe that your observations are right, and this is a great opportunity for us to help break down those those issues. And to me, that's one of the most exciting ways that we can make an impact.
00;28;00;06 - 00;28;21;18
You know, we've talked to several guests over past episodes about personalized medicine. Obviously, we don't get anywhere near personalized medicine without real world data. What are your thoughts about what the true barriers are to personalized medicine? Can we start looking for it and getting excited about it? Or are we still like a Star Trek distance away from it becoming reality?
00;28;22;09 - 00;28;32;15
Well, I funny that you mention Star Trek because I am a big fan and I still do. I still want to be Dr. McCoy with a tricorder. One of these days.
00;28;32;15 - 00;28;35;11
I think we all have dreams.
00;28;35;11 - 00;29;03;17
I always felt that watching sci fi movies is is a great way to imagine what the future can look like, like Judge Dredd and the Flying cars, you know, other industries already applying intelligence and suggestions. There are way ahead of us and these suggestions are derived everyday from everyday interactions right? You are constantly bombarded by ads that relate to a conversation you had with your spouse near a smart home device or via email or a search that you did.
00;29;04;04 - 00;29;32;26
So all of this is possible. It's very personalized, but health care data needs to be very protected. So I do believe we should be able to get there to more general personalized care, and the data is the foundation for that. There are definitely sectors or treatment areas like oncology, immunology, where these advances are already there in place. And we know more about genomics and other omics and we know how to target treatments for those patients.
00;29;33;07 - 00;29;34;29
So we are we're definitely getting there.
00;29;35;10 - 00;29;46;22
And thinking just about the Learning Health Network What do you see as the biggest opportunities for that organization? What does that look like in five years and what does it need to focus on to get there?
00;29;47;07 - 00;30;08;21
So I'll touch on three very important things for us. And I and I think, you know, that the ranking might be different depending on who you ask on our team, but global expansion is definitely a top priority for us. We want our RWD to power research all over the globe. We want to be a part of that movement and we want to facilitate that movement.
00;30;09;08 - 00;30;33;09
Extension of our data set is going to be very important and also with that extension of our platforms and our partnerships, we feel that there are many possibilities here to augment the current research and discovery processes with different types of data. We know that what makes up an individual and an individual's health, you know, only 20% of that is is health care data.
00;30;33;09 - 00;30;54;13
And what we do in hospitals and in practice, 80% of that is is more related to social determinants of health and our behaviors. So there is other data that we need to bring in as well to help that discovery in that personalized care and then leveraging the rural data to support other important initiatives is very important to us.
00;30;54;13 - 00;31;17;19
So rural data can help us leapfrog the current technical abilities that we have. I truly believe in AI and I know that our customers are dying to have that. So is that, you know, the easiest example I can give you that we need real data, real medical data to train AI and to create large language models that are more suited to health care.
00;31;18;03 - 00;31;24;05
And then, of course, we'll continue on our mission to to bring research into everyday practice.
00;31;24;20 - 00;31;45;24
With technology playing an ever increasing role in health care and how we deliver that health care to society. More of the focus does seem to be on landing on what role companies like Oracle can play. So I suppose my question is just that what's the appropriate role for a company like Oracle? What can it best do to shape the future of health care?
00;31;46;18 - 00;32;22;16
Well, I certainly don't want to simplify it. And, you know, I feel like we can we can do a lot here and and really make a big impact. But I feel in its most simplistic way that companies like ours are pivotal in enablement, in innovation. We have all the tools, advanced health care, we have experience to bring from other sectors and success in my mind is is not just being creative in building things that we think are cool tech, but, you know, really partnering and listening and understanding what clinicians and researchers need in solving for the right problems.
00;32;23;00 - 00;32;26;01
So that's how I see us as the conduit to get there.
00;32;26;17 - 00;32;34;18
Are there any really innovative products you're kind of seeing at Oracle that are especially relevant to the work you're doing and the goals that you're pursuing?
00;32;35;06 - 00;33;15;28
Well, I'm not going to lie. I am super excited about AI and how Oracle is applying AI to remove burden from health care. As a physician that suffered burnout in medical practice, this work is extremely important and it's also happening across life sciences, Oracle life sciences. So this is intelligence not only to decrease the huge amount of duplicative work that exists today, but also to be able to digest the overwhelming amount of data that we have in healthcare and provide more guided, guided decision support to clinicians and researchers and overall to improve safety for our patients.
00;33;16;12 - 00;33;54;15
I think that you had a chat with one of my colleagues who was working on the life sciences safety aspects of our work, and we are leveraging AI there to help read through tons of medical records to pick up those essential elements that are needed for Pharmacovigilance. I also wholeheartedly agree that employers, as often as they are today, should be a thing of the past and that health information needs to live in a different layer, needs to be more flexible, more usable for our patients, for our providers, and certainly for health delivery systems.
00;33;54;24 - 00;34;03;00
So Oracle is currently working on that and that's going to have a tremendous impact. And for our for us on the clinical research side as well.
00;34;03;08 - 00;34;17;15
Well, sounds exciting and we will, as they say, be watching that space very closely. Lu, thanks again for being with us. If someone wants to get in touch with you or learn more about your work or what Learning Health Network does. Is there a way they can do that?
00;34;18;02 - 00;34;44;27
Absolutely. You know, we welcome talking to any provider or organization that has EMR data to contribute. If you can contribute our data or health data in exchange for success, we want to talk to you. And this is regardless of whether you are an Oracle customer or not, today our RWD is EMR agnostic. We have data from at least 18 different health records and it's not exclusive.
00;34;44;29 - 00;34;55;07
So you can join multiple networks, but join ours as well. And you can reach out to us at Learning Health Network underscore at Oracle dot com.
00;34;55;16 - 00;35;27;13
Great Well if you are interested in how Oracle can simplify and accelerate your life sciences research, we invite you to check out Oracle dot com slash life dash sciences. Also be sure to subscribe to the show because there's more great insight and episodes ahead and join us next time on Research in Action.
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Research reveals that 95% of patients do not participate in clinical trials. How do we find better ways to connect willing and qualified participants to clinical trials? How do we ensure diversity in participant populations? And how can we make access to clinical trials more patient-friendly? We will get those answers and more in this episode with Brandon Li, Co-Founder at Power. Power is a fast-growing startup building a patient-friendly way to get access to clinical trials and is working to increase the diversity in clinical trials.
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Episode Transcript:
00;00;00;03 - 00;00;17;02
Are there better ways to connect willing and qualified participants to clinical trials? How do you ensure diversity in participant populations? And why do 97% of patients not participate in clinical trials? We'll get those answers and more on this episode of Research in Action.
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The need to.
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Build the Hello and welcome to Research and Action, brought to you by Oracle Life Sciences. I'm Mike Stiles, and our guest today is Brandon Lee, co-founder at Power. Power is building a patient friendly way to get access to clinical trials, and they're working on increasing the diversity in clinical trials. Brandon, thanks for taking the time to be with us today.
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Yeah, it's my pleasure.
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Great. Well, looking forward to it. And we are going to be talking about some amazing stuff as always. But we also always like to get a feel for the person behind that amazing stuff. So what did you want to be when you grew up and how did you get from there to the field of clinical trials and technology and the kind of things you're doing now?
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It depends on how far back you want to go, but I think that through most of my childhood, I probably wanted to be a like a professional trading card game player as.
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Are you a Pokemon man or.
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It was it was all of the above, right? It was like a Pokemon journey. Then there was like a, you know, journey. Then there was a magic. The Gathering journey. I kind of cycled through all of them, but I ended up landing on magic, I think, for most of it.
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Well, check those old cards. You could be a millionaire.
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I've been. I've been watching the the price of Charizard skyrocket with a lot of energy. You remember having plenty of money?
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Well, great. Yeah, but obviously that's not what you wound up doing full on.
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No, not at all. Yeah, I think the kind of journey here was. Well, at some point I became a consumer internet. Consumer marketplace person sometime between my my kind of professional trading card game times and and kind of coming out of college, I started thinking a lot more about consumer tech. So I spent a handful of years just doing things that look a lot like classic consumer marketplace work.
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Thumbtack, Airbnb, Zillow, all kinds of kinds of products. And at one point I had a close friend of mine diagnosed with a brain tumor who had to go looking for a clinical trial on her own and, you know, that journey was brutal for her. She did everything that patients basically go and do today, which is backchannel the heck out of every doctor that she knows.
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And eventually all roads ended up leading to clinicaltrials.gov. So she spent weeks there trying to figure out, okay, is there a trial that could make sense for me? Eventually, she finds one and the contact information is like the front desk of the hospital. So she's cold calling the hospital. The hospital's routing her internally. She's trying to find a way to get an appointment and eventually she gets in front of a study, she gets in.
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And that's what they had a positive readout earlier this year, which is probably the happiest journey somebody could have gone through. But it was through that kind of experience that I realized a few things. The first one is that she can't be the only person out there who is sitting in front of clinicaltrials.gov, sitting in this kind of situation trying to answer the question, are there leading medical researchers that can help me?
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And the second thing we realized was, while that journey is way too difficult today, right. Everything from even discovering trials in the first place to evaluating your options to figure out what you could be qualified for, what looks really promising through to even contacting the research sites. So we just put put our heads together and realize, well, I think that we can actually bring a lot from this consumer into that space and hopefully, hopefully help a lot more people in need.
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So tell me what power was founded to do the problems that it specifically seeks to solve?
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It's pretty straightforward, and I like to look at it through a couple of different lenses. So through the lens of the patient, it's exactly this kind of dream that I just described, right? It's helping individuals find and get access to leading medical researchers that could help them from the perspective of the sites. It's how do you connect with as many patients that are potentially interested in your study but not established at your site?
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So maybe you don't have a relationship with them yet, but we help you kind of like widen that catchment area as a site and then as a sponsor. It's well, we give superpowers to your sites and we help elevate the kind of the reach of your studies to the patients that are using our platform. And we have hundreds of thousands of them now.
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So plenty of folks on, on the website looking, looking around for trials and trial information.
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So the people who want to be in clinical trials would find useful connections to those doing the research. And what's the level of the research world? How is it embracing the platform? Is it eagerly seeking to connect with these people who want to do clinical trials?
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I think this this kind of touches on an age old problem, right where everybody I'm sure the kind of guest are. The the audience of your podcasts knows these stats, but we didn't coming in certainly turns out that finding patients to participate in trials is one of the biggest problems in life. Science, R&D, right? 86% of trials being delayed because they couldn't find the patients to participate.
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So what we found is that we've had north of a thousand like research sites already, like just sign up to start connecting with our patients from the kind of ground ground up. And that's led to a movement that we can then point to some really interesting data and say things like, Wow, actually turns out that the the the research sites that are using power or connecting with patients like ten times more than if they weren't they weren't using patients.
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And that data has been really meaningful for us to see.
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Well, is it a database of willing participants that the researchers can go look at and find? Because it seems to me most patients, they are totally taking the guidance of their doctor, you know, and so is the doctor playing a role in connecting these people with these research projects?
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There's kind of two things here. The first one is, yeah, we've got a registry where patients sign up and they say, Yeah, admitted registry. The registry experience from the the site's perspective is kind of like a LinkedIn for patients, if you can imagine it. It's like, Oh, there's these patient profiles, they've created a profile. I can see them.
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They might have answered some prescreening questions at some point. So I'm starting to paint a picture of, you know, medical history and I can invite them to connect if it makes sense. So there's kind of like this LinkedIn for patients. And then on the other side, there's also, you know, new patients signing up every month. And I think that's where a lot of the impact is, because our view is that the patients that are most recently active and interested are the patients that are most likely to actually take action.
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So it's all about new flow of patients in our mind, even more so than the the kind of depth of of the database or the registry.
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And then what about that Dr. element? Are doctors aware that this tool is available and are they eager or reluctant to get their patients involved in clinical trials?
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One of the most interesting things that we've started to see is that doctors are referring their patients to us, right? We're starting to see that in the data where, you know, maybe when we launched, nobody's doing that. And then a year ago, you know, you got a handful of people and that number has actually doubled like year on year of like the number of doctors that are actively referring patients.
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And it turns out doctors are okay, referring patients to clinical trial resources. It turns out they do that all day long anyways, but they actually send patients to clinicaltrials.gov. And if you talk to any doctor about it, they they kind of look at you like sheepishly and and almost kind of confess that they do it because they hate it, they hate clinicaltrials.gov, and they know it's not going to help the patients that they're working with.
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And it's going to be a really difficult experience. So one of the things we found is that by building a superior product experience for consumers, for individuals on the Internet to learn about clinical trials, doctors are actually more than happy to send patients to to the website to learn about trials. And that's been, you know, one of the kind of happy byproducts of building the kind of best patient experience possible.
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So because doctors weren't exactly in love with clinicaltrials.gov, they knew they would be sending their patients kind of down a frustrating rabbit hole.
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Correct.
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Now, your friend. Well, you're right in saying that, you know, researchers have a hard time finding participants for clinical trials. Your friend on the flip side was eager to participate in a clinical trial. So what makes her different from a lot of patients who are reluctant to participate? Is it because they don't know about the clinical trials or they're too scared to engage in them?
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What's what's your view on that?
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Yeah, I think it's actually about evaluation. I think evaluation is a key step. If we think about kind of the journey in three phases, there's like discovery, even learning about clinical trials and seeing the trials in the first place. That's difficult. You know, in clinical trials that is rather hard to do properly. Discovery or even your option search.
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Then there's the second stage of evaluation. What could be good for me? What am I actually qualified for, and why should I be excited about this relative to status quo? And then there's the kind of participation experience of connecting with the right sites. Right? But I think that, like the second stage of evaluation is really, really the the kind of one of the missing pieces here.
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All three are difficult, but evaluations of missing piece, oftentimes when we speak to patients and we speak to patients every week, the key question is, well, how should I be thinking about this trial relative to my current my current care? And is there a reason to believe that this is really exciting or meaningful and I think it's on are kind of like partners in the life science space to properly lay that out for patients.
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What is the driving hypothesis that makes you excited enough to put your your capital behind this, this study? And I think patients are looking for that with probably less of a clinical expert explanation of it, though.
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Your friend, you mentioned that the outcome was positive, So I'm assuming she got into a clinical trial. She participated. She was not one that got the placebo. She actually got a new drug that helped.
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Correct.
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Well, let's talk about a lack of diversity and the things that make clinical trials, not that user friendly for everyone. Why is diversity a hard problem to solve and what makes the reward well worth the effort?
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You know, we if we look at the stats, it's pretty obvious that clinical trials aren't representative of the population. I think the kind of problem here, let's sit with the problem and talk about kind of like the root cause here. I think the problem here, the problem with it is that it kind of poses a broader public health challenge.
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Let's imagine everything goes well and we end up getting new treatments through there. Phase three in front of the FDA approved and we start launching them, but we haven't properly ran these trials with a diverse group of patients. We don't actually know how some how some treatments might affect different different populations and that's why I call it a public health challenge, right?
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Because all of a sudden now something becomes standard of care. But we don't know how it affects East Asian, how it affects East Asians and that's and that's the kind of root cause problem. It's it's not a I think, a performative point that diversity, it's really kind of like a downstream potential public health challenge. So that's why it's so important.
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And then I think, B, the question of why is it the way it is today is an interesting one. And I think it has to do with the history of clinical research sites that that we choose to partner with. Typically, you know, you partner with a handful of clinical research sites. Those research sites are tasked with recruiting patients from their existing populations.
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And then, you know, the kind of set of patients you end up seeing on the set of patients that those sites have established. And it just so happens that the sites that we typically work with in research have a largely white existing patients and that that that ends up skewing the kind of population because you've got a bit of a sampling bias at that point.
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Right. So obviously research is not a one size fits all proposition. That's it's amazing that things have been passed that have not been tested on all types of people, all demographics, different patient sets. There's kind of assumption that, well, if it worked with this group, it's going to work with everybody.
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Yeah, yeah. I mean, certainly I think the the approach thus far. But you know, I think the the industry is making incredible strides here in raising awareness of this challenge. And then certainly with the recent FDA guidance starting to lean in more to understanding that, oh yeah, there is a potential health care challenge that comes with this that we need to be solving for.
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And that's been very inspirational. Watch.
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So you did form power to address all this. What does it do in terms of actively recruiting to solve the diverse party problem? In other words, increasing that pool of minority candidates, people that traditionally have not been participating in clinical trials?
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You know, we think of ourselves as a a source of unique patients that are interested in trials, Right. So we we help improve access for patients that may not be currently established at the at the research sites. So when we when we think about our role in diversity, what matters to us the most is, is our source of patients more diverse, right, than the other kind of status quo.
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And turns out when you look at our data, 40% of the patients who sign up and are actively participating on our platform are nonwhite. And that's right in line with what the US Census and what you would expect in a in a representative sample of of the US population. So I'm we're excited that we're able to hold true to that mission of improving access and that as a result of improving access, actually being a representative source of patients that are interested in research.
00;14;23;29 - 00;14;39;01
Well, you're tackling a tough space because there's so much regulation and the practices are absolutely entrenched. So what's been the rudest surprise you've encountered in your mission so far or the toughest hurdle you had to overcome?
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Not not rude surprise, but I think one of the the challenges that, you know, I think everybody can empathize with is that our research sites are incredible busy, busy and often overburdened. So sometimes what is potentially easiest for the patient isn't easiest for the research site. And when you when you think about solving this problem of improving access, if you haven't also solved the problem at the research sites, at the end of the day, you can't close the loop, right?
00;15;11;18 - 00;15;30;03
You can't kind of make the kind of transaction complete, so to speak. Right? So one of the kind of hurdles that we need to we need to overcome and we're constantly kind of like balancing is the line between what is best and easiest for patients and then what is best and easiest for the researchers that they actually need to connect with.
00;15;30;03 - 00;15;39;17
And it has to be, you know, a little bit of give and take and easy for both, Easy enough for both the they that they both can take action because ultimately if if one of them doesn't take action, nothing happens.
00;15;39;27 - 00;16;03;05
Right. So ease of use is definitely a factor. Trust is probably the other factor we kind of touched on this, but we're used to things like control groups and devices to make sure that bias and inaccuracies don't enter the clinical research picture. It seems like if there's underrepresentation and trials, the best results you're going to get are cloudy at best.
00;16;03;16 - 00;16;42;10
Yeah. Yeah. You know, trust is an interesting one, right? One thing that we've experienced with the patients on our platform is that once they've if they if they're coming through our platform, it's because they're almost predisposed to be interested in research. Right. If you think about the kind of factors that have to be true for somebody to be predisposed to be interested in research, one of the factors is that they've they've probably considered it a little bit and are coming in with a higher baseline level of trust, which is not to say that you don't have to continue to build trust.
00;16;42;10 - 00;16;59;15
As a as a researcher, I think everybody has to continue to build trust and it's easy to erode it, especially in a in a clinical setting. But what we're seeing is that the folks are looking around on our website and poking around and reading about different studies there and and then ultimately choosing to connect with it with a researcher.
00;17;00;05 - 00;17;04;02
It's because they've built up a requisite amount of trust already.
00;17;04;21 - 00;17;22;12
Well, let's say I'm someone with an understudied disease and I really want to participate in a clinical trial. How does someone go about that? I mean, obviously going to power and being registered and in the database, but what are the odds that I would get accepted? What factors come into play?
00;17;22;27 - 00;17;51;22
I mean, I think the kind of standard factors come into play at that point, right? So a patient kind of comes through the journey on the website, finds a trial and connects with a with a study, then I think the standard kind of factors come into play around eligibility. How qualified are we and can we prove our qualification as a part of connecting with the research sites in order to get the research site excited to kind of bring you in and kind of work with you?
00;17;51;22 - 00;18;12;12
Right. So some of that is on us as a platform to help help patients maybe put together what we call a dossier or an application packet that helps them get quickly considered and screened for a study. Part of that is the kind of nature of how the protocol is written, and I really think we can influence and that's okay.
00;18;12;12 - 00;18;17;28
And that's kind of par for the course. And just the way that research is structured, not everybody is qualified for every study.
00;18;18;13 - 00;18;30;24
Well, I was looking over the notes and, you know, one figure really jumped out at me. And, you know, correct me if this figure is wrong, 97% of U.S. patients and providers don't participate in trials.
00;18;31;14 - 00;18;55;27
Yeah, it's something like that. I think roughly 3% of of patients as the stat that I've seen, 3 to 5% of patients participate in trials, which is which is amazing when you think about the kind of opportunity to develop improve visibility of research. Research is such an important part of our system and oftentimes should be considered as a part of the the kind of treatment journey like for for an individual.
00;18;56;01 - 00;19;18;04
And I think that's part of actually solving this and increasing that percentage of want to think about that is like the end goal. Part of solving this, I think, is building a relationship with patients through their treatment journey and helping them understand, okay, I'm at this point and I'm on this, you know, potential treatment path and there are some trials that are available on and make sense right now.
00;19;18;13 - 00;19;33;24
But then there are also some trials that could make sense a year from now based on how these kind of treatments progress and based on how I react to them. And I think part of what we want to do as a platform is build that relationship and help be a part of that that journey in that planning for individuals.
00;19;34;17 - 00;20;05;11
Well, 97% is huge. And you said earlier 86% of clinical trials are delayed because they can't recruit enough patients. Is it that people and providers are not participating because trials are so hard to stand up and run? Or, you know, we've talked to other people before, you know, on the podcast and previous interviews and and a big problem is participants in clinical trials kind of don't really know what they're getting into in terms of the level of monitoring that's needed.
00;20;05;11 - 00;20;19;19
And, you know, it becomes very difficult to incorporate the clinical trial into their lifestyles. And are those some of the issues that are just preventing 97% from leaning into research?
00;20;20;12 - 00;20;43;24
You know, I go back to this evaluation question like, are we are we properly are we properly conveying to patients like the reasons to believe if there's a compelling reason to believe that this is a like the best kind of like path forward, I think that that's is kind of like a like put into context of the burden of, of participation.
00;20;43;24 - 00;21;05;28
And I think oftentimes from the patients experience, all they kind of like get exposed to really is the burden of participation without the, you know, the requisite amount of exposure to, you know, why is this the best path forward for me or the best option available right now? I think about it in terms of balancing these two things.
00;21;06;17 - 00;21;38;22
Yeah, there's an increased ask and burden on behalf of the patients and there's also potentially a really compelling reason why this is exciting. And those two things have to be put into a kind of like proverbial pros and cons list that individuals can kind of trade off as they as they think about about research, but not no, I don't think that's the kind of question of burden is excluding 97% of of patients, I think that there are patients that that will be turned off by the burden.
00;21;38;22 - 00;21;41;01
But I don't think it's 97% of people.
00;21;41;20 - 00;22;06;23
And for the general public, you know, getting excited about research, how do you think the amount of time that it takes to do good and qualified research, you know, and get all the way through to FDA approval? It just seems like it takes years and years and years. So it's it's hard to get excited about something that may not yield results for anyone until well into the future.
00;22;07;08 - 00;22;22;27
I think if you put yourself into the shoes of the individual participating, right, it's it's not typically a question of, okay, like what is the impact ten years from now? I think it's a question of, you know, what am I experiencing in the here and now? Does that make sense?
00;22;23;13 - 00;22;39;23
Yeah, absolutely. Is control of the major clinical trials in the hands of too few facilities and researchers, or do you feel it's pretty much properly democratized? You're seeing a lot of clinical research opportunities available.
00;22;40;09 - 00;23;16;16
Yeah, control is an interesting question, right? So certainly clinical trials are concentrated to a group of providers, sites that are familiar and let's say have a track record of doing research. And I think there are like very reasonable rationales for that. I would even argue, you know, probably okay with that, there's a little bit of concentration, right? Because the kind of bigger a trial gets, the more people that are or the more providers that are participating, the more noise and variance kind of gets introduced and gets introduced to the system.
00;23;16;16 - 00;23;38;20
And that's not always a good thing. Our perspective here is that we do need to increase access, but the way to increase access is not necessarily to get to 100% of providers participating in in every study. I think the way to increase access is actually to help individuals and patients learn about studies that are happening in their in their geography, and they get properly connected with those sites.
00;23;38;29 - 00;24;00;02
And to make that that kind of journey easier, rights for patients have more visibility to what's available and then getting connected with the right person in the city. It doesn't really make sense to have, you know, a hundred providers in Cincinnati doing a doing a study right is just about funneling patients to the to the right locations and improving kind of like access and transparency.
00;24;00;02 - 00;24;00;26
Those opportunities.
00;24;01;17 - 00;24;17;01
Well, you do have primarily a technology product. You're connecting people to clinical trials. Technology is going to play a role in that. But it's not like this is tender, right? Me So what what kind of tech and guidelines does power use to make these connections?
00;24;17;01 - 00;24;38;00
We think of the our, you know, our publicly facing platform and that's that's what most people see when they kind of engage with us as like an Airbnb like interface for individuals who are looking for trial. So it's really on the on the patients side, right? It's like a discovery and evaluation product and we do a bunch of things that are interesting there.
00;24;38;05 - 00;24;59;26
But one of the things we do that's interesting is we actually have one of the best structured data sets on eligibility criteria that is out there and then as a result, we can have patients now start to do their search on the basis of, for example, like their genetic biomarkers, and they can do filtering on genetic biomarkers relative or relevant to their their kind of condition that's not available anywhere, anywhere else.
00;24;59;26 - 00;25;31;04
Right. From a patient facing perspective, that's that level of kind of like of detailed search experience actually makes the discovery and evaluation process way easier on from a patient's perspective. Then on the flip side, you know, let's use that as continue the Airbnb analogy research sites get access to. Well, we like to think of as, you know, like a referral management or a recruitment management platform that they can use to see all the patients that are interested in their trial on our website, on our platform.
00;25;32;14 - 00;25;53;09
So it's kind of a workflow management tool that that sites can use to kind of connect those patients that are on our website and expressing interest in their studies. And then somewhere in between we've got a kind of like matching algorithm. So we're I'm sure everybody who's who's kind of come through here and is working on technology is thinking about ways that you can use A.I. rights to improve workflows.
00;25;53;09 - 00;26;25;05
Our view is that A.I. is an interface is not the end game, but as a as a component to kind of like your tech stack is really compelling. So we're looking at ways to use AI to improve match rates, improve kind of screening qualification, and in doing so, reduce some of the burden on the on the patient side for identifying what could be a good trial, but also reducing burden on the site's perspective and having to screen that these patients from from scratch every single time.
00;26;25;27 - 00;26;38;10
So it sounds like the databases, the processing power required for that would be pretty intensive. Is all of that being run smoothly and securely in the cloud? Is that a hybrid approach? Is it on premises? What do you have?
00;26;38;17 - 00;26;46;12
Yeah, it's all in the cloud and it's not a you know, we're not making our own A.I. models, right? So it's it's not nearly as intense as maybe it sounds.
00;26;46;29 - 00;27;03;24
So it sounds like the proposition is just that there are the ability to run filters and eliminate mismatches to get to good results better. And that a superior, I would assume, to what clinicaltrials.gov have offers.
00;27;04;10 - 00;27;23;18
Oh, yeah, certainly right. For if we're going to both sides of the equation, patients can more quickly figure out what trials they should actually be considering. Right. Like if you if your patient search on clinicaltrials.gov, you get thrown 150 different options that you need to track in a spreadsheet and try to whittle down towards five or ten that are a good fit.
00;27;23;18 - 00;27;39;06
So patients can very quickly do that. It takes them a minute on our platform and then on the researchers side, they can double click into the patient's profile, the medical history, all this kind of stuff in order to quickly make an assessment about whether this patient is qualified enough to kind of come in and screen.
00;27;39;29 - 00;28;08;20
So what we've been talking about is bridging the gap and making the connections between patients and clinical research. And Oracle Life Sciences mission is kind of bridge the gap between clinical research and then clinical care. So kind of in the connecting business as well. But if power is successful and we're running diverse clinical trials, what are your thoughts on how those learnings can then be made actionable in the point of care and patient portals area?
00;28;09;08 - 00;28;37;02
I think that, you know, and this is kind of early in and the way that we're thinking about it, but I think that providers have a really important role here and consideration and the consideration process of clinical trials. And one thing that we would love to to see more is for us to have broken down the barriers for providers to understand and what trials are currently running in their specialty and stay on top of the best options.
00;28;37;02 - 00;29;00;12
Right Today, you know, providers in the community have to stay on top of reams of information. It's really quite a difficult journey for them as well to stay on top of the kind of latest research in their in their category. So one thing we would love to see is for those providers to be able to leverage power to, you know, just stay smart on the kind of latest in a medical research.
00;29;00;17 - 00;29;05;14
That way when they do have a patient comes through, they have the information they need at their fingertips as well.
00;29;06;04 - 00;29;26;29
Are doctors reluctant to give patients? I don't want to say false hope because the hope is genuine, but it's almost like they don't want to get their hopes up by saying, hey, this clinical trial is likely to give you a solution where today we don't have a solution for you.
00;29;27;17 - 00;29;50;09
I think providers are are really the experts at navigating that that conversation. And I don't know any providers who I think misrepresent the the opportunities present in clinical trials. But I think really providers are quite thoughtful about how they present research as an option.
00;29;50;09 - 00;30;08;06
Well, we talked about your tech stack. And when you think about your tech stack and you look over all the tools that you have, is there anything on your wish list or is there anything you know, you touched on I a little bit that you see coming in the future that's going to really kick power up a notch?
00;30;08;26 - 00;30;11;27
Yeah. I mean, if somebody could just solve this medical record thing, I'd be nice.
00;30;13;11 - 00;30;29;07
Well, you've brought up an area of mass chaos, but kind of expand on that. You know, what's what's the problem? Is it just like incoherent, inconsistent, not interconnected methods for keeping medical records for Americans and others?
00;30;29;19 - 00;31;07;23
Yeah, all of the above. Right. And, you know, patients might want to get access to their medical records. How do they get those records? You know, the new clinical trial inevitably is going to want the medical records as well. How do how does the trial get access to those medical records, the kind of like general mosaic of different set ups and different communication norms and different like ways to share the records, I think introduces a lot of inconsistency into the space, which makes it difficult for everybody from providers to researchers to patients, and certainly for the life science companies that are pulling their hair out and looking at everything, trying to figure out is there
00;31;07;25 - 00;31;09;09
is there a good way through this mess?
00;31;09;27 - 00;31;12;25
Turns out a little standardization isn't a bad thing.
00;31;13;02 - 00;31;38;28
No, it could be really helpful. I don't know. You know, I think a little bit of the the kind of banking and finance stuff where Clyde has really solved this inter connectivity problem for our intraoperative interoperability problem for financial services institutions to allow fintech at some point. It'd be nice if somebody does that on the medical record side, and there are a lot of really great teams sprinting at this.
00;31;38;28 - 00;31;47;18
So, you know, I'm I'm cheering them on. Waiting for the day when collecting a medical record is as easy as connecting my bank account to a new app.
00;31;48;10 - 00;32;07;28
Well, if you were to assess where we are today in terms of bringing more participation and diversity into clinical trials and where we might be, say, five years from now, can you change mindsets and the culture around clinical trials in that period of time? Where do you see this going in, say, the next five years?
00;32;08;15 - 00;32;36;24
I think it's it's interesting. I think there's a ton of runway ahead of us for impact. Or let's go back to one of the stats that you brought up. 97% do not participate in trials. 3% do getting 1% more of the kind of population to be excited about research. And depending on research, just 1% increases. The overall the overall participate participation rates of the population by 33%.
00;32;36;24 - 00;32;56;25
That's massive, right? So can we go from 3% to 5% in the next five years, almost doubling the kind of participation rate? That's huge impact, a huge impact on on our industry. It's not yet broad population adoption. And I think that's okay. When you're starting from a small base, you kind of have to stack up the the wins and think about them economies relative terms.
00;32;57;14 - 00;33;03;15
Well, we'll look forward to watching the progress in the space and we'll let you know when that medical records thing gets sort of shorter.
00;33;05;01 - 00;33;05;03
So.
00;33;05;04 - 00;33;15;11
You can be on your way. Well, Brandon, thanks again for being with us today. If someone wants to get in touch with you or learn more about what power does, what's the best way to do that?
00;33;15;20 - 00;33;39;28
Yeah, you know, I think that get in touch with me. I probably shouldn't do this, but my email is Brandon up with power dot com. Feel free to send me an email. Always happy to chat and share. Share what we're up to. And then if you want to take a look at our website, it's it's free and public so it's with power dot com pretty easy to go find and take a look at the kind of experience that we're trying to build for for people who are learning about research.
00;33;40;11 - 00;34;12;22
Fantastic. And we appreciate it. If you are interested in how Oracle can simplify and accelerate your life sciences research, we invite you to check out Oracle dot com slash life sciences and also be sure to subscribe to the show because there's more genius ahead and join us next time on Research and Action.
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What does a data hippie believe about the democratization of data? What role do technology companies, government, academia, industry, and other stakeholders play in life sciences and discovery? And how might walking clinical trials lead to improved precision medicine? We will get the answers to those questions and more in this episode with Dr. Chris Boone, the GVP of Research Services at Oracle Life Sciences. Chris has held some prominent roles at AbbVie and Pfizer, influencing health economics, medical epidemiology, and real-world data and evidence. He is an adjunct assistant professor at NYU, engaged in national health data committees, and serves on several boards including the American Heart Association.
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Episode Transcript:
00;00;00;03 - 00;00;22;00
What does a data hippie believe about the democratization of data? What role should tech companies, government and other stakeholders play in life sciences? Discoveries? And how might walking clinical trials lead to improved precision medicine? We'll get those answers and more on this episode of Research and Action in the lead.
00;00;24;03 - 00;00;43;21
Hello and welcome to Research and Action, brought to you by Oracle Life Sciences. I'm Mike Stiles. And today we're going right to the source when it comes to finding out what Oracle is doing in the life sciences space, what does a company like Oracle have to contribute? Why is it in the space? What does it and the rest of us have to gain from its involvement?
00;00;43;21 - 00;01;09;03
Those are the kinds of questions will be throwing at Dr. Chris Boon, newly appointed EVP of Research Services at Oracle Life Sciences. Chris has held some prominent roles at AbbVie and Pfizer, influencing health economics, medical epidemiology and real world data and evidence. He is an adjunct assistant professor at NYU, engaged in national health data committees and serves on several boards, including the American Heart Association.
00;01;09;03 - 00;01;14;18
So Chris, you're obviously a very busy person, so we really appreciate your time today.
00;01;15;21 - 00;01;17;02
Thanks, Mike. I'm happy to be here.
00;01;17;11 - 00;01;30;01
Before we get started, tell us about your new role at Oracle and how you see scientific and industry expertise as kind of a winning combination with technology.
00;01;30;01 - 00;01;50;15
Yeah, that's a great question. And I think this is a very fascinating point in our health care and life sciences history. I mean, it's about but I'll start a bit with who I am and what exactly I do as the group vice President of Research Services. I get the great honor and privilege of leading our research services organization formerly known as Cerner.
00;01;50;15 - 00;02;17;14
And these are within the Hawk Oracle Life Sciences Organization. This particular organization has been primarily focused on data analytics and research, right? So in many respects it represents the convergence, if you will, of scientific clinical industry and technology expertise, which I think is pretty much nirvana for where we are with the future of evidence generation in our industry.
00;02;17;14 - 00;02;35;06
And so I'm extremely excited and honored to be able to sort of usher this organization and Oracle into this new realm and fully integrate all the great technologies that Oracle has with all the expertise and expertise and capabilities that that we've had in this R&D as a team.
00;02;35;26 - 00;02;53;21
Yeah, it sounds like there's a lot of people involved and buy in as necessary from a lot of different areas, from researchers to academia to technology. How are you finding the the openness and the willingness to include Oracle in these major efforts?
00;02;54;07 - 00;03;22;05
You know, it's interesting because I feel that the industry is very, very, very hungry for and interested even and curious. Maybe that's a better term for what Oracle will do in this space. I mean, I mean, I think after the Cerner acquisition, people became very intrigued of what Oracle could do, right? Because they sort of they think about the technologies, the advanced technologies that Oracle has, whether it be in a cloud computing automation and these great things.
00;03;22;28 - 00;03;54;26
They think about the clinical trial management platforms that it has. And now you have an electronic health record organization, a capability in addition to a research organization. So it does put Oracle at it's sort of an end of one really. I mean, there's no other company in industry that can can can make those sort of claims and to be true, but also have the ability to sort of drive transformation and how we think about clinical care as well as clinical research with all of the technologies we have at our disposal.
00;03;54;26 - 00;04;03;12
So I think it's a it's a very exciting time and I think that, you know, there's no better place to be right now than Oracle as it pertains to what we can do.
00;04;03;27 - 00;04;18;06
Well, there's no question how large a role data has played in your life and career, But you don't even call yourself a data nerd. Like most folks, you've actually referred to yourself as a data hippie. So what does that mean? Do you live in a van or something?
00;04;18;06 - 00;04;43;03
I think you're right about everything except the van part. But now the term data hippie, you know, it resonates pretty much with my career journey. You know, specifically going back to I first adopted the name back in 2014. I was leading a public private partnership called Health Data Consortium in D.C. but we were really focused on advocating for it and pushing this whole concept of open data and health care, I think.
00;04;43;11 - 00;05;04;19
And really which is sort of the genesis of this idea of the democratization of health data, really. And it was supposed to drive, obviously, innovation that would lead to higher quality patient care and making it more accessible and doing all these other things. In a modern times, though, I think we've sort of we've sort of moved past that a bit, right?
00;05;05;09 - 00;05;29;27
So I think now if I if I think about my, you know, current vision, it's just really about creating a system where you have the use of open, accessible data as a transformative force for the greater good of patients and ultimately the entire global health care system. So, I mean, I hope that there are more people I know that there are more people out there that share this vision, too.
00;05;29;27 - 00;05;37;01
So technically their data hit these just like I am, and we all are champions for this idea of the open exchange of health data.
00;05;37;01 - 00;05;51;04
Well, so if you're a proponent for data hippies, are you up against the man, the man being those who want more siloed proprietary data management? Why or why would anybody be resistant to this open access to data for all that you're talking about?
00;05;51;23 - 00;06;16;09
I think we sort of created a system that sort of has perverse incentives and, you know, and granted, I do believe that there are certain situations that warrant protecting the data privacy for individuals. So I'm not saying that everybody's data should be accessible to the masses for whatever they wanted to do with it. But I also think, too, that there is an opportunity to make data accessible for the public good.
00;06;16;09 - 00;06;34;29
I mean, if you go back to the pandemic, one of the one of the and there weren't very many, but one of the silver linings during the pandemic was this idea of global data sharing in order to sort of move faster with what would be the development of the vaccines, as well as treatment and therapies for for COVID, right?
00;06;35;00 - 00;07;03;18
I mean, that was only made possible by the free flow of data, right? So I think that what we have to do is create an incentive structure. We have to make people understand the value of data. I think you'll find that many folks became extremely educated on how the clinical trial process works and life sciences, but also the idea that using their data can actually be contributory to something that affects all of humanity.
00;07;03;18 - 00;07;25;09
And I think that and that's really where we are. So this whole that fragmented proprietary data, siloed nature that we existed in had, you know, has actually worked against us in many respects. And I think we're at a place in time where history will define what we do, what we've done, and the free flow of health data so critical to human health to be opposed to it.
00;07;25;27 - 00;07;49;14
Well, you mentioned that the the pandemic, what very few things good came out of it. But one of those good things is a more open approach to data and data sharing. What had to happen to make those walls come down that quickly was that a government instituted thing or did the industry itself decide we can't operate status quo and get a vaccine out there?
00;07;50;00 - 00;08;08;02
I think it was all of the above. I mean, but really I think it was more a genuine concern from all parties to really address this pandemic head on. And we knew that not one sector could could address it by themselves. Right. So you knew the public sector can do it by itself. Perhaps the private sector couldn't do it by itself.
00;08;08;02 - 00;08;33;12
So this idea of forming these collaborations, these partnerships, was was critical to sort of advancing science in the way that we knew it and that the way that we'll continue to practice it today, but also in a way that you know, we also had to engage even the community, the broader community, you had to educate people on what on public health matters that some may or may not have been concerned about in the past.
00;08;33;12 - 00;08;56;20
So you have this idea of engaging the private sector, the private sector engaged in a public sector, the public sector and the private sector engaging the public at large. And those are the things that were necessary to make this happen. I mean, and then it makes issues such as what you talk about data sharing a bit easier for people when they understand what the clear purpose is behind the sharing of their health data.
00;08;57;07 - 00;09;08;15
Well, obviously, you wound up at Oracle. How did that come about? What did you see out Oracle that presented great opportunities for what you want to accomplish, both personally and professionally in life sciences?
00;09;09;02 - 00;09;35;27
You know, it's interesting, and I would say that there is a short and a long answer to that question. But but but the short answer is, is that I actually didn't know much about what Oracle was doing and the health care and life sciences space prior to the Oracle Health Conference that I attended in September. And I was invited out to be part of the panel to sort of discuss the future of clinical trials and some innovations that we've seen.
00;09;36;09 - 00;09;57;28
And then I got an opportunity to listen to my Sicilian and Sima and a number of folks really talk about what their perspective, their world view on the future of health care life sciences looked like and what Oracle was actually doing to advance it. Right. And so, you know, you couldn't help but walk away feeling inspired by what this organization was seeking to do.
00;09;57;28 - 00;10;27;26
And so I had a bit of an epiphany while attending this meeting. And and just the idea of joining an organization that sort of shared my my sort of personal vision and values around the industry. And it's aligned with my professional goals. It only makes sense. Right. And it didn't it didn't hurt that the organization sort of believes in fostering innovation and and driving meaningful change and utilizing data and digital technologies to create a better world.
00;10;27;26 - 00;10;53;11
And and that that is what resonated with me. And the other pieces of that that I would say is that you know, I mentioned Mike Mike earlier but and Sima but you know, another person that I would add into that Ms.. Mix is David Fineberg. And I think that having inspirational leadership who have who are very passionate and committed about addressing these tough challenges that we have within the health care industry, I think is critical.
00;10;53;28 - 00;11;10;15
It makes all of our work feel more meaningful. Right? And so as a person who prides himself on being passionate about this industry and passionate about its transformation, it was it's great to partner up with with senior leaders who share that same passion and that same vision.
00;11;11;04 - 00;11;37;03
Well, it seems like technology is playing a bigger and bigger role as a solution to so many of the problems the world has and that we as a people have. Is it that the path to more, better and more accessible health care data is more likely to come from the private tech industry like the oracles of the world, than from some of the other traditional players like academia and government?
00;11;37;18 - 00;12;03;06
Again, I still think it's a multistakeholder approach that's necessary. I mean, you could you can point to the significance of academia. What we've seen with some of the peer reviewed journals and how they thought about the idea of of incentivizing folks to share their data with their publications. Right. And, you know, and sort of a de-emphasized in this need to say that you need to you need to keep your data proprietary.
00;12;03;06 - 00;12;24;15
It's your intellectual property and therefore, you know, it sort of affects their their ability to to move up in the ranks and their universities. But I also think the private sector, we've been at an interesting time the last decade where there's been a tremendous amount of focus on how to monetize data, which is sort of a disincentive for the free flow of data, which is sort of where I end with it.
00;12;24;15 - 00;12;51;24
Right. And I think that, you know, just by a lot of the things that we've seen even from a public sector perspective and regulators and the 21st Century Cures Act, for example, is a way that, you know, you've seen how the impact of working together and collaborating with both regulators, industry and academic researchers and how it essentially facilitates that necessary cooperation that we need.
00;12;52;03 - 00;12;59;17
And that's just one example of how I think that we've seen progression in this particular space.
00;13;00;07 - 00;13;15;15
Well, you brought up something kind of interesting. How do you work through the balance of the need to monetize on the part of private industry versus if that element weren't there, how far we could get, how fast with data sharing?
00;13;16;02 - 00;13;37;27
You know, it's interesting, a few several years ago I was I was quoted in one of the periodicals where I said that we were at a farm. I was at a in a data arms race and essentially what I was meaning by that is that we were looking to amass as many datasets as we possibly got. Granted, we weren't going to use all this data, nor could we even make sense of all the data that we were accumulating.
00;13;38;06 - 00;13;57;09
So what you're hearing, my personal belief is that people pay for insights, noxious, raw data, right? I think that it seems, you know, that that the raw data is the valued asset. And it could be if you actually know what to do with it. But I think that what people are looking for is insights to really drive decision making, right.
00;13;57;15 - 00;14;14;02
Whether that be at the policy level, whether it be at the clinical care level, whether it be at the research level, whether it be in the investment level. However you want to think about it. And I think that there's still the monetization of valuable insights is still there and that still should be very much a part of it.
00;14;14;09 - 00;14;32;07
And it doesn't mean that I'm opposed to the idea of monetizing raw data. I don't want that that belief to be out there. It's just that I believe that there is a greater good that we're all striving for and the more that we can get to an interoperable state within our industry, the better off patients will be in the long run.
00;14;32;10 - 00;14;35;16
And that's really sort of my core belief.
00;14;35;16 - 00;14;41;00
So you've talked in the past sometimes about a walking clinical trial. What do you mean by that?
00;14;41;19 - 00;15;04;11
Yeah, I mean, so the walk in clinical trial is sort of synonymous in my mind, at least with this concept of an app one trials that we've heard or some people refer to it, a single patient trials. And really what we're I think we are is that we're at a space where, you know, digital technologies have advanced and have been adopted and they're rather ubiquitous, you know, in our society as we think about it.
00;15;04;11 - 00;15;40;21
And so we're constantly accumulating data passively about patients and their environments and their lifestyles and their health conditions and even their medical histories. And we now have the ability to better understand and maybe in many ways be preventative with how we think about personal care. Right? I mean, so you get to understand quickly, which gets into this this this sort of world of precision medicine, where essentially treatment approaches are personalized to that individual based on their genes or their environment or lifestyle.
00;15;41;10 - 00;16;00;03
And I think this idea of being a walk, a walk in clinical trial, which is for all intents and purposes, is a paradigm shift from the way we thought about clinical trials in the past. But I think we now have all the technologies there to be able to embrace this concept. Does it apply in every single situation? Absolutely not.
00;16;00;12 - 00;16;12;26
Right. But I do think, and especially in the rare diseases space, there is a tremendous opportunity to do an app. One trials are walking clinical trials as often as I would describe it.
00;16;12;26 - 00;16;25;00
You mentioned precision medicine. What's your vision of precision medicine and how close or far away are we from it? What remains to be done to get us significantly closer to that vision?
00;16;25;23 - 00;16;42;17
I think we're a lot closer than we were, say, even five years ago. Right. And I think one of the biggest drivers for that has to be that direct to consumer genetic testing that folks are able to get. I mean, and the fact that the cost of doing that is much less. We've had clinical data from each US for a very long time.
00;16;43;09 - 00;17;10;19
We now have many of these sort of digital health apps available on mobile devices that can capture a lot of data about patients and in sort of a pro or a patient reported outcome format. So if you take the data that we have in the past, if you take the data that we collect from patients directly, if you take the genetic data, if you take the environmental data, we know a lot more about patients than we've ever known before, which actually gets us a lot closer.
00;17;10;19 - 00;17;31;10
And I think where we are is then is maybe in lacking some of the technological capabilities. The technology is out there, but it's not fully utilized. Don't embrace at this point. And, you know, and I think that's where technologies such as DNA, I you know, quantum computing and other tech that we are really excited about come into play.
00;17;31;18 - 00;17;44;05
And I think that once we're able to make sense of all the data that we collect on each individual, you know, then the better insight we can get and then the more personal your health care treatment plan will be for them.
00;17;44;23 - 00;18;10;18
Yeah, it sounds like the kind of future we all think about and that we believe that we should eventually get to, which is real time personalized diagnostics and treatment. But what I heard you just say, I think, is that technology is actually the the current barrier to that and that that technology exists. We just haven't applied it properly yet.
00;18;10;18 - 00;18;35;23
Yes and no. I actually think the bigger barriers, honestly, are going to be probably around the data privacy concerns that many folks have. And and this sort of core issue of informed consent, I do believe the technologies are there. Right. So that that is not a rate limiting factor in this case. I think that the probably the bigger concern and for many folks is the privacy concerns.
00;18;36;04 - 00;18;58;24
So I think as we move closer to the future of precision health, where individuals are providing these massive amounts of personal health data, it'll become increasingly more important that they fully understand and they consent to the use of their data for these secondary purposes. Right. And so I think that to me is the larger issue at this point.
00;19;00;08 - 00;19;10;22
Well, before we achieve the highest ideals of precision medicine, we first kind of have to start doing a better job of making clinical trials more patient centered, don't we? Isn't that step one?
00;19;11;17 - 00;19;44;25
It is step one. Yeah. I mean, I think we have to move to a paradigm where patients are not just seen as subjects, but as active contributors with valuable insights. Right. And and in order to get closer to that, I mean, we have to sort of create frameworks where it allows for engagement of diverse patient groups, and it takes into consideration these sort of variabilities that exist, whether it be varying health literacy levels, accessibility needs, geographic constraints.
00;19;45;04 - 00;20;15;01
All of these things have to play. And, you know, it's just all about building cultural sensitivity into how we think about study design for trials and whether it be randomized clinical trials or this whole end of one trials or walking clinical trial concept that we were discussing earlier. So I think that this is all important and it's not just purely a health equity play, it is in large part, but it's not purely that it's really about patient centeredness, and patient centricity is what some people will refer to it as.
00;20;15;09 - 00;20;18;13
And I think that's the world that we are trying to move closer to.
00;20;19;09 - 00;20;31;02
Well, you just kind of alluded to the fact that clinical trials aren't necessarily as diverse as they need to be. Right. We're not testing a significant number of populations.
00;20;31;15 - 00;20;33;00
Yeah. Yeah, absolutely.
00;20;33;05 - 00;20;40;12
And is that a is that a data problem? Is that a culture problem? Is it a privacy concerns problem?
00;20;41;19 - 00;20;59;17
You know, there's a number of reasons why I think, you know, a diversity of clinical trials is lack over the years. I mean, you know, what people tend to latch on to is this concept of trust. And while I do think that's part of it, I think that's actually probably a smaller piece of it than what we all want to accept.
00;21;00;11 - 00;21;31;09
The reality is, is that it's more of a awareness and a sort of an accessibility challenge, right? I mean, awareness, meaning that the vast majority of us will identify clinical trial opportunities from our primary care physicians or our specialists or whomever we're getting receive in our care from if they are not aware and or if they're not incentivized to really push this this notion of being part of a certain clinical trial, then typically the patients are never even aware that that is a possibility.
00;21;32;00 - 00;22;01;08
And then I think the other piece of this is that you get into some rather stringent inclusion and exclusion criteria for people that sort of exclude them. I'll give you an example. I am a hyper tension patient, a sort of a post-COVID condition that I've been dealing with the last couple of years. I mean, and so as part of that, I could easily be excluded from from an opportunity to be part of a clinical trial just by having that sort of chronic condition, if you will.
00;22;01;27 - 00;22;33;19
And so I think there's an issue of awareness and availability of the trial. You know, you know, sort of incentivizing or making it bring in the idea of this trial to the physician, making making them aware. There's also an idea of revisiting some of the inclusion exclusion criteria that are associated with being part of a clinical trial and acknowledging that certain subgroups, you know, may or may not be able to be part of that.
00;22;33;27 - 00;22;56;15
There's also a challenge of moving or shifting closer to more virtual trials. Some people call them decentralized clinical trials. And the idea basically is just the idea of utilizing remote monitoring or digital technologies to make it more accessible to people. I mean, that that's at the heart of it. And so I think that there's a number there's a myriad of factors that I think all contribute to it.
00;22;56;28 - 00;23;32;27
It's not simply trust, but that doesn't sort of diminish the significance of the trust issue in certain communities. But it also it but but it does mean that we have to acknowledge that there are other challenges that we must actively address, too. And and I think that's what you're seeing more of from many of the research or the sponsoring or organizations who are facilitating many of these trials is they're acknowledging that there are many that there are other issues that they have to address to want to sort of increase their recruitment efforts and also retain people to be part of those trials.
00;23;32;27 - 00;23;52;23
Well, going back to your data happy mantra of collaborating around readily accessible data, how open do you feel the industry is to that kind of multi-stakeholder collaboration? Like is that the role that government might have to play with policies like the CURES Act? I don't want to say force, but push that a little.
00;23;52;23 - 00;24;18;12
Yeah, no, I think the government plays a very critical role in their ability to sort of convene all the different stakeholder groups at the table and to really have a, you know, an honest and we'll say courageous conversation about many of these issues. And so it's not to say that they're simply just a convener, but I do think their convening power is critical in this state of forming many of these multi-stakeholder collaborations.
00;24;18;26 - 00;24;56;15
I also think that, you know, the idea that the government can play a role in facilitating these public private partnerships that we've seen around the globe in Europe, for example, they formed the Innovative Medicines Initiative, where they're essentially facilitating collaborations between the European Union, pharmaceutical companies and other stakeholders to really accelerate the development of next generation medicines. And, you know, so in addition to and then within the U.S., obviously you have the curious act, but you also have the single initiative, which has been something around drug safety that's been around for a while.
00;24;56;15 - 00;25;15;17
I think the World Health Organization has been collaborating with different governments around the world and NGOs. I just think that everyone recognizes how critical these multi-stakeholder collaborations are to really advance health care in the way that we all know it should be. And you won't get any pushback from anybody on that.
00;25;16;03 - 00;25;29;05
Yeah, so there's regulation, but there's also the carrot. What could be done to incentivize data sharing? How do you make everybody happy? From patients to researchers to profit to nonprofit to pharma, to IP holders, etc.?
00;25;29;25 - 00;25;52;02
Yeah, I mean, I think that the incentive structure has to be sort of multipronged, right? I mean, there is no one carrot for all the different stakeholder groups. I think recognizing that there is a diverse need, there are diverse needs and concerns from both for profit organizations as well as nonprofit organizations is the first thing we have to do, right?
00;25;52;02 - 00;26;27;04
So acknowledgment and acceptance is is key. I also think that you have to start thinking about it. You know, the reward systems or the incentives, Right. For pharmaceutical companies, for example, who are involved in some, you know, therapeutic development that their incentives may have to be aligned with some of their commercial objectives as well. Right. So if you think about what the role that policy can play, potentially, it could be, whether it be extended patent protections or tax benefits for companies that share data, especially data when it's coming from their clinical trials.
00;26;27;13 - 00;26;59;20
That could be one step. You know, it sort of addresses those concerns around competition and IP that many companies have. Right. While at the same time you're hoping that it accelerates the drug development and improves trial diversity, which is what we were just discussing. And I think that, you know, as it pertains to the the sort of academic community, you know, traditionally the the career advancement model was based primarily on publications.
00;26;59;20 - 00;27;32;09
I'm not going to say solely, but publications is obviously a big area of concern. So we have to recognize that that is the incentive and how do you shift that thinking to to sort of reward those those researchers who are more actively contributing their data to a larger repository for research purposes? And I think that those are the those things are essential not just for advancing health care, but also getting us closer to this precision medicine, which is what we all want.
00;27;32;27 - 00;27;45;04
Real world data and real world evidence are gaining prominence. What's your vision for how we use that to advance health care and life sciences? And is that where Oracle and Tech best plays a role?
00;27;45;27 - 00;28;13;09
I don't think that's the only place that Oracle can play a role. But let me answer the first part of your question first. I think that it's been incredibly exciting as someone who's been in the sort of real world Data Group 11, a space for for around so very long time and and to see it sort of come to prominence the way it has and and its ability to sort of transform how we do how we generate evidence and what evidence and how decision making, how decisions are made based on real world evidence.
00;28;13;09 - 00;28;34;05
I mean, we've seen it play a critical role in understanding disease, understanding patient outcomes, understanding the benefits and risk of certain treatments that are in the market, all of these things. And now we're at a space where, you know, you even have the ability to use real world data and where will evidence to streamline the drug development process?
00;28;34;05 - 00;29;05;06
So you're using it for a protocol design or are you using it to support post-market surveillance activities or facilitating regulatory decisions? As we discussed earlier with the 21st Century Cures? So I think my vision for it is that we continue to incorporate it, that we create this sort of learning health care system that we all that we all desire, where we're not only just generate the evidence, but the evidence is being fed back and to, you know, providers for clinical care policy.
00;29;05;13 - 00;29;23;23
So many of their policy decisions, so on and so forth. And we continuously collect that data and we also continue to learn from it. So I think ultimately that's really where it is. But with Oracle, you know, going back to my point about it being in such a unique position, we have this cloud infrastructure, we have these data management capabilities.
00;29;23;23 - 00;29;46;27
We have. Are it just sort of puts that puts the organization in a unique position to sort of really co innovate in this space. And I and I and I think that you'll also see the ability to sort of build these very sort of novel patient registries around certain diseases that allow us to learn more about it than we ever knew before, leveraging many of those technologies.
00;29;46;27 - 00;30;06;09
So I think I think in summary, I would say that the the integration and utilization of of real world evidence represent, you know, the new frontier in advancing health care and life sciences. And and I have no doubt that Oracle is ideally suited to be at the forefront of that transformation.
00;30;06;09 - 00;30;24;19
Well, we touched on precision medicine. We have all these new ways to monitor patients real time. And we read about the work being done in genomics. How do you balance the excitement of what can be done against the inevitable concerns about privacy and ethics, which you brought up before? Isn't it a lot like a lot of tech products?
00;30;24;19 - 00;30;42;24
Yes. You get great benefit from them, but the cost is a lot of trust that people have to have. And I'm not just talking about the population's having enough trust to participate in clinical trials, but overall, the level of trust that's needed to make open data and data sharing work.
00;30;43;08 - 00;31;09;16
Yeah, I mean, I think balancing that promise, what the pitfalls is, is obviously critical. And and then now when we start to get into this whole idea of using genomic data that really sort of scares people. I mean, we had a situation not long ago where one of those sort of genomic providers was hacked. Right. And so that that data tends to be highly personal and sensitive and can be misused that place in the wrong hands.
00;31;09;16 - 00;31;34;19
So we always want to keep that in mind. I think one of the and so it only elevates this issue of privacy as being a top concern for many folks. And I think that we have to this is where regulators come in right by it. You know, ensuring the the robust data protection and privacy laws that are safeguarding, you know, this information in a way that people feel comfortable with it.
00;31;34;19 - 00;32;00;11
Right. But I also think, too, you know, one of the things that's often that's near and dear to me that's often overlooked is really some of the ethical, ethical concerns with the misuse of the data. Right? So we have these privacy concerns, but this is where it does become a health equity issue. If if that data is misused like it's used to sort of discriminate against certain cell populations, then that is a huge problem.
00;32;00;16 - 00;32;40;10
Right? Some people are concerned about the use of it for whether it be in employment decisions, whether it be potentially in legal situations, insurance situations, you name it. And I think that that becomes a I would say that's also an added concern for people in addition to sort of the privacy issue. So I think where we are as an industry is that we got to pay more attention to providing the education and the literacy surrounding how health data is being used, how genomic data is being used, and what this concept of precision medicine really means and how it benefits them.
00;32;40;21 - 00;32;53;27
Right. I think that education is key, transparency is key and consent are key, right? I mean, so those are that those are the key instruments I think we have to use in order to really advance and address those concerns.
00;32;54;14 - 00;33;15;22
Well, looking ahead, what technologies do you think hold the most promise for clinical research and drug development? Like Oracle's focus is on generative AI and automation? One of their focuses are those the things that are going to really fling the doors open and lead us to getting effective drugs and treatments to market much faster than what we have now.
00;33;16;09 - 00;33;40;21
I do I do believe that, yes, the answer to that question, and I think but not only that right. I do think DNA and drug discovery is great. I mean, we can we can use the models to generate novel compounds, maybe even simulate their interactions with biological targets. That is how you speed up the identification of some of these viable drug candidates.
00;33;40;21 - 00;34;02;15
I think automation in clinical trials should address some of the efficiency challenges that we've had. And and also, you hope, reduce the likelihood of human error. As you know, when it comes to sort of the data capture aspects of it we've been using and, you know, the whole idea of natural language processing and literature search for a while.
00;34;02;15 - 00;34;24;25
Right. And I think that's another huge opportunity as we sort of automate much of that. I think quantum computing is exciting, too, you know, I mean, it's just and it's an we're still in the nascent stages of it, but, you know, right now, the way it's looking, the potential to unlock some of the challenges that we have a drug development can be addressed with quantum computing.
00;34;24;25 - 00;34;26;10
So I think that's pretty exciting as well.
00;34;26;25 - 00;34;42;25
Well, Chris, thanks for coming on the show today, giving us a glimpse of how you see the future of technology collaborate action and data sharing shaping up to revolutionize clinical trials and health care. If those listening want to learn more about you or Oracle's initiatives, how can they best do that?
00;34;43;03 - 00;35;03;25
Yeah, I mean, you can shoot me an email or you can find me on LinkedIn or even X. My my handle this data happy on both of those social media channels. Also have a personal website out there. Chris Bowen, SI.com, if you're interested in connecting that way, But I'm very easy to follow, so I look forward to connecting with everyone.
00;35;04;05 - 00;35;32;25
Fantastic. If you are interested in Oracle's contributions to life sciences research, just take a look at Oracle dot com slash life Sciences. Also be sure to subscribe to the show so you can be here for the next episode of Research in Action.
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What is the rare Gaucher disease and how does it impact patients, families, and life sciences? Is enough emphasis being placed on research and discovery for rare diseases? And what are the patient-centered approaches that best serve those battling rare diseases? We will get those answers and more in this episode with Tanya Collin-Histed, CEO of the International Gaucher Alliance. Tanya has been a longtime driving force in supporting patients with rare diseases and advocating for world-class healthcare. Her work has been nothing short of groundbreaking and she’s become the go-to person for patients, medical practitioners, industry, and governing bodies. As a mother of a child with Gaucher disease, she brings a unique, first-hand, and compassionate approach.
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Episode Transcript:
00;00;00;00 - 00;00;25;09
What is the rare gosh disease? Is enough emphasis being placed on rare diseases? And what are the patient centered approaches that best serve those battling rare diseases? We'll get those answers and more on research in action in the lead to the world. Hello and welcome to another episode of Research and Action, brought to you by Oracle Life Sciences.
00;00;25;09 - 00;00;49;25
I'm Mike Stiles. And today we have a truly inspiring guest. Tanya calling his dad, CEO of the International Gosh Alliance, has been a long time driving force in supporting patients with rare diseases and advocating for world class health care. Our work has been nothing short of groundbreaking. She's actually become quite the go to person for patients, medical practitioners, industry governing bodies.
00;00;50;03 - 00;00;52;01
Tanya, thanks so much for being with us today.
00;00;52;14 - 00;00;55;04
Thanks, Mike. It's an absolute pleasure to be here.
00;00;55;19 - 00;01;05;11
Well, before we get into the incredible work you're doing, let's get a baseline understanding of exactly what Gaucher disease is and just how rare it is.
00;01;06;00 - 00;01;37;11
Okay. Well, as a caregiver, I'll give a lay lay version to you. So it's a genetic condition and it's inherited. It's caused by a storage disorder. And that is because people with Gaucher have a deficiency in an enzyme. And the function of that enzyme is that it's in the body to break down substances. And because there isn't enough of that enzyme, the substances store in different parts of the body.
00;01;37;25 - 00;02;05;17
And it really does depend on what type of disease you have to how the disease affects you. But all patients can have a large liver and spleen. They get anemia, they get bruising where the blood doesn't clot properly and bone pain and bone damage due to the cells being in their bone marrow where which is where the blood cells are made.
00;02;06;02 - 00;02;42;09
Now, for patients who have type two and type three, there's also brain involvement and that really ranges from patient to patient. But that can include things like cognitive impairment, seizures, hearing and sight loss, unsteadiness in their movements and tremors. Now, it's it's a rare disease, as you say, and roughly it's around one in 100,000. However, this will different differ from region to region and also from type to type.
00;02;42;21 - 00;03;11;18
So historically, type one cases, disease is the most prevalent. Then we go into type three and then type two is like what we would call ultra ultra. However, as we become a much more globally connected community, we are seeing that there are many more patients with type two and Type three in Asia, whereas in sort of Europe and the West, we see more Type one patients.
00;03;12;05 - 00;03;27;29
Yeah, well it sounds like just that one issue, the the deficiency of that enzyme can cause countless problems all over the body. It already makes it obvious why this is such a difficult disease to get a handle on.
00;03;28;17 - 00;04;03;25
Yeah, absolutely. And I think the thing is, is that often when patients become ill and they go to maybe their general practitioner, you know, and they describe the, you know, how they feel that there are lots of things that could be wrong with patients. And therefore often patients have what we call a sort of diagnostic journey, a diagnostic odyssey where it will take a long period of time for them to actually get diagnosed.
00;04;04;12 - 00;04;12;04
If someone is diagnosed and they do get a correct diagnosis for, gosh, what are the typical outcomes?
00;04;12;20 - 00;04;38;28
Wow, that's a good question. So again, this goes back to whether or not you have type one, Type two or type three as a rare disease. We are incredibly lucky. So over 30 years ago, there was a medicine developed called enzyme replacement therapy, and this was developed and it what it does is it puts the deficient enzyme back into the patient's body.
00;04;39;06 - 00;05;00;14
So it's a bit like, you know, when you've been men. Tom So you've been, you know, you start up or your waist and, you know, you put it to one side and then the binmen come and they empty it, and then you start to store it up again. Well, of course, it's a bit man dotcom, you know, that storage gets more and more and more and starts to affect the average around it.
00;05;00;20 - 00;05;34;04
So that that's a sort of good analogy for go phase disease. But because this enzyme replacement therapy was developed and it was it's like an infusion. So patients either have it once a week or once a fortnight, it puts the enzyme back into the body, gets rid of all the storage and a significant proportion of patients. If they get treatment early on and they get the right dose of treatment, then they can actually live really good lives with great outcomes.
00;05;34;10 - 00;06;05;22
Now here it's important to say that enzyme replacement therapy is for the non neurological aspects of the disease. So that is your liver, your spleen, your bones. Now it doesn't cross the blood brain barrier. So the type for patients with type two and type three, they still have the all the neurological aspects of of the disease. So if you're type one, it will depend on where you live in the world, whether or not you get treatment.
00;06;05;22 - 00;06;13;28
And that's some issue. But if you do get treatment and you get good clinical care, then you can expect to have a relative normal life.
00;06;14;18 - 00;06;31;20
Well, and unfortunately, the reason the world has you as such a strong advocate is that this is a disease faced by your own daughter. Tell us about her, what her symptoms were when they started showing up and that journey that you mentioned of getting properly diagnosed and treated.
00;06;32;10 - 00;07;01;05
Of course, yeah. This is this is going back a few years ago now. So in 1995, Maddie was my daughter, Maddie was 15 months old. And it was towards the end of the year and we just noticed that she just wasn't that well. And she had quite a low mood and a cold. And, you know, like many pet parents, you know, she was was still quite young.
00;07;01;05 - 00;07;29;11
So we took her to the doctors and they were like, yeah, she's got a you know, she's got a throat infection, She's got ear infection. You know, hear the antibiotics go away If she doesn't get any better, come back. So a week goes by, ten days go by. She's she's not any better. So we took her back and at that point, the general practitioner said she's very pale, if you notice that she's very pale.
00;07;29;25 - 00;07;47;12
And we was like, Well, yeah, we have noticed, but that's why we just thought it was part of her not not feeling great. So he said, I'll tell you what he said, I think we should you should go to the local doctor, local hospital and they'll do a hemoglobin C what her, her blood types are, and we'll take it from there.
00;07;48;13 - 00;08;20;01
Well, that from that morning, basically, we went on a three month journey to the local hospital. Her hemoglobin was 6.4, where it should be around 12. She was admitted she had a number of blood transfusions. On examination, they found out she had a large liver and spleen. We were given the diagnosis of leukemia. So that was obviously very, very challenging for us as a family.
00;08;20;02 - 00;08;55;05
She was our first born. Now, at this point in time, we lived not far from London, and the local hospital had shared care for pediatric pediatric oncology with Great Ormond Street Hospital, who most people would have heard of. So we were taken by ambulance to Great Ormond Street Hospital. We were admitted onto the oncology ward and it was like a little conveyor belt of all these little children going through for Beaumaris to aspirations so that they could give her a final diagnosis.
00;08;56;05 - 00;09;23;16
Actually, after waiting a number of hours, we were told that she didn't have leukemia, but they suspected that she had something called Go Shay's Disease, which was a very rare disease. Now, you will remember I previously set about this diagnostic journey and diagnostic odyssey, and it takes a long time to be diagnosed. Now, ours was not a typical one for a patient with rare disease.
00;09;24;02 - 00;09;56;11
And it goes back to what I said about there being that new medicine in the early 1990s. And because it was approved, the company put investment into awareness and actually Great Ormond Street Hospital had become a center of excellence for Go Shay's Disease. And they had a very, very good doctor there. And actually that doctor cared for Maddie until she was 18 years old at Great Ormond Street when she transferred to the adult hospital at the Royal Free.
00;09;57;23 - 00;10;27;19
Now, you know, we were lucky because when they did that bone aspiration for leukemia, because of their expertise, they noticed the sort of shape and the pattern of the cell and that's why she was diagnosed with Go Shay's Disease. And actually from the first visit to the doctor at the end of 1995 to her first infusion of the new medicine to help with her liver and spleen, it was only actually approximately six weeks.
00;10;28;04 - 00;10;59;20
So we were, you know, we were very lucky. We did stay in Great Ormond Street for three months because her liver and spleen were so large. She underwent a what we call a partial splenectomy. So she had most of her spleen removed. She was severely underweight and her breathing was very shallow at the time of of admission. So we were in Great Ormond Street for a long time when she when she was first diagnosed.
00;10;59;20 - 00;11;15;06
And actually she was on a feeding tube for about a year afterwards just to build her back up. But, you know, if you can have a great diagnosis, then I think we were extremely lucky. In that case.
00;11;15;23 - 00;11;37;28
I would absolutely have to agree. I mean, what a horrible thing for Maddie to have to go through and for your family to have to go through. But, you know, it sounds like you landed in exactly the right place to be with the right people. And then based on my own experience, you know, it's not uncommon to go beyond just caring for your loved one and want to make a bigger impact to help others like them.
00;11;37;28 - 00;11;48;05
So walk me through your own thought process. What did you see the need was and how did you first go about exploring what role you could play in it beyond Maddie?
00;11;48;15 - 00;12;17;11
Yeah. So, you know, when Maddie was first diagnosed, I, you know, it took me almost a year really, to be strong enough to do more than just survive. To be honest, My, my, my, my marriage failed, and I actually became a single mum, which is not uncommon for patients or families that have children with with chronic conditions. But I did have a good job and a great family and friends who were there for me.
00;12;17;11 - 00;12;47;18
So when Maddie was diagnosed with type three, Go Shay's Disease, it's obviously have has neurological involvement. There was literally no information out there for me as a parent. And when I went to the library, it said Death within a year. And nobody had ever heard about it. So for me, you know, I set out to develop information for patients and parents so that they wouldn't be in that situation.
00;12;47;28 - 00;13;16;19
But also I set out to sort of develop and build a community in the UK, and that was really for support, for support for me, support for Maddie and support for others. Now, around five years before Maddie was diagnosed, that was the UK and Shay's Association was actually set up. Now it was set up because of this new medicine that had come up for type one Gaucher disease.
00;13;17;12 - 00;13;41;20
And as patients were going to the hospital and having treatment, they were talking to each other. And this organization set up. So there was already an established group in the UK and I decided to join them and then they invited me to sit on the board as a sort of representative for patients with type two and Type three.
00;13;42;09 - 00;14;04;10
And they asked me to do that really, because everybody else on the board had type one Gaucher disease. And if you're a patient or caregiver with a with type two or type three, it really is it's almost like a completely different disease. So I think they saw the benefits of me having the benefits of of having me on the on the board.
00;14;04;10 - 00;14;31;16
I did have a lot of support from the founders of the UK Association, Susan Lewis and Jeremy Emmanuel, and also Maddie's consultant doctor Elodie, who was really great in terms of educating me about the disease, what was going on in research, who the the doctors were, where the other patients were. So it was really a sort of collaborative effort.
00;14;32;13 - 00;15;02;29
And, you know, I started to bring patients and parents together on family days out and conferences and sort of listened to the challenges. And then we write books on education, trying to find out what was going on in research, the developments, and really how best to go about sort of trying to improve patient outcomes, whatever that looks like, to to to to a patient.
00;15;02;29 - 00;15;27;05
You know, were there any new treatments? Was there ever going to be a cure? And it was really about putting information, you know, putting my feelers out there, getting known, getting people to talk to me and, you know, feeding all that back to to the community. I became a board member of the UK Association in 2005, and I started working for them then.
00;15;27;25 - 00;16;03;01
And actually I remained working in the UK as well as sort of then going into the European and global state until about 2018. And in terms of my work, European and internationally, again before my time actually back in 1994, again because of this new treatment, seven patient advocates for this disease invited themselves to a European meeting where doctors and researchers were talking about this disease.
00;16;03;21 - 00;16;31;07
And these advocates sort of formed an anarchy of of patient of a patient group, because they you know, they saw they had common interests and goals. And by working together, they could see that they would have a much, much stronger voice. And that European sort of group of patients soon turned into a sort of international group of patients.
00;16;31;07 - 00;16;57;11
And today that's nine is the international alliance. We'll be celebrating 30 years next year. And I am the CEO of the International Gaucher Alliance and have been involved, you know, since 2008. Really, I sort of got my foot in the door in the UK and then slowly learned a lot and then sort of started to get my foot in the door in Europe and internationally.
00;16;57;29 - 00;17;24;24
But I think when I when I really think about why I did what I did and why I became a patient advocate, it really does go back to Maddie being born in the UK, you know, and she had access to treatment and good clinical care. And to me I wanted to try and make sure that wherever other patients lived in the world, that they too could have this.
00;17;25;12 - 00;18;02;06
And because treatments were so successful for many patients that, you know, there was a hope for those patients to have a future, but also that they didn't feel alone. Having a rare disease can be very lonely. And for many patients that I work with, I will never, ever meet them. But they know that there is somebody out there who's advocating on their behalf and the if they're feeling down or helpless and have nowhere to go in their own community, then actually there is somebody who does care.
00;18;02;28 - 00;18;31;19
Yeah, it is a tremendous resource and sorely needed, not just for Gaucher disease but for others. Actually, the challenges faced by those battling Gaucher disease are so similar to those overall who have or are caregiving. For someone who has a rare disease, as you just touched on it a little bit, but talk to me about what it's like to live in that world where you have something very serious, but because it's rare, you kind of feel emphasis isn't being placed on it.
00;18;31;28 - 00;18;35;00
And it can it can feel quite isolating, right?
00;18;35;08 - 00;19;00;15
Yeah. So I think I would start by saying people say you've got what I've never heard of. What is it? What is it? And, you know, this is the reality for patients and their and their caregivers, because you absolutely have to become your own advocate or the advocate of your your child. And you have to fight for everything.
00;19;00;24 - 00;19;29;01
And every time you go for an appointment, you have to again, go through what it is, how it affects. And then they're interested. You are an interesting case and that in itself is is is very, very challenging. And I think, you know, this is why patient organizations are so important because they provide the support that patients need, that, you know, that pastoral or support that time.
00;19;29;01 - 00;19;58;11
Somebody to talk to who knows how you feel and has often been through that situation. But they also provide information and advice so that they can empower you and patients and, you know, for better outcomes. But, you know, I rare diseases don't have the coverage of of more common diseases. And you may live in a country where they're just really on any other patients.
00;19;58;11 - 00;20;22;18
Speaker 2
So it can be really, really lonely. I went to Ireland many years ago with a member of our board from the UK and we actually have met a couple of patients now in Ireland and there was a gentleman there and he was in his fifties, so he'd had chase disease for 30 odd years and he had never met another patient.
00;20;23;05 - 00;20;47;25
Wow. You know, that is in a place like Ireland. So you can see how how lonely and isolating it can be not only for the patient but also for their family. I think you hear when we think about, you know, the environment we live in now, you know, social media like Facebook can be very important. Linking patients and families.
00;20;47;25 - 00;21;18;05
And often they become, you know, online communities sharing stories and advice. And we see that a lot in negotiate community. You know, type three that my daughter has many years ago there was one type three patient in in Lithuania. So, you know, by using things like social media that that parent could come into a community and sort of be part of a wider family.
00;21;18;21 - 00;21;39;27
One of the biggest things that affected us many other patients is that, you know, because it is a rare disease and people don't know a lot about it, it means that people have an unknown future. You know, when Mary was diagnosed, we read death. We knew within a year and we were told not to make any future plans.
00;21;40;14 - 00;22;10;10
Parents are told to take their children home and just enjoy life. You know, it's a physical and real emotional rollercoaster. And the thing is, you can't get out of it. It's exhausting. It's not something you can, you know, you can sort of just put to one side. It's part of everything you do. And the thing is, is reality is, is that if you don't fight as a family, nobody will fight for you.
00;22;11;01 - 00;22;57;05
And I think like many rare diseases, you know, mental health is a massive challenge for patient and caregiver community. And, you know, we are seeing much more attention being given to this topic, which is good. But like anything in life, it's patchy and not available to all. So importantly, you know, I see my role as sort of being that people often spend a lot of time, you know, just WhatsApp, a new families or people sending little videos and just having a chat and that enables me to sort of hopefully help them make them not feel so alone, but also enables me to sort of link them up with other people that I might know that, you know, they may get support from.
00;22;59;25 - 00;23;28;06
Yeah, it sounds like what families need most is connection information and ongoing research. But have you found that the perception isn't necessarily true, that there are actually medical practitioners who are working on and who are captivated by finding solutions to rare diseases? Because that sounds like what you've found. And specifically, have we gotten anywhere in terms of advanced treatments since the early nineties?
00;23;28;23 - 00;23;29;01
So. You know, I think, you know, we are really lucky and go chase disease. You know, we we work in an environment where, you know, our doctors and researchers are really committed to improve patient lives and together as a community, you know, physicians and patients, we've really developed a great global community. You've got the international Law Alliance, which is an umbrella organization, and we have 58 member countries, plus we work in another 25 or 30 countries with patients.
00;24;06;13 - 00;24;46;09
And then you have the International Working Group on Disease, which is a sort of platform for clinicians and research is globally who are interested in in Gaucher disease. And actually we do a lot of work together on things like guidelines, consensuses, meetings, and we often body doctors are who are new in go chase disease with, you know, people from the Iwg day, for instance, there was a doctor in Kenya who'd got a new patients, had never treated a patient before.
00;24;46;15 - 00;25;19;27
So we were able to, you know, buddy them up with somebody from the UK who had a lot of experience. We there is a lack of like diagnostic testing in Zambia. So we know doctors in Brazil that would do testing free of charge for patients. So we link those those doctors up and you know, there's we're working a lot in Africa at the moment and there's a lot of education to be done.
00;25;20;07 - 00;25;58;00
So we recently did a online educational session which actually got 1200 doctors from Kenya and the surrounding countries that are interested in pediatric medicine. And one of our doctors from the Iwg today did that educational session for us. So there's a lot of of volunteering, there's a lot of joint working, there's a lot of preceptorship. And, you know, it's really a great collaborative environment now, you know, that's 30 years in the making.
00;25;58;16 - 00;26;30;25
But, you know, over the last few years we've seen a real acceleration, you know, in reaching areas of the world that maybe before were cut off. You know, we didn't know that there were patients there. So that's all really positive. And, you know, we patients disease is a is a bit of a success story really in some ways because for type one patients, enzyme replacement therapy has just completely changed the patient, a patient's life.
00;26;31;13 - 00;27;04;14
You know, they have been able to get access to treatment. They have been able to get access to, you know, doctors that are very knowledgeable. And, you know, they've been able to get on with their lives, to have families, to have careers, to run marathons. And, you know, enzyme replacement therapy that came on over 30 years ago has been followed for type one Déchets disease, an oral therapy called substrate reduction therapy.
00;27;04;14 - 00;27;35;16
So we've gone from, you know, weekly or fortnightly infusions to taking a pill once or twice a day, which has transformed patients lives. And actually at the moment where we are again mostly for type one, there are a number of clinical trials for gene therapy for type one. So, you know, we've gone the real sort of like infusion pill and now we're potentially looking at a one off treatment for Gay Shea's disease.
00;27;35;25 - 00;28;07;06
Now most of that is for type one. There is currently one study for type two and one study for type three. So, you know, that's an area still where we are trying to find out how to address the neurological involvement in patients. And there's still a long way to go to go for that. I think the other thing I would say is that one of the challenges for us as a global community is that, yes, we are 30 years down the road from that first enzyme replacement therapy.
00;28;07;19 - 00;29;01;05
But if you are born in Kenya or Zambia or Cuba or Pakistan or Jordan, treatment is not available through reimbursement. So that is where there is still a lot of work to do. Now, there are opportunities for patients to get treatments, and that's through charitable access programs. And that's one of the things that we as an organization, the International Gateway Alliance, do a lot with the companies who manufacture these therapies is that we work with them and they have a number of slots for charitable access where patients can be given treatment, a lifelong treatment where there's no river reimbursement in their countries so that they can have that future and that life.
00;29;01;05 - 00;29;25;05
You know, we've talked to guests several times on this podcast about patient centered research and citizen science. And it feels like, especially with rare diseases, there needs to be a tighter collaboration where patients and their families are more involved and work more closely and directly with researchers. Are you seeing that happening and is the research side leaning into it?
00;29;25;16 - 00;30;04;07
So I think the this is an area that we have been really strong on in as I described earlier, you have the patient community and you have the clinical community who have sort of grown up together and are working very, very closely together. And then you've got the research community and the sort of pharma community who, you know, are not big pharma, they are small pharma, and they recognize that patient centered research and and patient centered support needs to run through everything they do.
00;30;04;23 - 00;30;36;06
And what we see is that we see that we are invited to have a seat at the table from very, very early on to really understand the condition, to understand the challenges that patients and their families face, to understand what's important to patients and what areas they're still very little known about. And we can we deliver that to the different stakeholders.
00;30;36;21 - 00;31;17;10
And basically we are seen as an equal partner and, you know, things like the development of research projects, the development of clinical trial design, the patient community are really co-creators in this. I think this is an area where we have had a lot of success. So I think generally in rare diseases that you see that there is a real recognition of the value of having patients and patient advocates at the table from the very beginning, because ultimately whatever you're doing, you want it to go as smoothly as possible and you want it to have the biggest effect.
00;31;17;22 - 00;31;39;11
Now, if you get everybody around the table at the very beginning, you're more likely to see that happen. Whereas if you get to a point and then you say, Oh, actually maybe we should invite a few patients or patient caregivers or advocates around, see what they think, and then you're having to go back or you're not actually doing that.
00;31;39;24 - 00;32;07;23
And then I think, you know, we're seeing more encouragement and necessity by health technology assessments and marketing for licensing like the FDA and EMA to say, you know, where is your involvement from your patient community? How did you know your patient? How did you work with your patient community? What is important to patients? What do they want you to address?
00;32;07;23 - 00;32;16;03
Well, in fact, I think you've partnered with Cerner and Visa, which is now part of Oracle Life Sciences, for some research efforts. What does that partnership look like?
00;32;16;21 - 00;32;43;08
Yeah, so this is really, really exciting. So as I've said, you know, a lot of work in progress has been done for patients with type one diabetes disease, not so much for type two and Type three. And I've been in this community for 26 years and I've sadly seen many of our patients lose their lives to type two and type ricochets disease now because it is very rare.
00;32;43;27 - 00;33;20;12
No single center has enough patients to study. There is a real lack of natural history data on these patients. And actually when you look at patients, even when they have like the same genotype, they have completely different phenotypes. You know, they the way that the disease presents itself in them is completely different. And therefore, it's a really, really challenging disease to really understand and see how you could potentially develop a therapy that is safe and effective.
00;33;20;21 - 00;33;54;03
But also, you know, how should we be managing these patients clinically and what are the care and support do these patients need to function in society? So what we did as an international alliance is that we had an idea to set up a patient led patient owned registry just for type two and three disease. And for the last couple of years, we have been working with what was Sunrun Visa and now Oracle, in setting up a registry called Guardian.
00;33;54;13 - 00;34;27;07
And Guardian collects patient reported data from patients and caregivers around the world on the way that Type two and Type three patients disease affect patients in their everyday life. And the way that we set it up was we work collaboratively with interviewing patients, doing focus groups, finding out what was important to them, and then developing the question, as in Guardian and the role of Sutter and Visa.
00;34;27;07 - 00;34;53;26
Oracle is that they are the they are the the organization that provide all of that support to us in terms of running the registry as a patient organization. We had a vision, we had an idea, we had the passion, but we didn't have the skills and resources in in-house to run a registry. And that is where Sutter and Visa Oracle have come in and we've developed this partnership.
00;34;54;11 - 00;35;14;21
Well. So on the research side, obviously clinical trials are where the rubber meets the road. If I have a rare disease, is it getting easier for me to participate and find a clinical trial if I want to? And how easy is it now for researchers to find the patients willing to participate in these trials?
00;35;14;21 - 00;35;48;13
So so we do have some trials for go shows disease, but because it's a rare disease, it's not like working in, you know, oncology or diabetes or anything like that. So, you know, there are not a lot of trials, but there are trials. And, you know, the thing is, is that we have a lot of centers of excellence around where patients go to have their disease managed.
00;35;49;01 - 00;36;35;17
So the this is an ideal opportunity where you have cohorts of patients to be able to raise awareness and make patients aware that, you know, there are clinical trials for their type of disease. I've got to say the one of the challenges is that most clinical trials are done in the West, whereas we have huge unmet need in the east of the world and that comes down to expertise, but it also comes down to it's easier to run a clinical trial in Europe than it is in Africa, which is something that we as a patient organization are trying to work with.
00;36;36;00 - 00;37;22;22
Those interested in bringing clinical trials to shades disease to try and have a different approach. And I think because we have the International Working Group on disease and we have a very strong patient organization and we have a few really good pharma companies that are interested in Roche's disease, We, you know, we work together. So I think that it's not easy to develop trials, but but actually it's also not easy to recruit for clinical trials because patients have also had enzyme replacement therapy or substrate reduction therapy for a number of years now.
00;37;22;22 - 00;37;53;04
And these drugs have been really, really good. They do what they say on the tin and patients are living a really good quality of life. So actually recruiting patients into these clinical trials can be quite challenging, particularly when you're thinking about new technologies and patients want to know about safety and efficacy and the benefits of switching from a a safe therapy, which they've been on for for years into something that is experimental.
00;37;53;19 - 00;38;08;22
So as an organization, you know, we are really trying to raise awareness and share information on clinical trials and educate patients on clinical trials, you know, to support their decision making.
00;38;09;12 - 00;38;33;11
Well, Tanni, it's been so great hearing your story, hearing Maddie's story. There are real people and human beings behind these rare diseases, and you've done such great work bringing that vibe to health care and the work being done on pragmatic solutions. I'm going to bet that listeners will want to learn more about you and what you're doing. Is there any way they can get more information or get in touch with you and the Alliance?
00;38;34;00 - 00;39;03;17
Yeah. So like most organizations, we have a great website which is Geisha Airlines dot org and we can also be found on social media platforms like Facebook and other sorts of Instagram. So we, you know, we do have a really good social media presence for you to do is is is find out where the newsletter is or click on the join us on on Facebook.
00;39;03;17 - 00;39;13;27
And you know, we have somebody in our group that works specifically on communication and we try and share not only the work we do, but work that our partners do.
00;39;14;06 - 00;39;47;16
Perfect. Well, thank you so much again. And if you faithful listener want to find out how Oracle can simplify and accelerate your life sciences research, just check out Oracle dot com slash Life Sciences. Subscribe to the show so you don't miss anything and we will see you again next time on Research in Action.
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International Data Corporation reports safety caseloads are increasing by 30% to 50% each year, and emerging technology will be the only way to keep up. But how are powerful technologies like generative AI advancing safety and pharmacovigilance? Is touchless case processing a good or bad thing? And how do we balance AI, automation, and the human touch? We will get answers to those questions and more in this episode with Bruce Palsulich, Vice President of Safety Solutions at Oracle Life Sciences. His portfolio includes Argus Safety, the industry-leading adverse event case processing and analytics solution, and Empirica Signal, the standard for signal detection and risk management. He has more than 30 years of experience in the healthcare and life sciences industry, including 25 in pharmacovigilance.
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Episode Transcript:
00;00;00;00 - 00;00;13;22
What is pharmacovigilance? How can technology best handle the tracking of adverse drug events? And is touchless case processing a good or a bad idea? We'll get those answers and more on this episode of Research in Action.
00;00;15;01 - 00;00;18;28
The lead, the Building.
00;00;20;10 - 00;00;48;22
Hello, welcome to Research in Action, brought to you by Oracle Life Sciences. I'm Mike Stiles. Today we are talking with Bruce Palsulich, vice president of Safety Solutions at Oracle Life Sciences. Bruce's portfolio includes Argus Safety, the industry leading adverse event, case processing and analytics solution, and empirical signal, the standard for signal detection and risk management. He's got more than 30 years of experience in the healthcare and life sciences industry, including 25 and pharmacovigilance.
00;00;49;02 - 00;01;03;25
Now, why is that important? Well, International Data Corporation reports safety caseloads are increasing 30 to 50% each year. Bruce is intimately involved in tackling that volume. So, Bruce, thanks for thanks for being with us today.
00;01;04;05 - 00;01;06;00
Yeah, thanks, Mike. Happy to be here.
00;01;06;16 - 00;01;17;04
Yeah. Let's get acquainted with you first. How did Life's path bring you into life sciences technology? How did you kind of wind up at Oracle and what are you tasked with getting done there?
00;01;17;29 - 00;01;50;08
You know, back back when I was still in university, I actually started off doing software development and consulting with a medical device company. And so early in my career, it was working on the actual embedded software that controlled medical devices. And early on ended up joining a consulting firm that started off doing engineering, consulting on medical devices, and eventually working towards quality software and regulatory submissions.
00;01;50;24 - 00;02;17;04
And so came to Oracle in 2009. So we had acquired a company that was that small engineering startup that I mentioned. And this is the company that originally developed Argus Safety, so I managed the team that developed Argus safety originally and through my time at Oracle, I jumped out of a safety for a little while.
00;02;17;04 - 00;02;42;24
For about four years I was running our healthcare strategy. That was when we had a much smaller healthcare footprint than we now have with our acquisition of Cerner. But at the time we did a lot of things in sort of what was called health-information exchange, sort of the foundation for national platforms under Australia and Singapore and multiple provinces in Canada.
00;02;43;09 - 00;02;51;18
And after doing that for about four years and then I came back to the safety side of the business about ten years ago or so.
00;02;52;03 - 00;03;02;25
Well, did you always see yourself doing something in medicine and life sciences, like when you were younger, or did this was this a life path that kind of surprised you?
00;03;03;08 - 00;03;29;12
You know, I ommitted the part where for four years I actually worked in aerospace. So I even though when I was still at university, I started off in medical devices. I did take a job in aerospace for four years. But that's sort of left a hollow feeling and not the same sort of mission driven purpose. When you do have a role that's within the broader health care or clinical development.
00;03;29;12 - 00;03;55;04
So, you know, I think many people like myself that, you know, whether you're on the vendor side or whether you're on the the pharma side of drug safety or pharmacovigilance or even broader clinical development, I think you do appreciate that there's there's a calling and you feel more purpose driven life. I suppose working in a field that's helping individuals, helping patients.
00;03;55;26 - 00;04;13;27
Well, for our audience, and I'm deflecting because our audience is smart, this is mostly for me. Let's just level set. What's what's the main goal of safety and pharmacovigilance? And I imagine safety standards would apply across every step in that drug development process.
00;04;14;10 - 00;04;46;07
Yeah. So drug safety and pharmacovigilance is really trying to understand the safety of drugs that are under both clinical development as well as once they complete their clinical development and are approved for broad market use. And so clinical trials really focus on safety and efficacy, but that's done under controlled conditions with a limited number of patients and and sort of restricted patients as well.
00;04;46;07 - 00;05;27;27
And once a marketed drug is approved, it's going to be exposed to significantly more patients. And so during a clinical development, a clinical trial, if you had an adverse event that occurs in one out of 10,000 people, that's that's sort of defined as a rare adverse event or adverse reaction. You can imagine if you gave that to a billion people, maybe, for instance, in the example of the COVID vaccines, Now that rare adverse event that's only occurring in one out of 10,000 people is actually occurring 10,000 times in a billion people.
00;05;27;27 - 00;05;42;04
And so so really, you know, pharmacovigilance is looking at and trying to understand that benefit risk and manage that risk when it's being exposed under real world conditions to to actual patients.
00;05;42;24 - 00;06;11;20
So the study of a drug is hardly done after it's approved by the FDA and goes out into the public, the public market, that monitoring is still happening while safety is paramount, It can't be easy. I mean, for whatever reason, the public does seem to expect perfection without risk when it comes to their drugs. So, I mean, what are the biggest challenges that Pharmacovigilance and the industry has to deal with currently?
00;06;12;04 - 00;06;50;12
So, you know, getting back to sort of those controlled conditions that are under clinical trials, for instance, typically you're not looking at pediatric or children exposure. Quite often you're not dealing with elderly patients or immune compromised patients or patients taking multiple medications. You know, do you have the diversity within your clinical trials such that you're getting genetic differences that might exist within different populations and such?
00;06;50;12 - 00;07;21;16
And so so all of those are exposures that are going to occur during broad use of those products once they get approved. And so so pharmacovigilance is really trying to, you know, track that, trying to collect as many adverse reactions that occur. It's trying to evaluate whether or not those events truly are a reaction that's related to the drug that's being studied and the drug of interest.
00;07;21;16 - 00;07;46;15
Or is it just occurring, for instance, within the general background rate that you would expect within within a patient population? And so all of that analysis is to try and understand, is it more than correlation that just, you know, we have an adverse event that occurred with a drug? Is that coincidence or is that related to other drugs you're taking?
00;07;46;15 - 00;08;13;16
Is that a progression of the disease that the patient is taking a medication for, or is it something that is actually induced by by the drug of interest? And how serious is that reaction? And is that something that should be, you know, updated on the prescribing information that's tracked along with a drug and the, you know, communication and education that's done to the health care community.
00;08;13;16 - 00;08;16;08
So they understand the risks associated with the drug.
00;08;16;28 - 00;08;46;17
So I get the challenge, which is that in a clinical trial to get a drug approved and on the market, there's no way to cover every possible circumstance and every type of person and every type of situation where, like you said, there are other actions with other drugs. And I already get the enormity of the challenge of keeping track of all of those people, all of those interactions, all of those adverse effects.
00;08;46;20 - 00;08;59;13
I imagine technology is tackling those challenges, right, Or at least helping to tackle them. For instance, like how can we better efficiently do data management? How does that play a big role in tackling these problems?
00;08;59;28 - 00;09;24;29
Yeah, So the you know, we talked about the increasing volumes somewhat. It's still generally estimated that somewhere on the order of between five and 10% of the actual adverse events that occur are actually reported. And so many people might just say, well, I felt dizzy when I took that and so I stopped taking it. And, you know, did you ever tell your doctor, Well, no, I just manage that on my own.
00;09;24;29 - 00;09;56;21
So so really part of the challenge is how can you make it easier to collect a higher number of of these adverse reactions that actually occur? How can you reduce the burden on both the patient and on a health care professional to report those? The other is that, you know, we want to move beyond the handling and the workflow of processing these individual adverse event reports and get to a more of the emphasis being placed on driving or deriving insights from the data itself.
00;09;56;21 - 00;10;18;20
So so we want to make, as we deliver our own solutions, we want to make the pharma companies more efficient at being able to handle these sort of transactions. But with the real value out of that of then more, more effort and more value can be derived from the insights. From the data itself.
00;10;19;10 - 00;10;37;03
Yeah. I mean, there's a need to track adverse events that are happening all the time. The volume and the sources of that data increases exponentially. So you kind of touched on it there. How do you go about not just effectively managing the data flow but actually making it actionable?
00;10;37;14 - 00;11;18;12
So I think part part of this is, is within an ecosystem where perceptions are changing. And I'll say when I entered the field, you know, back in the mid nineties and such, the perception was sort of like an ostrich putting their head in the sand or something. And, and I don't want to know about what hasn't specifically been reported and, and Pharmacovigilance and drug safety was really looked at as sort of a a tax on the business a cost of doing business and wasn't appreciated as a valuable information asset that can be leveraged, you know, within a biopharma organization.
00;11;18;12 - 00;12;00;26
And so now I think PV data being an expensively curated data set, is now looked as a valuable information asset within organizations. It can be used to identify new indications, it can be used to inform drug discovery and portfolio prioritization. I think more and more we're seeing safety used as a competitive differentiator and certainly we saw that with the COVID vaccines and those that were commercially successful versus those that perhaps were perceived as having a more risks associated with those.
00;12;00;26 - 00;12;26;19
And towards this, I think, you know, we're looking at, you know, how can advances in data science, technology, things like machine learning, predictive models, generative AI, how can they be leveraged in order to process and be able to make use of these increasing volumes of information as well as diverse sources of adverse event information as well?
00;12;27;07 - 00;12;42;22
Yeah, that's where I want to go next. Are you seeing cloud based platforms and AI transforming pharmacovigilance? I mean kind of balance the hope and the hype for me. How do you see those technologies changing, how we approach drug safety and in like, say, the next decade or so?
00;12;43;05 - 00;13;18;23
So I really think and not not even just in this field, but in all fields, if you look at sort of the proliferation and the scaling of accumulation of data and information, it really requires new methods to approach that. So I do think that things like the large language models like Generative AI, are really going to be transformational into how we leverage this data and information specifically within health care and life science, but but also broader, I think, as a global population.
00;13;18;23 - 00;13;50;04
But so you can imagine even things like, you know, querying the data versus the natural language conversation, you know, perhaps you could ask how rare is this actual event or how does the rate of this adverse event compare for my drug versus other drugs within the same therapeutic class or given the volume of adverse events for this drug in 2023, how might how many reports might we expect to receive in in 2024?
00;13;50;04 - 00;14;26;08
Or are there clusters of patients that appear to be more likely to have this adverse event than other patients? And could you describe those differences? And so those I think, are all sort of examples that we're going to move from strictly having skills of of a data science list or query builder, a developer and such accessing data to sort of expose those questions of the data closer to the the individuals that are forming the question.
00;14;26;08 - 00;15;06;24
And so I think right now, you know, we really don't know what sort of insights or what sort of interactions are going to exist between these diverse data sources that are going to lead towards improved insights, improve patient safety. You know, we really want to, you know, identify what drugs work for, what patients and inversely know which patients shouldn't be exposed to certain drugs and and what characteristics, what scientific information is out there already, both broadly, you know, basic chemistry, genomics, pharmacokinetics, things like that.
00;15;07;12 - 00;15;10;29
But then bring that down to the experience of an individual patient.
00;15;11;18 - 00;15;24;29
Well, you've talked before about touchless case processing and what that could look like in the future. Tell us what that is and what companies should be doing now to start transitioning to that kind of model.
00;15;25;17 - 00;15;55;05
So I think sometimes the the phrase touchless case processing can sound a little scary, you know, that humans are going to be completely out of the loop and such. And I think the industry is generally looking for something a little bit more incremental. So we're not looking to say all cases should now be touchless. We're looking at things like, well, perhaps non-serious cases that don't provide a lot of new scientific information.
00;15;55;05 - 00;16;37;28
Perhaps those should be handled automatically by the system, perhaps for drugs that are well understood or have been on the market for a long time. Perhaps those would be better candidates for having automated case processing then things that are going to be a new a new drug on the market with less experience and exposure, perhaps cases that are received electronically and, you know, or cases from partners, you know, quite often they'll be global relationships between one pharma who partners with another pharma to to market that product in another region of the world.
00;16;37;28 - 00;17;03;22
And so you're receiving adverse event cases from this partner who who is originating those from patients or health care professionals. But if you're receiving that from a partner, you probably trust that they're sending it to you and maybe you can process that item automatically. The other is, is I think again, people get get a bit concerned if you say, well, this is going to be end to end and no human ever touched it.
00;17;03;22 - 00;17;35;06
And now we're going to be reporting this. You know, it doesn't necessarily have to be end to end. It can be the high volume of effort activities like doing the actual data entry. It can be decision support to support perhaps the causal assessments or to assess whether or not this is team serious or to look at is this an adverse event that's already listed on the the product label or prescribing information So it can be, you know, specific work steps are workflow steps.
00;17;35;06 - 00;18;15;27
Could be touchless, but overall, you know where it is appropriate. I think we still want humans in the loop to to oversee the process overall. So I think there are tremendous opportunities again, to take repetitive non value added processes out of and automate those from from requiring human effort to process those and allow the humans to focus on, you know, insights and focus on more value rather than these repetitive steps that that computers are well suited to be able to process as well.
00;18;15;27 - 00;18;39;08
You said something earlier, and that's very legitimate that, you know, a lot of patients will start taking a drug and experience some kind of adverse reaction to it and then just stop and not even tell their doctor about it. No one's ever going to know about the adverse reaction that they had. So there's even a reliability factor on the part of the patients and their willingness to report.
00;18;39;27 - 00;19;05;15
How far away are we from being able to have essentially a digital model of patients that drugs can be tested on? I mean, am I going way far ahead in the world of science fiction where in Silico gets kicked up a notch and safety procedures are tested on not real people, but essentially digital versions of patients?
00;19;05;15 - 00;19;35;22
Yeah, I think this whole concept and people may have heard the term digital twin and such is is obviously very interesting and I think we'll have certain benefit. I think, you know, certainly, you know, establishing toxicity and such would much better be supported through some of these models than than experimenting on on animals or on humans in order to establish toxicities and such.
00;19;35;22 - 00;20;12;08
And so so I think, you know, it's going to start from sort of the bottoms up that way when you're looking at those types of exposures. And I think as we get again, as we sort of stitch together these diverse data sources and have tools to be able to look for correlations and linkages that that are there, that would be difficult for humans to ascertain, then I think, you know, that will allow us to sort of advance these digital models that that represent a human response to medications and such.
00;20;12;08 - 00;20;44;18
So I think that's something that is definitely being advanced and we have pockets of that, and those pockets will ultimately end up being combined into a larger simulation of, you know, humans. So yeah, it's certainly an interesting area. And even myself, you know, it took me a while to sort of get my head around what that concept of digital twin and how that's going to benefit clinical development as well as is health care overall.
00;20;45;16 - 00;21;06;07
Well, we touched on the balance of hope and hype, but there's another balance here that you also touched on a bit. It feels like we want every advantage that technologies and automation and machines can bring us, but then we only trust those things up to a point. We do want human experience, human judgment and expertise to kind of have the final word.
00;21;06;07 - 00;21;13;22
So how do you view where that balance is now between tech and human? What gets us to the lowest error rates?
00;21;14;07 - 00;21;47;22
So I think, you know, one of the perception challenges that exists right now is that people think the humans are probably doing a better job than they really are right now. So if you gave the same health care record source document to five different people and said, you know, take from this piece of paper and enter it into the system, you would probably end up you would not end up with five identical versions of data entry from abstraction from that source medical record.
00;21;47;22 - 00;22;15;14
And so, you know, which one of those five is right. And what's the error rate there? And so I think you would normally say that humans are going to be somewhere on the order of six or 7% error rate for that type of work. And so even in manual processing is adverse event cases, typically there's going to be some sort of QC sampling that's trying to keep a handle on detecting errors and keep a handle on the overall process and such.
00;22;15;14 - 00;22;43;04
And so looking at how, you know, automation or machine learning is going to apply similar things are going to occur. You still want some checks and balances in order to know that you still have control of the automated process and things that are getting into medical judgment. I still think we we want to stick within what we would say is sort of augmented processing or decision support.
00;22;43;04 - 00;23;27;27
Speaker 3
So you want to provide assistance to the person making those judgments and say the system has determined that we think this might be related to this drug and based on these factors, why we think that might lead to that decision. Again, it would be up to the health care professional to make the final judgment there. So I think we are you're trying to bring the facts, bring the the right parameters and such into view so that the human can make the best decision, given the data points and the assessments that are being being suggested by by the system.
00;23;28;04 - 00;24;04;15
So I think we're still, you know, I was listening to NPR yesterday and they had a discussion on self-driving cars and there are self-driving cars ever going to get to the same accuracy and insights of of a human. And I think, you know, this is similar here, although probably, you know, certainly a different problem than looking at real time sensors in forming a automated self-driving car, but trying to look at human experience, human judgment, you know, how do we model some of those?
00;24;04;26 - 00;24;16;25
I think right now we'll stay in this augmented decision support mode for many of these, you know, clinical medical decisions and certainly leave the final judgment up to a clinician.
00;24;16;25 - 00;24;34;24
So, yeah, I remain terrified of human drivers. So in your role at Oracle Life Sciences, how is Oracle specifically leveraging these emerging technologies that we talked about like AI and big data to enhance drug safety and pharmacovigilance?
00;24;35;10 - 00;25;15;20
So there's a number of technologies and that's that's one of the benefits of being part of the broader Oracle, is that, you know, you kind of have all of these other areas and big areas of investment in AI and data science and high capacity compute and large language models and generative AI. And so so we get to it's like going to the toy store or something and decide which which things already have been built that you get to pull off the shelf and decide how we could apply those into our area of drug safety and pharmacovigilance.
00;25;15;20 - 00;25;45;13
And so, for instance, we just added the translation facility and, you know, out of the box in our Argus Cloud, you now have a translate button and it doesn't sound like a big deal, but if you were using an external tool before and then had to cut and paste and you were doing that 20 or 30 times within an adverse event report case to report it to local regions, just taking out that cut and paste and making it as a button straight in the system.
00;25;45;13 - 00;26;07;27
And by default we'll hook it up to the Oracle Cloud Translation Service. But if you wanted to hook it up to Google or you wanted to get up to a life science translation service, you could do that as well. Again, we're trying to look for where there are bottlenecks and we're trying to go out and look at where can we leverage an investment that Oracle's already making and then apply that into our specific field.
00;26;07;27 - 00;26;52;00
And, and part of that's what's exciting about our acquisition of Cerner is that, you know, I may have had a use case that sounded interesting in Pharmacovigilance. Maybe it's a case narrative generation or a case narrative is not all that different than a discharge summary for a health care record, or if you're doing a health care referral letter for referring the patient to a specialist and giving a summary of their their specific case and such, that's not that different than perhaps auto generating a letter that is a follow up request for collecting additional information on an adverse event case and so on.
00;26;52;00 - 00;27;17;28
Many of these there's there's overlap and we're able to team up with the teams that are focused on the health care use cases and add on our life science use cases and, you know, really benefit both teams or sometimes health care is leading the charge and sometimes life science is leading the charge. But ultimately that power together is like a multiplier, not not addition.
00;27;17;28 - 00;27;31;14
And and I think is a big benefit. And one of the big benefits of our of our acquisition of Cerner and the fact that we now are a leading health care company, in addition to, you know, what we've traditionally done in life science.
00;27;32;06 - 00;27;48;28
Yeah, there are a lot of industry players in life science. So is is what you describe what makes Oracle a real differentiator in the space when it comes to safety and pharmacovigilance? So things like combined assets and the Cerner acquisition.
00;27;49;11 - 00;28;25;29
Yeah I think there's there's a couple of things. One is sort of foundational with our cloud infrastructure and capacity there. For instance, we have high capacity compute and GPUs and just within our drug safety solution area, you know, we have two GP2 cloud instances available, dedicated 100% to our use and that's multimillion dollar worth of compute that we have dedicated to to our team of data scientists working to NPV.
00;28;25;29 - 00;28;58;05
And that would be difficult, not impossible, but difficult for a lot of other vendors to sort of dedicate that sort of compute capacity in such just to their life science use cases. Now the other I think is is around, you know, the acquisition of Cerner. So we talked about we now have a point of care footprint. So where, you know, clinicians are using Cerner software as the electronic health record when they're interacting with patients.
00;28;58;05 - 00;29;28;19
And so if we want to collect information as part of that point of care relationship, we can do that if we want to leverage, You know, we have something that's called the Learning Health Network that has a electronic health record, real world data asset. And so companies that our health systems sign on to use this because they they want a few benefits, they want access to clinical trials.
00;29;28;19 - 00;29;55;07
So they want their their patients and such to be able to be included within cohort selection and recruitment, site selection and recruitment for clinical trials. They also want to understand how they're delivery of care matches against other health systems across the country and eventually across the globe. So that they can sort of benchmark and compare how they're doing.
00;29;55;16 - 00;30;23;05
So that ends up creating this research data asset That, for instance, is very important for drug safety and pharmacovigilance, so that if you have a particular risk or an adverse event that's been reported against your drug or therapy, that you can then go out and say, well, is that just a correlation? Is there enough information within these individual cases to establish causality to the drug, actually cause that adverse reaction?
00;30;23;18 - 00;31;11;09
Or do I really need to go investigate that and understand its usage within the, you know, electronic health care record or claims data? And so so that's one of the areas that we are really focused on right now of sort of benefiting this better together with with the combined assets of and expertise between Oracle and Cerner is how can we leverage that real world data to understand and investigate risks that have been reported in adverse event reports to be able to go out and and understand real world usage there and and look at and understand how many patients are taking this drug, how many patients potentially had this reaction?
00;31;11;25 - 00;31;31;17
How many patients generally have this reaction not taking our drug, you know, understand those background rates and such. And so it's another level of understanding of the benefit risk once you have not only the adverse event reports, but the ability to research these within a real world dataset also.
00;31;32;03 - 00;31;38;03
Okay. I've got one more question for you. The all those warnings at the end of the pharma TV ads, is that because of you?
00;31;38;24 - 00;32;07;22
Well, ultimately, you know, I feel like sometimes we're plane name that tune or something. So a commercial comes on and I'll say, Oh, that's a pharma access to pharma y company. And you know, I'm usually right on naming the drug to that company. But, but it is, it is vitally important, you know, what is being done and where traditionally pharmacovigilance has sort of been a retrospective.
00;32;07;22 - 00;33;02;11
What can we learn after it has occurred? We're really trying to move towards what or labeling as precision pharmacovigilance, which is better understand that safety profile, better understand that risk benefit profile, not at these broad population levels that might be by by gender and age group, but getting down to smaller and smaller subpopulations and ultimately ideally to be able to go back and impact proactively the care of an individual patient where we might be able to identify based on a certain patient characteristics, a patient history, genomic marker, current labs, other concomitant medications they may be on presently, that maybe there is a higher risk to that individual patient of therapy versus therapy and provide that
00;33;02;11 - 00;33;39;18
information to the clinician that's treating the patient at that point of care. So so we intend to continue to drive towards that advances in drug safety that can improve overall population level help, but want to drive that down to to the ability to inform care around an individual patient. And thus, you know, when we see and hear those commercials and we hear the list of adverse events that are potentially associated with that drug, to give us better context, to say, well, what does that mean for me as bruise versus what does that mean for Mike?
00;33;39;18 - 00;33;51;15
And maybe one of us needs to be concerned and maybe one of us doesn't, and wouldn't that be great rather than just hear the list and and know that randomly that might be meaningful or not so obvious?
00;33;51;15 - 00;34;08;19
It's a vital part of drug development. And it's been interesting to hear what approaches are being taken and who's leading them. We appreciate you being on the show. For those who are interested in Pharmacovigilance and their interest has been tweaked, is there any way they can connect with you or get more information on what's going on?
00;34;09;09 - 00;34;51;14
So for me, I can be reached at [email protected]. If you're on any one of your web search engines, you could just search on Oracle pharmacovigilance. The other is that we do have a community that we call the Oracle Safety Consortium. So if you search on Oracle Safety Consortium, you'll come up with and that's sort of our end user community where we have regular monthly events and such that are discussing industry, but as well as Oracle Solutions and how we're addressing the needs of industry through this sort of peer consortium group as well.
00;34;51;14 - 00;35;00;09
So those are sort of three ways that you could either follow up with me individually or learn more what we're doing here in Oracle for drug safety and Pharmacovigilance.
00;35;00;24 - 00;35;29;25
All right, we've got it. And if you want to see if Oracle can accelerate your life sciences research, just head over to Oracle dot com slash life dash sciences and you'll probably find out what you need to know. Don't forget to subscribe to this show and join us next time for Research in Action. -
How is clinical research becoming more patient-focused and more convenient for patients to participate in clinical trials? Why is a decentralized approach especially important concerning rare diseases? And how will digital innovation advance the way clinical research is conducted? We will learn those answers and more in this episode with Scott Schliebner, an innovative life sciences executive with 30 years of experience across the biopharma, CRO, medtech, and non-profit sectors. With a strategic and consultative approach to building and growing life science businesses, Scott has developed relationships, partnerships and collaborations that have driven commercial success. His vast experience includes leveraging real-world data and real-world evidence (RWE/RWD), leading technological innovation, and driving patient-focused paradigms to accelerate clinical drug development. Scott is an active board member, advisor, and mentor and his passions lie with infusing data and innovation into life sciences organizations—especially where rare diseases are concerned. He is currently the leading executive at Rare Clinical.
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Episode Transcript:
00;00;00;07 - 00;00;24;21
How is clinical research becoming more patient focused and more convenient for patients to participate in? Why is a decentralized approach especially important when researching rare diseases? And what is the most likely future for how clinical research is conducted? We'll get the answers to all that and more on Research in Action.
00;00;24;23 - 00;00;48;24
Hello and welcome back to Research in Action, brought to you by Oracle. I'm Mike Stiles and our guest today is Scott Schliebner. Scott is a leader and innovative life sciences executive with 30 years experience across biopharma, CROs, medtech, and nonprofit. He's developed relationships, partnerships and collaborations that have driven commercial success with a strategic and consultative approach to building and growing life science businesses.
00;00;48;27 - 00;01;16;06
Scott got a lot of experience, including leveraging real-world data and real-world evidence, leading technological innovation and driving patient focused paradigms to accelerate clinical drug development. And he's an active board member, advisor and mentor, and he's all about infusing data and innovation into life sciences organizations, especially where rare disease is are concerned. And last but certainly not least, Scott is the leading executive at Rare Clinical.
00;01;16;09 - 00;01;35;01
Scott, we're glad to have you with us. Thanks for letting me grill you with all these questions. Thank you, Mike. My pleasure to be here with you. Well, let's start at the beginning. A fine place to start. What got you into the field of clinical research and drug discovery and why this special focus on rare diseases? Yeah, great.
00;01;35;01 - 00;02;04;13
It's a great place to start. I think, like a lot of my colleagues in this clinical research, clinical drug development profession, a lot of us sort of find our way into this field as there aren't necessarily a lot of like formal training programs or pathways necessarily. So for me, I was in graduate school, I was doing some more like I would call more basic science, more basic research that I found my one day struggling to.
00;02;04;16 - 00;02;22;00
As I was writing a grant for a professor, I found myself struggling to justify why, why this was really important. I kept saying to myself, Yeah, this doesn't really seem very applied. Is this really make a big difference? I, I can't convince myself this is critical. How am I going to convince a funder of our grant that this is really important?
00;02;22;00 - 00;02;44;17
And it kind of was a little bit of a light bulb moment for me that made me realize while I loved the field of research, I needed to be doing something that was more applied and could have a little bit more of a direct impact upon people. So it sort of led me to the clinical drug development space and clinical trials, and I got started back.
00;02;44;17 - 00;03;12;21
It's been a couple of decades now as I've been around for a little while, but it got started in a sort of like a biotech clinical research setting, helping to design and manage clinical trials and have been sort of engaged and passionate about this industry ever said. So it's been it's been a fun ride. But again, like a lot of people in this space, I think I stumbled into clinical research, maybe not accidentally, but, but, but there's not an obvious clear entry point for some of us.
00;03;12;23 - 00;03;33;25
Yeah. So I get that you, you got into the bio research space and drug development and those kind of things develop that interest. And I get that you wanted to make a real impact that you could feel like you were making a difference. Is that where the focus on rare diseases came into play or when did that? Yeah, thanks for following up on that part of the question.
00;03;33;25 - 00;04;12;02
I think that, yeah, after having been in the industry for a little while, you know, about, I don't know, this was probably like 12 years ago or something. Rare diseases at that time were really still a little bit. They weren't certainly a hot and sexy topic like they are today in 2023. But I came across some patients, I came across some patient groups, and I also came across a couple of clinical trials and I realized that what we were trying to do and what was required really to function and develop drugs in the space of rare diseases really required, honestly, a completely different, really way of operating a completely different paradigm than what we
00;04;12;02 - 00;04;48;16
were doing in most of clinical drug development. And with, you know, with our biopharma industry being pretty risk averse. That's a theme I think you'll hear come up probably a lot today. In our conversation. There hadn't been a lot of appetite or initiative around trying different approaches or looking at things differently. And these rare disease studies for sort of a countless sort of logistical and medical and scientific reasons really require a very different approach of, you know, you're talking about small populations that are geographically dispersed.
00;04;48;16 - 00;05;23;21
You're talking about patients that may have they may have to go through a diagnostic odyssey. A lot of people don't know about these disease states. There's a host of challenges that kind of come together and create a scenario that is even more complicated than your average challenging clinical trial. So also, when you look at the fact that there's something like 10,000 individual rare diseases individually, they're all rare little sub populations, but taken together they make up about 10% of the U.S. population and about 10% of the global population.
00;05;23;21 - 00;05;50;24
So it's it's a big area of unmet medical need. When you look at it from a big picture perspective, when you drill down into individual disease states, individual patient populations, you notice that these patients and families don't have any therapies, they don't have any treatments, they don't have a lot of hope sometimes. And clinical trials. And this world is really their only source of hope at times.
00;05;50;24 - 00;06;10;22
It's less of an experiment and more of a care or treatment option for rare disease patients. And so I found myself really immersed and passionate about this area and felt like it was a space that really needed new approaches. And I've been happy to kind of delve into that and try to make a difference there. And what is the state of that research like?
00;06;10;24 - 00;06;39;24
Is there reason for people with rare diseases to have hope? For instance, there are people in my family who have ankylosing spondylitis, which is a relatively rare form of arthritis. Is it appropriate for them to have hope that in their lifetime something's going to happen? Or are these populations so small and the research to develop drugs for it's so difficult that, you know, we're looking at 50, 60 years in the future before we make any progress.
00;06;39;25 - 00;06;55;20
Yeah, it's a great question. I mean, there really is a really broad spectrum here when we talk about rare diseases. We have such a such a large number of them. I think that the short answer is there is hope. And in a lot of cases that hope is in front of us or is on the very near horizon.
00;06;55;22 - 00;07;18;09
There certainly are other scenarios where another disease states where it's going to take a while and that hope is a little further out to be seen. But the good news is that we've well, there's been a lot of mobilization, there's been a lot of innovation and a lot of attention devoted to rare diseases over the last decade, 15 years, we've seen a lot of drug approvals.
00;07;18;11 - 00;07;39;24
We've seen a lot of companies, we've seen a lot of investment in biopharma biotech firms come into the rare disease space, whether they are small little biotech startups or whether they're the big pharma of the world. Everyone sees this as an opportunity to help develop drugs and help people. And in an area that really needs as much help as we can provide.
00;07;39;24 - 00;08;15;29
So there's a lot of hope. Some of these disease states are a little more clear than others. We understand the biology and the genetics, and maybe we can develop targeted therapies that help these patients some of these other more obscure, ultra rare or nano rare diseases. We're still learning who the patients are and how do we diagnose them and before we can develop a drug and show that it works and that it's safe in those populations, we need to first even understand a little bit about the natural history of some of these diseases and how they progressed kind of on their own and what kind of end points we would want to choose and some
00;08;15;29 - 00;08;37;27
things like that. But the bottom line is that there's a lot of hope, there's a lot of progress, there's a lot of activity, there's a lot of investment. I think there's a fair amount of awareness. We've seen a lot of progress here with people, with people and organizations and industry really getting into the space. Of course. With that said, there's a lot more that we can be doing.
00;08;37;27 - 00;09;02;21
There are a lot of disease states that really need some more attention and more funding and more research. But from where I sit, we've made some great strides and I hope to kind of keep accelerating that progress. Well, science is kind of inherently a social enterprise, but despite that, scientists and clinicians seem to work mostly behind closed doors, maybe even a little too far removed from the people they're actually working to help.
00;09;02;23 - 00;09;24;27
The pandemic changed a lot of things, but for one thing, Big pharma got kind of pushed out of its risk averse comfort zone because they had to speed the science and adopt more openness. So what do you think COVID did to innovation in the clinical research space? What changes are permanent and which ones aren't? Yeah, this is a fantastic topic.
00;09;24;27 - 00;09;57;11
We could we could spend a lot of time on those, I think. Well, necessity being the mother of invention, I think that COVID presented a lot of unique challenges and picking on my risk averse colleagues who may not want to necessarily try something new or go out on a limb with some sort of more risky, unproven approach. COVID forced us to reconsider how we were doing things, and it forced us to keep clinical trials going in a in a manner and keep them operating.
00;09;57;11 - 00;10;32;15
When we couldn't go to clinics or go to hospitals or when we had to social distance. And it forced us to really rethink a paradigm that had not really changed in many decades. So if you rewind a little bit to pre-COVID, there was several movements out there around creating more patient focused approaches. So this idea that you mentioned science being inherently a social enterprise, I envision a lot of clinical protocols and clinical trials being they're often developed in a little bit of a bubble.
00;10;32;18 - 00;11;01;01
Sometimes I'll joke and say in a conference room in New Jersey, right, these clinical trials come to life and are sketched out and designed in a little bit of an insulated bubble of sorts that don't really take into account the perspective and the input and the needs and the voice of the end users, namely the patients themselves. So similarly to the fact that, you know, you may have an iPhone sitting there on your desk next to you.
00;11;01;04 - 00;11;26;27
Apple, of course, didn't design a camera to put on their phone and say, let's see if people want to use a camera. The camera was designed, of course, by consumer demand and designed for the people using it. Ironically, even though science and even though clinical drug development is completely dependent upon patients participating in clinical trials, we rely on them and their data to move things forward.
00;11;26;29 - 00;12;06;22
They're very rarely considered actually, in the design process. Right. That's the irony, is that we rely on them. We must have their participation, but they're kind of an afterthought historically when it comes to designing a clinical trial and thinking about how to implement it. So that being sort of the baseline of how we've operated COVID hits and all of a sudden our world is interrupted and some of these novel approaches that had been being developed, these mobile health platforms, early COVID, we were talking about how can we make clinical trials, quote unquote virtual or hybrid with some of the language we were using.
00;12;06;24 - 00;12;35;18
How do we instead of requiring patients to maybe travel long distances to a clinical site or an academic medical center? Sometimes it could be a weekly visit for 52 weeks. A lot of times that's not going down to your neighborhood primary care physician. It might be driving into Manhattan and going to Memorial Sloan-Kettering every Friday afternoon and taking time off of work and away from your family and your children to participate in the clinical trial.
00;12;35;21 - 00;13;02;09
The bottom line, clinical trials were really not designed for patients, often not realistic and often not feasible. So when we ran into COVID and the challenges that kind of shutting down hospitals sort of created, it forced us to adopt this what we ended up naming decentralized clinical trial paradigm, and it forced us to think through, well, how do we bring clinical trials to patients themselves?
00;13;02;11 - 00;13;25;15
So this was a long, long overdue need that was out there. Again, we've been operating in a little bit of an archaic fashion for quite a while, putting out studies that were not realistic for patients. But when the world around us sort of crashed down and we needed a new approach, we adopted this more patient focused paradigm simply out of need, I think.
00;13;25;18 - 00;14;05;21
So there's been some traction with this. Decentralized clinical trials have become a common term in this industry. We have the Decentralized Trials and Research Alliance that was formed in 2020. There's a lot of companies on investment that have come up to develop this new paradigm of, instead of these critical end users, patients, instead of having them have to travel long distances and inconvenience themselves and for a scenario to be very hard for them, let's create something that revolves around them, that's create a patient centered, patient focused approach where we bring trials to patients in their homes.
00;14;05;21 - 00;14;28;07
And so we do this via some tools like apps on our phone and a mobile health platforms. We do this, of course, now via telehealth and things like that that have become much more routine and regular. We're able to collect data remotely. We're able to push out sort of questionnaires and quality of life and clinical outcome assessments to patients wherever they are.
00;14;28;11 - 00;14;53;23
We're able to send nurses to their home to help them administer drug or check on how they're doing or evaluate their symptoms. So this transition that COVID has sort of forced us into, again, necessity being the mother of invention has forced a more patient focused approach that I personally think we've been really long overdue. So I think of that as a little bit of a silver lining of the pandemic.
00;14;53;25 - 00;15;24;08
There's been some good progress, I think, made as a result of that. But these technologies that you're talking about that are used to monitor these patients in these trials, like maybe wearable technologies or whatever, what's the reliability level of that? Does a lot of this rely on the patient just reporting accurately what's going on? Well, as we've come out of the pandemic now, the interesting sort of dynamic is does this new model really stick around when it's not as needed as it was during COVID?
00;15;24;11 - 00;16;06;16
Do we continue to move forward in this new innovative approach, or do we revert back to the way it was? And along with that, are these sort of challenges maybe, and complications that come along with this decentralized approach, like remote data capture, lots of data sources coming from various areas, various directions, wearables, as you've said. And there's also this kind of push also to not only engage patients where they are, but also to collect data in a little bit of a real world setting in this, you know, real world evidence, real world data, you know, kind of concept around, you know, we're conducting clinical trials that are controlled and we're we're looking at specific variables
00;16;06;16 - 00;16;25;12
and we're looking to evaluate safety and efficacy. But at some point, if this new therapy is going to be approved and patients are are using this in their daily regular life, how it's better for us to also know what that's going to be like, like to study that real world experience now even in the context of a clinical trial.
00;16;25;12 - 00;16;44;27
And so you are even seeing regulators like the FDA encourage the collection of more real world data for that to be used to supplement more controlled clinical trial data. So you're having a little bit of a mixture here and a little bit of an evolution, I would say, in terms of the data and evidence that we're bringing in.
00;16;44;29 - 00;17;12;08
But your point, there's there's lots of challenges with that as well. Now we have a lot of different technology platforms. We have a lot of data sources that need to interface and communicate and integrate. There can be complexities with having lots of different technology platforms for clinical sites and patients to use. You mentioned the reliability component. Are we using instruments that are validated and have been used over and over and we can trust?
00;17;12;10 - 00;17;39;17
So with this new approach of collecting more data, collecting data from different sources, collecting real world data, we also have to make sure that we're integrating it well, that we're not overly burdening both the clinical sites and the patients. But the trend that we're seeing is that each year now, clinical trials become a little bit more complex. They're collecting more and more data each year.
00;17;39;20 - 00;18;10;11
Data points in these clinical protocols are becoming more extensive. Right? So, you know, that's more data that becomes a little bit more of a burden for a lot of people. And it also takes us back to this, this mantra of, okay, let's remember the patients again, because if you're going back to my example, if you're a scientist or a drug developer in a conference room in New Jersey, you may very well want to collect all kinds of interesting data points that you think are going to be informative to you.
00;18;10;11 - 00;18;41;03
And if everybody sort of pours in all their sort of data requests, you can see this sort of ballooning, mushrooming clinical trial becoming overly burdensome. And let's not forget that each of those measurements require something of a patient. So there needs to be some kind of balance here between gathering more data, real world evidence controlled clinical trial data, but also remembering that, you know, the patients are producing that data and let's not make things overly complicated here.
00;18;41;03 - 00;18;59;00
So there's a little bit of a dynamic there that I feel like we're right in the midst of it. I'm interested to see how this kind of plays out a little bit. Well, yeah, And that's being seen everywhere. There is a ton of data. Companies are drowning in data. Some of them know what to do with it, how to handle and process it, process it.
00;18;59;00 - 00;19;22;20
Some don't, but it is crucial. There are challenges and benefits to being data focused, especially where sensitive data is concerned. Things like evolving standards. I mean, is too much data a problem? Are these supposedly connected platforms causing redundancies and other headaches? Yeah, I mean, I think so. Probably depends on who you ask, right? I'm sure a lot of people would say more data, the better.
00;19;22;20 - 00;19;45;16
Let's get everything we can. It'll inform us better on a patient experience or on the effects of a drug. At the same time, though, right, there's logistical challenges. Where are these pipes of data running into in the while? It's happening across all kinds of industries in the clinical research, clinical drug development space, you also have the added piece of patient privacy.
00;19;45;19 - 00;20;11;07
And in this country, HIPA and the need to, you know, keep patients data safe, private, de-identified as well. So when you're implementing different platforms that are collecting data at a clinical site, but maybe also at a patient's home and also maybe a wearable as a patient is, you know, walking around and just their daily life and collecting data via that.
00;20;11;09 - 00;20;34;22
Where do these all come into? How are they getting analyzed? Is it secure? We can very easily and very quickly make things more complicated than we needed to. I personally think we should be mindful of not collecting every possible data point we might have an interest in. We might not even know what we want to do with that data today, but that might be nice to have down the road.
00;20;34;24 - 00;20;56;18
I do realize that's great for science and discovery and exploration, but again, in the context of a clinical trial, you know, the environment we're in right now with clinical trials is that more than 60% of all clinical trials are behind schedule due to enrollment. And even when patients do enroll, we also have a lot of patients dropping out and not staying on studies.
00;20;56;18 - 00;21;27;09
So the retention of patients is also a problem. And so while we balance collecting more data, while we balance more complicated, complex clinical protocols as we're increasing the burden at times on patients and I use this patient word a lot, but really we're talking about people, right? We're talking about people like like Mike and I who have jobs, who have lives, who have hobbies, who have families, work people, and we have other commitments in our lives.
00;21;27;09 - 00;21;50;24
And we can't just drop everything to participate in a clinical trial. So the the concept of if you build it, they will come doesn't really apply here really anymore. And we need to be thinking about building things that will appeal to people and be realistic and feasible for patients, both in terms of time, commitment and travel and there might be you know, there might be emotional issues.
00;21;50;24 - 00;22;14;12
There's all kinds of domains of burden that we've learned. And this balance of like, wow, we can collect data from anything anywhere, any time, that's great, but let's maybe we need to real that and a little bit here and balance that out with what can a human being really handle And are we overly burdening patients because we're finding that people are just declining to participate, which is actually.
00;22;14;14 - 00;22;40;16
So this idea of more data better can actually be slowing down drug development in a way because clinical trials are delayed now due to enrollment. So there's an interesting dynamic there that I think progress in this area, real world evidence, remote data capture, lots of data sources, is also creating a more complex environment that I think is giving giving some patients pause to like before and roll in that study.
00;22;40;16 - 00;23;09;24
I'm going to I'm going to think twice. So really interesting thing that's really very fluid and dynamic. I think this is kind of changing on a monthly basis these days. Well, let's turn back to rare diseases, because I think we can all agree plenty of innovation is needed to make a dent in those. But what kind of innovations and as I hear you talk, it's like, okay, there's challenges to this patient centered research, decentralized research as it is now.
00;23;09;24 - 00;23;37;12
You're talking about rare diseases where the population is small to begin with, it seems. I mean, what are the most effective things we could be doing? Is decentralized trials the answer? Yeah. Well, I think, you know, in that rare space, you're right, clinical trials are challenging. Clinical trials are behind schedule. Clinical trials might be overly complex. And I think that happens in worlds where we could be dealing with a fairly common, you know, diabetes or arthritis study.
00;23;37;14 - 00;24;03;10
When you overlay those challenges on a disease area and on a patient population, that is rare or ultra rare, you know, it becomes magnified, it becomes extra challenging. You know, some of those challenges include things like, well, by the nature of the name rare diseases, there's very few patients with that disease. Sometimes those patients and some of these disease states are very, very small.
00;24;03;12 - 00;24;25;08
And people are, of course, geographically spread out. So if you wanted to learn more about a disease, study it, run a clinical trial, what have you. You know, you're not just opening up a clinical center in New York City and enrolling all those patients. You might be needing to go to multiple countries around the globe just to be able to find a couple dozen patients.
00;24;25;10 - 00;24;50;26
So you've got a dispersed and few and far between patient issue is challenging to come to come up with. And again, by the nature of, you know, the definition, there are physicians and our principal investigators in clinical research sometimes don't see a lot of these patients. So for those of you listening that have that know a little bit about the rare disease space, you'll know that that's the symbol of rare diseases is the zebra.
00;24;51;02 - 00;25;13;17
And the reason for the zebra symbol is, you know, back in the fifties, there were some physicians that were training medical students, and they used to use the phrase that, you know, trying to teach their medical students that, you know, keep things simple, Don't overly think it don't overly complicated. If you think you're sort of stumbling upon a diagnosis, you're probably right.
00;25;13;17 - 00;25;34;13
So the phrase was, you know, if you hear hoof beats, it's probably a horse. Right. And the rare, rare disease community, of course, sort of shudders at that idea and says, well, hold on a second here. You know, if you hear hoof beats, don't forget that 10% of those diseases could be a zebra. Right. And the zebra or the rare disease has been one to not forget about.
00;25;34;13 - 00;25;55;17
So we we also have challenges with physicians that may come across a case or a patient like that once a year or once every couple of years. So there might be a limited knowledge about the disease and the care of those patients. It also makes those patients being diagnosed initially really, really challenging. I mentioned earlier the diagnostic odyssey.
00;25;55;19 - 00;26;19;18
It's not uncommon for a rare disease, patient or family to see seven, eight, nine, ten physician ones go to all kinds of different hospitals and institutions and have a variety of sort of tests done to figure out even what they have. Right. They're craving a diagnosis so they can figure out what's going on with them so that then they can start to think about how do I get this treated.
00;26;19;18 - 00;26;44;22
So there's there's challenges around diagnosis, There's challenges around how do you develop a drug in this new rare disease where clinical trials never been done before? What what are the end points? What kind of benefit do we need to see if it's a genetic or life threatening disease? Does that change our, you know, the the efficacy safety sort of ratio we're willing to accept?
00;26;44;22 - 00;27;10;07
Right. So whole bunch of challenges there in that space. Again, though, I think there's been amazing progress. We've even seen things like the FDA and other regulators be more flexible and encourage innovation. They realize it's hard in this area and, you know, there aren't that many patients and conducting clinical trials and finding those patients and collecting data is extra challenging and we're not going to get that much of it.
00;27;10;07 - 00;27;53;14
So I've seen the FDA be very flexible and responsive and kind of partnering and collaborating with industry to help because we all want to kind of move these therapies forward and help these patients. So lots and lots of progress, but extra challenges. And I think it really creates an environment here where the rare disease space has really been the tip of the spear, both with decentralized clinical trials, with maybe some of these remote data capture paradigms, because again, necessity being the mother of invention, just to just to manage to do this in the rare disease space does require us to think differently and approach things differently and be creative and I think the
00;27;53;14 - 00;28;13;25
success we're seeing in this space, I'm hoping that other parts of our industry see that and also can adopt a little bit of innovation in their own little areas as well. Well, I'm always looking for good stories. Do you have some examples of where patient driven data really changed the trajectory of drug discovery for a specific rare disease?
00;28;13;27 - 00;28;49;06
Well, there's been a lot of good examples of this patient focused approaches that we're talking about, this idea of get outside of that conference room bubble, incorporate the patient voice and perspective into your drug development just to the point of. So if you're developing a, you know, a drug and you have a clinical trial, you're looking at endpoints, you're looking to write to measure the effect of your drug on, say, some kind of performance factor, You know, when you look at how we're going to develop that, the FDA may want a certain endpoint that is validated and it's the gold standard.
00;28;49;06 - 00;29;21;15
And they're looking for industry to kind of measure that and hopefully exceed that in their trial. The drug developers and industry, you know, they're often thinking about what's more what's realistic. Does it take us five years to achieve that endpoint? Is there something that's sub or is there a surrogate, is there a biomarker? And then interesting, when you talk to patients, you know, you hear this a lot of diseases, well, we'll use what's called the six minute walk test, which has been talked about ad nauseum as a measure of a patient's sort of performance.
00;29;21;15 - 00;29;44;20
The how far can you walk in the six minute space? And if you have, you know, any kind of respiratory or cardiac condition or maybe even something neuromuscular going on, it really limits your ability to kind of perform and walk in that that test that's been used as a standard for a time that's very controversial, that, you know, the FDA is required at a Times or industry has wanted to pursue it.
00;29;44;23 - 00;30;06;14
And then when you actually sometimes talk to patients themselves and say, you know, they'll look at the endpoint in a trial as measuring and say, well, that's not really relevant to my life. You know, if I'm able to walk across my kitchen and reach my arms up and get something out of the cupboard, that would be a dramatic, meaningful benefit to me, right?
00;30;06;20 - 00;30;27;22
Just the ability to do that on a day to day basis would change my life. And is there a way to measure something there that's maybe a little bit more relevant for patients, but also balances out what our scientists and our regulators and our industry professionals want, I think is so there's often a dynamic there around what are we going to measure?
00;30;27;22 - 00;30;53;07
There might even you might even argue there's a there's another arm in there that's maybe our our payers, right. Are insurance companies, what are they wanting to see, What's the benefit there? Because this drug will cost something. So it can't just be safe and we think it works. Is it working enough? Is the cost benefit enough? So there creates multiple kind of perspectives on how do we measure the effectiveness and and from what from whose perspective are we measuring it.
00;30;53;07 - 00;31;18;16
So that's pretty interesting. You're seeing more and more, you know, even in FDA new drug review meetings, you're seeing patients come up to podiums and share their experience on the trial, share their experience on the difference this drug made. There's been a lot of, you know, in the muscular dystrophy space, it's a really challenging disease, and drug development has been exceedingly difficult.
00;31;18;16 - 00;31;39;16
So it's been a lot of interesting stories there around not only the six minute walk test, but also just hearing patient voices, hearing the impact a drug has had on a patient or a family or a child. And there's often some competing data here around, well, the seemed to work for patients, but it didn't hit the primary endpoint that we wanted it to.
00;31;39;16 - 00;31;59;15
Yet there's some benefit here and we end up in some kind of gray area. And it's been an interesting kind of discussion and dialog we see playing out in those areas. So yeah, kind of competing priorities in a way. How do we find like what works for everyone? Now I'm going to ask you to put on your Nostradamus hat and predict the future.
00;31;59;23 - 00;32;22;05
Thinking about how things are trending now, what role will patients have in the next ten years of drug discovery? Will it be a story of, Hey, we found better ways to do decentralized trials and involve patients and that? Or does it shift to, hey, most of this stuff is done in silico with AI and that's how we do our research.
00;32;22;07 - 00;32;48;27
Yeah, fascinating. Yeah, I think the patient focus, the emphasis on being patient focused and considering patients, I feel like, you know, ten, 12 years ago was a really novel concept. I think we've made incredible strides in that area to where that's not a foreign idea anymore. You still may have some some people in the industry questioning the value of that, or can patients really inform their disease?
00;32;48;29 - 00;33;10;17
You know, a lot of us think the patients are truly the experts in their space. And there's been a lot, I think, to be there's advance things that informed us a lot by including that patient voice, patient perspective, bringing patients and patient panels to the to have a seat in that New Jersey conference room I referenced. Right. To actually provide their input early.
00;33;10;17 - 00;33;34;19
We're starting to see that more and more. And I think that's having impact and progress on making sure that we're creating things that are feasible for patients. So, you know, my crystal ball here on my desk sees us continuing to do more and more of that. I think there's a nice trend. I think rare disease, again, has been a space where we've kind of led the charge with that out of necessity.
00;33;34;21 - 00;33;56;02
But I think you'll see that extend into most other therapeutic areas. It's logical, right? It's good science. Consider your end user. Consider the people you're trying to help. Make sure what we're building or delivering or or trying to execute works for the people. You know, it's our Apple. Our iPhone works for the people who are actually using it right?
00;33;56;04 - 00;34;21;25
So I think we're going to see more and more of that, the decentralized clinical trial sort of paradigm that popped up as a necessity as a solution during COVID, you know, really has been like the hot sort of term and topic in our industry for the last two years. Again, if you picture if you if you zoom out, you see an industry that is risk averse and has been conducting clinical trials the same way for several decades.
00;34;21;28 - 00;34;45;25
We have a pandemic, we adjust, we adopt some new technologies. You know, from where I sit, I see this pendulum swinging back toward the middle a little bit. I feel like decentralized clinical trials are being looked at, maybe with a little more scrutiny and skepticism. You know, was this something that we just had to do short term? Is there really value in doing things that way?
00;34;45;25 - 00;35;19;25
Is there really are a slide back to your earlier point, Mike, Are we are we making things more complicated at times? Right. When you start to think about a patient focused approach where we collect data remotely, where we have nurses visit a patient's home, where we have things on telehealth, maybe we go into a clinical site as well, kind of introduces a few more different variables, and it makes not only the data more complicated, but if you're a patient, you might suddenly have six, seven, eight touch touchpoints of Who do I contact?
00;35;19;25 - 00;35;40;10
Is that the is it the help desk for the app or is it my nursing group or is it the clinical site or is it the sponsor or the CRO? So we're I think we've made some things a little bit more complicated and I think some of the risk averse folks in our industry are sort of looking at decentralized clinical trials saying, I don't know about this.
00;35;40;10 - 00;35;58;15
I wonder if maybe we're going to this pendulum will swing back and maybe all clinical trials will have maybe a little bit of a DCT component in them, maybe a little bit of remote data capture, maybe a little bit of consent, maybe a little bit of telehealth, and maybe that'll be just kind of the way we do things.
00;35;58;17 - 00;36;15;28
And we won't be looking at a regular clinical trial or a full DC trial. It'll be a little bit maybe about a mixture would be my thought so, But I do think we're going to continue to emphasize patients more and more. I think there's value in that. I think it's important. I think it's the right way to operate and the right thing to do.
00;36;16;01 - 00;36;33;16
Again, I think in any kind of industry, right, you want to be paying attention to your to your customers, right. And thinking about what they need and what's realistic for them. And I think our industry has a long way to go still in that area. So but again, with my crystal ball, I'm encouraged. I'm excited about where we're headed.
00;36;33;19 - 00;36;54;21
Well, getting back to the technology, especially how researchers figure out what tools to use, making decisions like legacy on premises systems versus cloud, what do you see? Are there mostly hybrid strategies out there, or is everything moving to the cloud? What are the pros and cons of each? Well, I'm the strongest technical person when it comes to things like that.
00;36;54;21 - 00;37;15;18
I do tend to focus on how we can collect data with patients, and I do a lot with wearables and some of these mobile platforms. I mean, it feels like, you know, the people I talk to, it feels like the legacy and on premises systems are, you know, are going away. It feels like everyone's in the cloud. Granted, I don't know, Mike, I live in Seattle.
00;37;15;18 - 00;37;37;16
I have Microsoft and Amazon down the street from me, so maybe it's just a little bit of a a bias with where I am geographically, but it feels like the cloud is where everything is going. I'm sure there are some folks listening who know a little bit more about the details than me, but that's my take. Yeah, well, you have been a longtime partner of Oracle, and in fact, you were at the Oracle Health Conference in September.
00;37;37;18 - 00;38;07;16
You're often participating in Oracle Life Sciences webinars. And I guess this goes back to the question of, you know, what is the industry's role in this thing? What has it been like working with Oracle and what role do you see companies like that playing in clinical research and drug discovery? Yeah, well, it's been a great partnership working with Oracle, both working with folks like yourself and your colleagues, but also leveraging a lot of the good technology solutions that Oracle developed.
00;38;07;19 - 00;38;38;17
I think that, you know, not to be a broken record, but again, risk averse drug development industry here. I think that a lot of innovation can occur from organizations like Oracle all pushing forward new technology, new concepts, new approaches. I'm a strong believer that the innovation in the space occurs from, you know, technology companies, service providers, bringing new solutions to biopharma sponsors.
00;38;38;17 - 00;39;05;18
So Oracle's been a group like that that has moved forward with different electronic data capture systems, you know, sort of the regulatory safety database solutions, things like CTMS's, the platforms that are being created are making us more efficient, they're making us more effective When it comes to the trials themselves. They're allowing data to be captured and integrated better from lots of different sources.
00;39;05;21 - 00;39;29;15
We talked about those challenges to that. But I think the direction is is a really good positive one. So Oracle and, you know, organizations like Oracle, I think are the ones really driving that. They're the ones to be to present new bright, shiny objects, new innovative technology and new solutions to pharma, and to say this will help move things along faster for you.
00;39;29;15 - 00;39;52;05
And with the you know, what the pressures around, you know, right now, the pressures around fundraising, the pressures around firms, maybe like prior noticing different sort of compounds in their pipeline, the challenges in the industry right now, I think everyone's looking for better, smarter, faster solutions. And that's where I think some technology and some innovation can come in.
00;39;52;05 - 00;40;15;01
And I think that's where Oracle will continue to make a really, really strong difference. Well, embrace my own shortcomings as a host. I never assume I've properly picked my guests brains. So what are you thinking about most these days? What's the big question or challenge you think we're facing? Or maybe there's just something you think it's important for our brilliant listeners to know.
00;40;15;04 - 00;40;35;25
And oh boy, we've covered some really interesting topics around, you know, data being captured. Is there too much data out there? How do we integrate data from all these all these different sources? I feel like that is a that is a topic that won't be going away anytime soon. Right? That is something that I think we're going to struggle with for a while of.
00;40;35;28 - 00;41;16;22
We want to capture data from all these new sources. How do we manage it, integrate it, validated, keep it secure. And then, of course, when you have this group of data, we're seeing, of course, artificial intelligence and machine learning and all kinds of derivatives of that occurring with really every data set we have. So that's I think the other big piece is how do we how do we as we collect more and more data, what kind of systems do we have built that are going to help us learn from that and inform us and hopefully within the context of clinical trials and drug development, all of the data we're collecting should allow us to design
00;41;16;22 - 00;41;44;25
the next trial better for the next one to be a little more smarter, to be a little more efficient or a little faster applying this. Maybe upstream into some of the drug discovery pre-clinical stages when we're really looking at new drug candidates, what might work? I think being able to leverage that data and be smart and inform ourselves to be able to accelerate drug to drug discovery in drug development.
00;41;44;28 - 00;42;12;15
I'm hoping that that's where we see great progress, because there are patients out there that really can't wait. And their only hope is that new therapy coming from a clinical trial. And right now, our process just takes a long time. So to that point, do you think do you think A.I. is overhyped? Like if I'm someone with a rare disease and I'm hearing about A.I. and I think, Oh, this is it, this is going to get the therapy or the drug treatment I need in the next year.
00;42;12;16 - 00;42;34;01
Yeah, I think I think that you should be realistic, right? I think that, you know, the AML is going to be those are going to be sort of tools and approaches that are going to be a big part of, like you said, probably most industries and our daily life everywhere. I don't know if that's going to be, you know, a magic bullet that is suddenly going to, like, revolutionize drug development overnight and move things along in a year.
00;42;34;09 - 00;42;53;17
I would temper expectations probably a little bit, but I'd be hopeful that this will help us and this will help us move faster and be smarter. But yeah, maybe that's not a maybe that's not a silver bullet that fixes everything. I think that's another tool in our arsenal to kind of move things forward faster. Well, Scott, thanks again for your time today.
00;42;53;19 - 00;43;15;07
If anyone wants to learn more about you or what you've talked about or a rare clinical, what's the best way for them to do that? Yeah, absolutely. It's been my pleasure to be here today. I've really enjoyed it. Really enjoyed the topics in the conversation. You know, my email address, I guess will put an email out. There is a Scott Schliebner – I’ll spell out Schliebner
00;43;15;12 - 00;43;40;19
@ msn.com. You can also find me on LinkedIn. Scott should leave her and be happy to engage, support, help you out there in any way that I can. Great. We appreciate that. If you are interested in how Oracle can accelerate your research and data needs, all you have to do is check out Oracle dot com. And join us again next time for research and action.
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How is academia fostering research that later turns into startup companies? What are new computational powers bringing to in silico drug design? And what is MoveableType methodology and why should pharma be excited about it? We will learn those answers and more in this episode with Lance Westerhoff, President and General Manager of QuantumBio. QuantumBio is a biotech startup operating in the vast field of drug discovery and molecular design. As President and GM, Lance oversees QuantumBio’s day-to-day management including the research, development, and deployment of advanced technology, as well as strategic partnerships and business development. Lance earned his PhD in Chemistry at Penn State University, and he is an entrepreneur, computational biochemist, and published scientist with projects involving the synergistic application of quantum mechanics and molecular mechanics in the life and pharmaceutical sciences. QuantumBio recently earned a Small Business Innovation Research (SBIR) grant from the NIH to run calculations for their MovableType methodology research, which they will be working with Oracle on that research project, and we talk about that and much more in this episode. -------------------------------------------------------- Episode Transcript:
00;00;00;00 - 00;00;26;06
How was academia fostering research that later turns into startup companies? What are new computational powers bringing to in Silico drug design and what is moveable type methods? And why should pharma be excited about it? We'll get those answers and more on research and action in the lead. The leading scene. Hello and welcome to Research and Action, brought to you by Oracle for Research.
00;00;26;06 - 00;01;00;18
I'm Mike Stiles. And today our guest is Lance Wester Hof, who is president and general manager of Quantum Bio. That's a biotech startup that operates in the field of drug discovery and molecular design. Lance oversees day to day management, including the research, development and deployment of advanced technology, as well as strategic partnerships and business development. He earned his Ph.D. in chemistry at Penn State, and he's an entrepreneur, a computational biochemist and published scientist with projects involving the synergistic application of quantum mechanics and molecular mechanics in the life and pharmaceutical sciences.
00;01;00;20 - 00;01;24;09
In fact, Quantum Bio earned a small business innovation research grant from the NIH to run calculations for their movable type methodology. Research. They'll be working with Oracle on that project. So, Lance, we're really glad to have you with us. Certainly. Well, thank you for having me. I look forward to the discussion. Well, listeners, I hope you're ready to get into the weeds because we're going to get into chemistry quantum and all the exciting things that are becoming possible.
00;01;24;12 - 00;01;44;12
And it's all emerging science and technology. So keep listening. You'll be well caught up. But to start, we're always interested in what got you, Lance, and what you're doing. What was that professional and personal journey like? Certainly. Yeah, well, and actually, I when I first started things out or I just started really putting my head around what I wanted to do for a living.
00;01;44;15 - 00;02;06;22
Science was actually pretty far from from the discussion or my thought process I'd actually started is as a semiprofessional professional amateur theater geek, doing a lot of five local theater, that sort of thing. I worked at a local Renaissance fair, you know, those sorts of things that that that people that wanted to go more into the the arts.
00;02;06;22 - 00;02;24;22
If you will, you're really wanted to do. And then one day I was when I was in high school and starting to think about what I wanted to do for a living, it just kind of dawned on me that, you know, you could be the best actor in the world and be very successful as a and have a lot of a lot of great enjoyment.
00;02;24;24 - 00;02;46;20
But if you don't catch a break, you can have all sorts of professional and financial difficulties throughout life. And so I started looking at what classes I did well in in high school or what I was doing well. And at that time I was in 10th grade and of course it was the sciences biology at the time. And at the same time I was I had always been into computers.
00;02;46;23 - 00;03;09;06
And so I think my first computer was a Vic 20, which I believe as I, as I looked up, just came out in 1980. So so that kind of puts it perspective that I was about six years old, and so I knew that I would want to do something with computers, something with biology. So then I started really setting up my my high school career for that, for that sort of background.
00;03;09;06 - 00;03;36;13
I studied some theater on the side. Theater is always fun, but, you know, that was where I focused my energy. Then I went to college. I ended up majoring in biochemistry and computer science with an eye towards doing exactly what I'm doing now. And so my wife always jokes with me that and she knew me then too, that, you know, I wanted to do something that most people, including her at the time, had never heard of before, and that was computational biochemistry or computational chemistry.
00;03;36;18 - 00;03;54;15
And so I spent my years in college, you know, certainly learned a lot in biology. I was I was more focused on the biology versus the chemistry side of things, you know, And of course, like I said, with the comp sci. But then when I went, when I started looking at grad school, I had already met my future advisor at the time.
00;03;54;15 - 00;04;18;14
His name is Kenny Myers began at Penn State at the time and now he's he's moved on as well. But I actually had met him a couple of years before I graduated from college and, you know, started talking to him. And then we ended up I decided that was the lab that I wanted to work in. You know, once I went to Penn State and so as I settled in into graduate school again, that would have been in 1998 when I had started grad school.
00;04;18;16 - 00;04;45;15
By about 2000, 2001, you know, I was really starting to think about and talking to him, of course, at the same time about the possibility of starting a company. And I had already done started some companies back then, back in, I guess you could say the the college years doing, you know, web design for people you know back when the web was very, very young and and just getting started those sorts of jobs.
00;04;45;15 - 00;05;15;02
And so I had already had an understanding of of the basics of of getting a business started. And so at that time, then, you know, Katie and myself and then another person began the companies really to focus on commercializing the linear scaling semi semi empirical quantum mechanics technology from from his lab and spinning that out again as as a company that's really focused on applying these methods to drug discovery working in the pharmaceutical space.
00;05;15;05 - 00;05;42;13
Yeah, I've been calling quantum bio a startup, but it's actually pretty established. It's spun out of Penn State in 2002. How did the company come to be and what does it aim to do? What were your highest aspirations for it? Well, I'll tell you, when you're around that long and you've done, you know, a lot of say, ups and downs, we we we always joke with our investors and everything else on the topic that you're really you know, there's a lot of trial by fire when it comes to entrepreneurship and that is part of the process.
00;05;42;13 - 00;06;07;00
And so you become very comfort, comfortable with trying different things, seeing what works, what doesn't work, and learning from mistakes and moving forward. And so when we first spun out the company, it was very focused on a we have a patent that's associated with it, which was a quantum scoring based methodology that again was published probably about that same time frame.
00;06;07;00 - 00;06;28;09
You know, you know, early 2000s. We thought this was going to be the greatest technology that was going to be known to man or whatever and was going to be very successful in pharma. And I think what we learned was that, you know, trying to just develop a academic software package and commercialize it, it's well, it takes a lot more than just a good idea.
00;06;28;10 - 00;06;50;22
You know, you really need to understand, you know, how software is put together. You need to not necessarily focus on it from an academic perspective, answering academic questions, if you will, and really focus more on your client is what the client really needs to do and how much time and effort they're willing to spend on that. And so that's how we learned.
00;06;50;22 - 00;07;10;11
We had a couple of hard lessons along the way, you know, that, you know, these things had to evolve a little bit more, so on and so forth. And so, you know, we certainly but the good news was at the same time we were bringing on clients and, you know, we've we've had made a lot of friends, you know, a lot of folks that we could work with, collaborators, so on and so forth.
00;07;10;13 - 00;07;41;25
And then over the years as we really put our heads around this and understand how things had to progress, I begun to work with the the National Institutes of Health, and I took over the general management of the company at that time and then really focused on raising funding specifically for development of new technologies. And so we've been able to raise probably on the order of about 8 million or so dollars from the Spire program over the over the last several years.
00;07;41;27 - 00;08;12;12
And again, that is focused very specifically on development of new technologies for pharmaceutical research. And we also then at the same time, we expanded beyond just the scoring methodology that we had done, and now we're in the free energy space, the X-ray crystallography space, the nuclear magnetic resonance space. So we've been able to, you could say, grow that that nugget or completely redevelop that nugget and then now expand to into a different lot of different applications.
00;08;12;20 - 00;08;36;05
And that then becomes our key. Then for from a business perspective is now we're focused very much on applications of these technologies. And in order to solve problems, you know, the more interviews we do on the show, the more I'm seeing startups come out of academia as some kind of deliberate ecosystem that's been set up where colleges are basically incubating research startups that then go on to take off.
00;08;36;05 - 00;09;00;08
What what are the universities get out of that? Well, I mean, I think it obviously depends on on a case by case. You know, there's but but in terms of the generalities, those sorts of deals can take a lot of different looks, I guess you could say. So in our case, you know, most of the focus was that you would be bringing out a technology that was developed in the lab.
00;09;00;10 - 00;09;23;08
Again, as I already mentioned, an academic way to solve a problem is oftentimes different than a industrial way to solve a problem. So there's a lot of that R&D that needs to go into developing a technology. And so that's that's one aspect. Certainly the and so therefore, getting that technology out to more people, you know, tends to be a key benefit for universities.
00;09;23;11 - 00;09;48;14
I think the other, of course, you know, is it comes down to a monetary, you know, very oftentimes thanks to the by double act and so on and so forth, there is a requirement that they take this technology and put it out to the world and actually take some sort of monetary value. And so you get a certain amount of of ownership in that in whatever downstream company comes about.
00;09;48;16 - 00;10;18;25
And so that's how generally universities, you know, develop, they pay for their intellectual property offices and so on and so forth by actually investing in those companies. And usually not necessarily, again, invest in cash as much as investing technology into those companies. And then they get they get a certain percentage of the ownership. And so as we as we move forward, then the the certainly it's oftentimes students, grad students, postdocs, faculty, they get the experience and enjoyment of spinning out of business.
00;10;18;25 - 00;10;41;11
So therefore they get some of that training that goes along with it. But then I think also the university gets some some financial benefit then as well. Well, how do you think that relationship is working? Because entrepreneurs are very unique creatures who put it that way. And a lot of PhDs aren't really entrepreneur material. Or better to say, it's not something that comes naturally to them or that they aspire to be.
00;10;41;13 - 00;11;04;08
That's got to be hard. Throwing themselves into business, especially in something like pharma, which is really regulated and competitive. Right, Right. Well, it actually it's interesting. I would actually argue that actually very oftentimes PhDs, especially in the sciences, I again, I can't really speak for, you know, the humanities, but in the sciences very often they are actually entrepreneurial in terms of their spirit.
00;11;04;08 - 00;11;26;04
Now, again, that might manifest itself in different ways. So a great example of that is a professor at a research university. They generally need to raise their own funding to support their labs. They are extremely it's really important that they go out and do quote unquote marketing in the form of going to conferences and conventions and and writing papers and so on and so forth.
00;11;26;06 - 00;11;50;15
And so that that entrepreneurial spirit, I think, is actually pretty strong. And certainly anybody that's in the sciences and, you know, using the scientific method is, you know, already pretty comfortable with risk and uncertainty because, of course, a lot of what we do stems from hypotheses that some of them don't work out. And so, again, that's something that, you know, a lot of entrepreneurs, you know, would be would understand very well.
00;11;50;17 - 00;12;15;02
And so I think that there is a lot of that spirit. I think the difference then oftentimes is, you know, a lot of folks maybe don't necessarily understand a priori or at the beginning of, well, how do I actually raise funding, raise my own capital in order to develop a new a new company out of that? And so it's those aspects that I think where the university can be a really big benefit.
00;12;15;04 - 00;12;38;27
You know, they they kind of provide that little that little test bed or that little seed bed, if you will. They allow that the people to take risks, that it's a little harder to do if, again, you're out on your own. And so I think that that ends up being where a lot of the benefit comes from. And I think that therefore, then they can really kind of play to those strengths and then grow from there and build out from there.
00;12;39;00 - 00;13;04;29
In terms of the pharmaceutical space, absolutely, very highly regulated. That tends to be a an impediment often. I mean, I think it certainly has benefits, but I think the the, the minus of it is you generally have to have a lot more infrastructure that can support understanding of those regulations, understanding of how those those regulations work, how that game is played, quote unquote.
00;13;05;01 - 00;13;24;28
And so I think that part does tend to be a little more difficult. And again, that is where, you know, a university or even just a corporate partner can take a lot of that push, a lot of that heft in terms of competition. You know, I think that's something that I think we we all like and appreciate. These things should be highly competitive.
00;13;25;00 - 00;13;48;26
But the regulation is something that, you know, like I said, there's always this expense that goes along with it and legal fees and so on and so forth. Computational drug design or in silico has shown promise in enhancing the success rates of drug candidates and saving time and money. Now, of course, it can't replace experimental bench work, but in silico platforms like Quantum Bio, they're starting to be seen even by regulators as having a lot of potential.
00;13;48;28 - 00;14;13;21
I mean, the NIH is even funding you. What is so exciting about in Silico drug discovery and design and and why are folks excited about quantum bio? That's a really you know, I think it goes to a core question or a core core benefit that you're absolutely right. I mean, in Silico back, as I mentioned at the beginning, that back in the day was really not something that people fully understood.
00;14;13;28 - 00;14;39;17
They saw maybe a lot of promise there, but there was a lot of concern, you know, is the are the computational methods just going to replace all all lab bench work? And of course, that's nonsense. Of course, lab bench work is is is critical as well. And at the same time, there's a lot of evolution still going on in the field where we were still trying to fully understand how to.
00;14;39;17 - 00;15;11;12
And I think we're still fully trying to fully understand how proteins and ligands interact with each other, how all these different molecules interact with each other. And by expanding that or as that continue to evolve, if you will, and mature, then it really has now become a core aspect of the of any pretty much any pharmaceutical company out there is likely going to have, you know, a number of computational chemists that are working on projects on a day to day basis.
00;15;11;15 - 00;15;32;16
You know, this is now a critical part, a core part of the drug discovery process where again, back back before it was probably more something that folks kept an eye on. They they wanted to see what sort of ideas would be coming out of it. But oftentimes is that as the saying would go, you know, you're you're only going to give them a certain amount of time to give a result.
00;15;32;16 - 00;15;59;02
And if if not, I'm just going to go ahead and go to the lab and make it anyway. And so methods like the ones that we work with and and develop have now, really, like I said, they've become ubiquitous. You know, they are something that's that's part of the drug discovery or pharmaceutical space. And now then where we focus them is laser on very specific specific solutions to very specific types of problems.
00;15;59;04 - 00;16;19;03
And so and so therefore, we play to our strengths and then we very oftentimes then partner with other software companies that then are applying to theirs. And so in in our world, collaboration between pharma, between other software companies is is just part of the day to day. You know, we need to make sure that our software works well with theirs.
00;16;19;03 - 00;16;43;08
They're doing what they do really, really well, and we're doing what we do really, really well. Then that then provides a solution or a set of solutions that really gets added into a toolbox for the pharmaceutical space. And so a firm before and so a practitioner in the pharmaceutical world will have any number of tools. Ours is one of them that that would be solving the types of problems that they need to solve on a day to day basis.
00;16;43;11 - 00;17;10;10
Pharma, it seems to me, moves really slowly and cautiously, sometimes frustratingly slow toward emerging innovations. And silica has been around a long time, so they got used to that. But now computational power has made it a real for something with enormous potential. So how is pharma acting now? Are they do they get it? Are they fully adopting it to modernize and speed drug discovery?
00;17;10;12 - 00;17;34;01
Yes. Oh yeah. I think clearly that's the case. You know, I think now it's it's really like I said a few minutes ago, I mean, I think it's it's it's a critical part of the R&D process now. I would be surprised if there's any pharmaceutical company doing direct or R&D efforts in the world that that doesn't have, you know, at least some computational chemistry muscle.
00;17;34;08 - 00;18;05;08
Because, again, I think what what a lot of it is we can test we can test hypotheses in the computer that are either difficult to test in at the lab lab bench or that are just expensive or that are, you know, maybe a little, little early in the sense that things that we might we try to what we want to try to build a hypothesis as far as possible before you start throwing a whole bunch of chemicals at it, you know, chemicals and the people and so on and so forth.
00;18;05;08 - 00;18;42;20
Obviously there are costs. And so what you try to do is you want to optimize their time as much as possible, not maybe flush quite as many chemicals down the drain and really focus on solving the cases or addressing the the solutions that you really need to address in order to understand how a molecule is interacting. And so if you think about it this way, a, the drug discovery process takes, you know, billions of dollars and they go through untold hundreds, thousands of potential compounds to finally get to that one compound that's going to be the winner.
00;18;42;22 - 00;19;12;09
Anything that we can do or to to understand and better impact decisions, the better for the whole process it gets. Obviously, the process hopefully gets cheaper, but much more importantly is it gets more, more efficient. We start solving problems quicker so that way we can get that drug to market much, much quicker. Do The pandemic changed the dynamic in terms of how important it is to get to discovery, get drugs to market really, really quickly?
00;19;12;09 - 00;19;47;05
I mean, was that was it any kind of wake up call for speeding discovery? Absolutely. Yeah. I think the pandemic was a you know, it really showed, I think, where computational chemistry can can, you know, really adds to the whole whole process of drug discovery. And so, I mean, Grady, just on the very simplest level, even where as we had as we were doing was shut down in the very early stages of the of the pandemic, you know, people a lot of pharmaceutical companies had to also shut down.
00;19;47;05 - 00;20;10;20
They had to you know, people couldn't come in to the lab. They couldn't work in the lab. So even on the simplest level, computational chemists could continue working. You know, we didn't have to go into the lab. You know, we continued to do the the modeling, the the R&D to really understand what was going on with COVID and understand how the virus is working and getting structure very, very early on.
00;20;10;20 - 00;20;46;22
And so I can remember very early on being a party to online virtual meetings, conferences, meetings with clients and partners and collaborators where we were actively discussing how are we going to solve this problem, How can we as a field add value and solve this problem while, again, everybody else was effectively locked down in their houses and so very quickly there was structure that had come out of this this these these sorts of efforts where we understood what the structure looked like very early on.
00;20;46;24 - 00;21;15;13
And that was just an amazing there's a whole websites and papers and books that are that are dedicated to that topic of just the process of coming up with structure, understanding how this thing was going to work, and then therefore then we could take that and move forward into here are the therapeutics. At that time we didn't necessarily fully recognize that we would get to any sort of vaccine as quickly as we did, and I think that was an amazing accomplishment in itself.
00;21;15;15 - 00;21;34;02
But we were at that time we were still talking about, well, this is the way that this virus works. How can we develop therapeutics in order to address it? And so that that effort, you know, I think was a definite success. And it really showed what computational chemistry can do, especially, like I said, in a very hard situation that we were dealing with as a world.
00;21;34;05 - 00;21;59;28
You're now each research grant is for your movable type methodology research. Now, I don't know what that is, but I know it's patented so I can't steal it yet. So tell me what that methodology is. Certainly. Certainly, Yeah. So this this methodology was actually one of the kind of we were alluding to earlier was it was developed in the lab, in the academic lab originally, and we licensed it from Michigan State University.
00;22;00;03 - 00;22;23;14
At that time. We took it, you know, licensed it, redeveloped it, re-implemented it from the ground up, so on and so forth, actually partnered with the university and to really get their expertise as we were doing it. So I think that was a win and that was certainly a showed a nice core collaboration between a university and an industrial partner and how that can be very successful.
00;22;23;21 - 00;22;44;21
And from there then we've we've now taken that technology and brought that to the world. And now it is something that we're marketing directly to pharma, to biotech, to CEOs, consultants, that sort of thing. Now the question to answer the question of what it is or what it's doing, it's effectively it's it's what's called a free energy simulation method.
00;22;44;23 - 00;23;06;09
The way that that that modeling generally works are simulations. Work is they usually take a lot of CPU time, a lot of GPU time actually, and you model how to molecules interact with each other over time. And when I say over time, it's you're generally modeling nanoseconds or picoseconds worth of time that's in the solution, if you will.
00;23;06;16 - 00;23;40;12
But this is taking weeks or excuse me, I should say weeks anymore, but, but certainly hours. The days in order to get to get to those results, it's something that then you're modeling those interactions and how that that these two molecules or three or four or however many are interacting through time. And what that gives us an understanding of is when it's happening this way and in the quote unquote test tube, in this case a computational test, you or the in silico test tube, it mimics what is likely happening also within the body.
00;23;40;14 - 00;24;19;23
And so by doing that, we can inject the different and I say again, a kind of error code, inject this all obviously computationally or virtually inject a different molecule into this solution and allow that interactions, those interactions to happen. And by modeling those those changes over time, we can see that this interaction with or this particular molecule and again, I'm just talking about the protein ligand space just for this example, but a little molecule with a big molecule, how those two are interacting with each other and if they interact and actually bind together, well then that's, that's a possible drug.
00;24;19;26 - 00;24;35;17
Yeah, we might we might have just found $1,000,000,000 drug alternatively, and this is what usually happens is it falls apart. You know, it didn't, it didn't actually interact. And so that those are the failures, those are the things that then you would tell the bench chemist, I probably don't make that one, make this one, this one looked like it interacted.
00;24;35;17 - 00;24;54;05
Well, that one didn't. But the problem is, as I alluded to, that takes a lot of time that that interaction, all of those interactions takes a lot of time, a computational time. And of course, time is is expense both in terms of the the lab chemist that's maybe waiting for an answer and that person's only going to wait so long.
00;24;54;08 - 00;25;22;01
Also, on the other hand, and it's just the amount of, you know, paying the keep the lights on there, the air conditioning, so on and so forth that goes along with the with the computer. And so what we do then what moveable type does is it says, well, now hold on a minute, Do we need to do all of that modeling or can we start with some key starting points and that maybe maybe they would be what are what we call doc positions or just positions of that ligand within the active site?
00;25;22;03 - 00;25;48;20
Or maybe we actually run shorter simulations and we take snapshots and then we take those points and we say, okay, now we're going to use our method again, what's called movable type to basically smear or blur the interactions between the protein and the ligand In this case. What that does then is that effectively mimics that binding. It mimics all of these local very, very local sampling interactions.
00;25;48;20 - 00;26;22;05
And so what that does for us is we don't have to do the long simulations in order to get an understanding of binding between that that protein and ligand. And therefore our hope would be awe. And what we're seeing is that we can now inject that that that virtual drug in quicker get a quicker understanding of is this good or bad, is this a good molecule or a bad molecule from a binding perspective and then pass that that information down, then to the the medicinal chemistry of the bench chemist to then then go ahead and make the winners versus the losers.
00;26;22;12 - 00;26;55;11
And so the methodology itself is something that then can answer these questions much quicker, that then we can then move a potential drug down that line much, much faster. As I mentioned, Oracle is partnering with Quantum Bio on this NIH research. But in in what way? What does that look like? So that so that's that's I think a core critical aspect that I think is, you know, hopefully, you know, beginning to come out of this this discussion is that a lot of what we do and a lot of what our our field does is a lot of collaboration.
00;26;55;16 - 00;27;24;12
It's a lot of going back and forth between between different entities. No one person or no one organization tends to bring everything to the table and so in our case, what we need is we need the computational muscle. You know, we have the the the algorithms, the software, if you will, of the part of this aspect. But what all of our our methods need is, is some level of modeling or simulation.
00;27;24;15 - 00;27;56;27
And that does take a certain amount of CPU time. Now, we could of course, go and buy a bunch of computers and we of course have some computers that, you know, cluster of our own that we, that we can do some basic testing on. But in this particular project where we're running not just, you know, ten or 20 dynamics calculations in order to get those little snapshots, but we're actually running hundreds of dynamics calculations where now again, each one because now as part of the project, we're comparing to conventional dynamics calculations.
00;27;56;27 - 00;28;23;06
So we still have to run those long simulations to give us a baseline. But then what we do then is we take a take snapshots along the way, with the idea being that hopefully, depending upon the success of this project, we won't need to run all of those long calculations. We could run maybe 20% of the time and still get similar predictive capabilities versus, you know, what the conventional method is.
00;28;23;12 - 00;28;53;00
And so what Oracle is bringing to the table is that ability to run these that computational muscle, that hardware, and that goes along with it, of actually running all of those calculations in parallel. Okay. So now I'm going to put us in our nonexistent time machine and fly forward to the day all of your research is done. If you prove that 90% of the time quantum bio's methodology can get the same or better results with just 25% of the computational time, what does that mean?
00;28;53;07 - 00;29;15;04
What would a Fama exact see? And that that gets them really, really stoked. So that that is, that is savings in terms in a number of different ways. One of course is is the obvious one and that is the just the cost of running computers or cloud computing or again, building their own computers and having to call them and show them and so on and so forth.
00;29;15;11 - 00;29;35;15
So that's the obvious one. That's the obvious best benefit. But there's also an opportunity cost that as I've as I've alluded to, is that if you can't answer a question, if you can't answer a medicinal chemist's question fairly quickly, they will go ahead and make the compound anyway. Of course. I mean, they still have to do their job.
00;29;35;15 - 00;29;56;07
They still have their own hypotheses that they need to test. And so we want to really address both those costs that if a if a calculation is going to take a conventional again, not with movable type, but a conventional calculation may take, you know, again, hours to days, you know, maybe a week or so potentially to get to get an understanding.
00;29;56;09 - 00;30;21;21
That's something that a lot of folks it becomes just problematic to wait for. You know, why not? Why don't we just go ahead and move forward? Why should we wait that long to test hypothesis so we can cut that time down to basically over almost over lunchtime, you know, over a short period of time. Now you're now you've actually given the tool, a tool that then the client can now solve more hypotheses.
00;30;21;27 - 00;30;52;29
They can try more hypotheses, they can they can squirt more virtual chemical into a virtual box and get their answer quicker to then separate the the garbage from from the good stuff during that that downstream process. And so that's that's really where we're coming in is and that's where there's a huge amount of upside benefit to that pharmaceutical company by cutting down that cost, not just the cost but the time that it takes to get to that.
00;30;53;04 - 00;31;15;26
That final answer when researchers are thinking about, okay, what tools am I going to need to use? Am I stuck with a legacy system? Should I use on premises or go with the cloud? Will a hybrid strategy work? What were your answers to those questions? What did you see as the pros and cons of those choices? Well, so I think I mean, I think the answer is probably in this in the short term is all of the above.
00;31;15;28 - 00;31;41;16
You know, I don't think anybody's looking for necessarily a panacea that that this is the one thing that's going to work for everyone. What I do see is that when it comes to having on site clusters, like I said, they do serve a purpose. We we have one of our own as well. That they are a benefit when it comes to that very quick turnaround testing, you know, almost like that workflow testing, making sure that things are working the way that that they're supposed to work.
00;31;41;19 - 00;32;08;28
But when things shift to production, it doesn't matter where that that hardware resides really as long as the the machine is secure and the the partner is secure, which again, Oracle would be, would be, you know, a partner that would provide that security where we can submit those jobs from anywhere as we were talking about back in the with the COVID discussion, people would be literally sitting on the beach and they would be running calculations.
00;32;08;28 - 00;32;29;22
You know, it really doesn't matter to a computational chemist where that hardware is. We have long since done away with the idea of of that. It has to be a local workstation or a local machine and so I think to computational chemists I think it yeah, the cloud definitely makes a lot of sense and, and that's certainly where I think we see a lot of benefit.
00;32;29;25 - 00;32;52;02
The other side of it then too of, of having on the cloud is then generally someone else is taking care of maintaining the system, upgrading the system both on a hardware and a software basis, addressing again, security needs, all of those that infrastructure and that overhead definitely tends to go out the window and we worry about or we we addressed that the partner is taking care of that.
00;32;52;04 - 00;33;11;08
When it comes to the I guess you could say the the management or what what magic management tends to see then is they might see things a little differently where they would they might see it as well. Yes, that's all a benefit. But then they, they still sometimes are in the the belief of risk, you know, of risk management.
00;33;11;08 - 00;33;43;25
Is the cloud more risky than just having it on a local and a local cluster? And that, I think, is probably a good debate. It's debatable. I do. I would say that one benefit of, you know, getting a cloud provider, somebody an organization like Oracle or some of the others that are focused almost exclusively on make it, making sure that they're maintaining a good secure system, you know probably might be better than your, you know, the the local i.t person that you may have hired for you to take care of your own, your own machine.
00;33;43;25 - 00;34;12;03
So, you know, so so my point is that, you know, I think that there's a lot of benefits to, to the cloud. I think that's certainly where things are going. There's, you know, maybe a little bit of concern and again in the in the farmers space about risk. But I think that is really starting to fall away as as more and more of of us vendors, myself included, are shifting a lot of our attention on to the cloud and allowing clients to run things on the cloud.
00;34;12;03 - 00;34;34;04
I think it's it's like anything else, it's it's a feedback loop. A company's success running on the cloud. They're going to continue to run it on the cloud, and especially as they can push through more and more hypotheses that much quicker. So just like computational power took in Silico to a whole other level, now we have this new great leap forward or backwards or sideways, depending on what you think.
00;34;34;04 - 00;34;56;21
With AI, what is under hyped and overhyped about emerging technologies like AI and quantum computing, for that matter? Yes. So, you know, these are these are certainly two very, very hot topics. You know, I think that in some respects, especially when it comes to quantum computing, I think the that one is still, I think a technology of a of a whole lot of promise.
00;34;56;21 - 00;35;16;07
And we're not sure necessarily where it is all going to go. I mean, there are there are obvious benefits of the ideas of, you know, being able to solve multiple hypotheses at once and do things in a Uber parallel level when it comes to quantum computing. So I think that is it is going to happen, but the progression is is on the slower side.
00;35;16;07 - 00;35;48;08
I mean, we were we were talking about quantum computing back in probably discussions we're having is happening in the lab in 2000. You know, so that's something we've certainly been talking about for a long time. The question has always been, you know, where it's going to be. And I think it's a it is a slower moving evolution and we're going to see where things are in the next 510, you know, so so on in terms of artificial intelligence, that's that's here And now, you know, most folks in in certainly in my space is become a tool in the toolbox.
00;35;48;10 - 00;36;09;00
You know, I think everybody sees the strengths of it. Everybody sees the the abilities of it. They see it also see the weaknesses of it. You know, we're still falling for the interpolation versus extrapolation issue that, you know, AI is pretty good at at solving problems. It's already seen it's it's a little harder to use it to solve solve problems it hasn't seen.
00;36;09;02 - 00;36;30;19
But that being said, it is now something that people use to push their their hypotheses through a little bit quicker or get a better understanding of what they should be studying. And that would be the go to kind of saying or belief is A.I. isn't going to necessarily take your job. What it is probably somebody that uses A.I. is going to take your job.
00;36;30;21 - 00;36;56;10
So we've talked a lot about computing power. And you know, as we've seen, our incredible computing power is now in just about everybody's hands. And in research, we're starting to hear more about patient led research or citizen science. So I guess my question is, what place do you think citizen science has in research? Is it is it real or is it mostly just pretending to let non-scientists have a role?
00;36;56;12 - 00;37;19;25
No, I think it I mean, I think it's real. You know, I think they're it's like anything else. There are pluses and minuses. I think there's it's always a plus to, You know, for folks, this is an, if you will, the person on the street, the layman or whatever term you want to use to better understand the scientific method and the process and what we're really doing, what scientists are really doing.
00;37;19;25 - 00;37;51;20
And very often it's kind of like developing a program or software. The best way to learn a programing language is actually to sit down and do it, you know, from a just a day to day experience perspective. I think the more people understand what science is, what it's doing, the process, that's what's behind it, the better, I think where the, you know, some of the really neat things that citizen scientists or citizens bring or the the layman brings, if you will, they bring a different perspective.
00;37;51;21 - 00;38;17;23
You know, and I think that perspective is a benefit. Things that we have to be a little more careful about, I think, is that your folks can be wrong, scientists can be wrong. Anybody can be wrong when we're going through and part of the scientific method is actually an in embracing the potential of being wrong. You're actually saying that, yes, this is something that we could be incorrect on when we're trained for that.
00;38;17;25 - 00;38;33;29
You can find some difficulty, I guess if you're if you're a, you know, someone that really starts getting behind what they believe, sometimes it can be difficult to shake them. That could be a maybe what I'm trying to say is maybe an embrace of your bias. There's a certain amount of bias that that we work into. Anything is the scientists.
00;38;33;29 - 00;38;57;12
I think they they could end up falling into that bias maybe a little bit stronger. But what do you find yourself thinking about most these days? What's an either looming question in your mind or what's something that maybe you wish researchers like our audience knew? Oh, yeah. I mean, I think one certainly right now just with how, you know, I don't want to go into unnecessary politics and that sort of that sort of aspect.
00;38;57;12 - 00;39;19;08
But I think, you know, something I wish that, you know, a lot of people did understand was that, yes, scientists are people like anyone else, but we don't necessarily know all the answers. It's not about knowing all of the answers. What it is is about using a system, using a method in order to figure out those answers, something that I certainly think about a lot.
00;39;19;10 - 00;39;38;00
You know, and it kind of what we were just talking about a few minutes ago is that how to get more people to understand that method and how that method works and really address the types of questions that the big questions that we have as a society. You know, these these this method is the way to do it.
00;39;38;06 - 00;40;02;00
And, you know, I think we certainly have a great track record in solving problems. Do you think that faith in science and particularly in public health officials took a hit during the pandemic? I mean, people put a lot of stock in what they say. And if they are coming out there and confidently getting it wrong, what kind of damage does that?
00;40;02;03 - 00;40;23;06
I think that if if folks who understood what again, the process of science is all about, I don't think that that it would have been nearly as hard. But yes, I would say that there there has been a hit and I don't think that's necessarily all that controversial at this point. You know, and I think that is something that does need to be addressed.
00;40;23;08 - 00;40;46;06
There has to be a recognition that, for one, mistakes were made. I think there's also a recognition that part of that is in better communication. You know, people are smart enough to understand risk. They're smart enough to understand what is and is not risky to them. And so I think that was probably the part that that really was was undermined the most.
00;40;46;13 - 00;41;12;10
A great analogy that we use a lot, actually, when we're talking about predicting molecules and predicting binding is there used to be a time when when a computational chemist was expected to come in and say, this is the right answer and this is the wrong answer, and that is really started to evolve now to actually I would say that that just started it's now has become more looking almost like the weather report analogy to the weather report.
00;41;12;10 - 00;41;35;27
Weather report talks. Yeah. You don't you don't usually watch Al Roker or whoever you're going to watch in the morning and they tell you that it's going to rain. What it's usually is, is some percentage. It's a percent chance. And so I think people do have an understanding of risk or they can understand risk, but the health officials need to appreciate that and they need to be honest with what the risks are.
00;41;36;00 - 00;41;53;12
Maybe focus more on that perspective, allow people then to to make choices that are going to work for them. Well, that's thanks again for being with us today. I'm really glad you chose science over acting, because if you dare, you'd be walking a picket line right now and you'd probably be very hungry. That's right. It might be. That might be the case.
00;41;53;16 - 00;42;13;20
Well, I'm sure we're going to bring you back because we do want updates on that research project you're doing with Oracle. If want to learn more about you or quantum bio, how can they do that? Absolutely. We are certainly we're we're on LinkedIn as as most folks in our field are. So that's always a good place. Certainly if you Google Quantum bio, you'll you'll come across our our website.
00;42;13;23 - 00;44;33;25
Most of all of our updates are there and certainly you're welcome to subscribe to our list through that. Then we get announcements, then that sort of thing of, of what we're doing at the time, from time to time. All right, perfect. If you are interested in how Oracle can simplify and accelerate your research, check out Oracle dot com slash research and make it a point to check out the next research in action.
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What are the 17 United Nations Sustainable Development Goals? What are the biggest challenges in pursuing and achieving those goals? How does technology play a role? And what’s the best way for government, academia, and industry to cooperate and collaborate in support of fundamental research? We will learn those answers and more in this episode with Declan Kirrane, the Chairman of the Science Summit at the United Nations General Assembly, and founder and managing director of ISC Intelligence in Science. Declan has more than 25 years of experience as a global senior advisor to governments and industry on science research, science policy and related regulation. He has been actively promoting a more significant role for science within the context of the United Nations General Assembly since 2010. This has culminated in the annual Science Summit within the context of the UN’s General Assembly. The focus of the Summit is on the role and contribution of science to attain the United Nations Sustainable Development Goals – or SDGs. The current edition – UNGA78 - takes place from September 12-29, and will bring together thought leaders, scientists, technologists, policymakers, philanthropists, journalists, and community leaders to increase health science and citizen collaborations to promote the importance of supporting science. And we are thrilled that Oracle will be part of the Science Summit with a few of our executives speaking and attending, including Alison Derbenwick Miller, global head and VP of Oracle for Research.
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Episode Transcript:
http://traffic.libsyn.com/researchinaction/Research_in_Action_S01_E19.mp3
00;00;00;00 - 00;00;22;29
What are the United Nations Sustainable Development Goals? What are the biggest challenges in pursuing and achieving those goals? And what's the best way for government, academia and industry to cooperate and collaborate in support of basic research? We'll get the answers to all this and more on Research in Action.
00;00;23;02 - 00;00;49;08
Hi, and welcome back to Research and Action, brought to you by Oracle for Research. I'm Mike Stiles and today's distinguished guest is Declan Kirrane, who is the chairman of the Science Summit at the United Nations General Assembly and the founder and managing director of ISC Intelligence and Science. And we're talking to a guy with more than 25 years of experience as a global senior advisor to governments and industry on science research, science policy and regulation around science.
00;00;49;10 - 00;01;17;07
Declan has been promoting a bigger role for science in the context of the U.N. General Assembly since 2010, and that's led to an annual science summit that focuses on the role and contribution of science to reach the United Nations Sustainable Development Goals or SDGs. The current edition UNGA 78 is happening September 12th through 29th and will bring together thought leaders, scientists, technologists, policymakers, philanthropists, journalists and community leaders.
00;01;17;09 - 00;01;37;02
We'll talk about increasing health science and citizen collaborations and why it's important to support science overall. Now, Oracle's actually going to be part of that science summit a few of the executives will be there speaking, including Alison Derbenwick Miller, who's global head and VP of Oracle for Research. Declan, thank you so much for being with us today.
00;01;37;08 - 00;01;58;13
Thanks, Michael. Great to be here. Thank you for the opportunity. Delighted to be here. What we want to hear all about the science summit at the U.N. General Assembly. But before we go there, tell me what got you not just into science, but science policies and your role in creating this summit? Well, first is, I suppose, the simple answer to that is happenstance.
00;01;58;13 - 00;02;21;10
I have to tell you, it was not planned. My primary degree is the history of art. And then I did law and probably needed a job after all of that. And then as a lot of people did in the late, late eighties, emigrated to the U.S. of A and on the basis that there was nothing going on in Ireland.
00;02;21;10 - 00;02;51;23
So opportunity beckoned and therefore from that worked on Wall Street and at a boutique mutual fund company. And then between one thing and another, I ended up in a in a boutique similar boutique company in Paris. And from that to Greece and from that, I got into more consulting side of things and from that started working for global multilateral bodies such as the World Bank and the IMF on a contract basis.
00;02;51;23 - 00;03;23;25
And then from that got more into telecoms and from that into into science coming out. And I suppose from the area of telecoms, infrastructure and data rather than, if you like, a bank scientist. And I suppose my history of art background gave me a wonderful perspective on policy, at least that's what I argue. And, and from that I got very interested and from the insights, but partly because the European Commission invited me and a couple of others to set up a dissemination service.
00;03;23;25 - 00;03;57;19
It's called Cordis. Cordis and the Cordis Information Service was designed by the European Commission to provide information on ongoing collaborative research and to provide information on publicly funded research opportunities in the course. The reason the European Union did that was to was to ensure that the information resulting from funding they're providing reached a very, very wide audience. So my job was to to do that and we built that out and that brought me into the area of science policy.
00;03;57;22 - 00;04;27;19
And I gradually began to understand the huge importance of science policy. And of course, 20 years ago science policy was not a thing, you know, it doesn't really exist in terms of policy making headlines, but it gradually came to be and as you know, it's it's part of the lexicon now. A lot of governments around the world have science policy priorities, and it's recognized as a driver for economic development and global competitiveness and driving solutions to global challenges.
00;04;27;19 - 00;04;51;05
So sciences is a thing, but 20 years ago it wasn't. So it's a relatively recent and I began quickly to appreciate the policy dimension of that, and that led me to work on policy that led me to understand policy mechanisms. And, you know, from my standpoint, I mean, there's no point in looking at some global challenges or many global challenges from a national perspective.
00;04;51;12 - 00;05;21;24
Really, it has to be global, it has to be international. That led me to engage with the United Nations. And from that, we just started to build from, as you say, from 2010, to start to build, engage with nations. And I really want to stress these were designed to be very, very simple to present not to a scientific forum, but to the U.N. for it to the mother ship, to the General Assembly, to diplomats, to policy and political leaders, and show them what science is.
00;05;21;24 - 00;05;43;04
And to give you a practical example, our first meeting was on biobanking. And you know, the main attention, wasn't it? What's biobanking? You see, that's exactly what we want. The want the question we wanted them to ask. And from Matt and that first mission, I think there's about 18 people in the room and we had about four or five diplomats last year at the Science summit.
00;05;43;06 - 00;06;07;02
We had approximately 60,000 participants. We had just under 400 sessions and we had 1600 speakers. So we've come a long way. And that really now is it's it's it's established. But we want to keep promoting. We want to keep science in the eye of the U.N. and we want to ensure that the future recognizes the contribution of science.
00;06;07;05 - 00;06;27;29
That's quite a journey. I think you did just about everything except science. Are you sure you weren't in the circus as well? Yeah, well, it's it's, you know, it's all true, you know, So, yeah, it's it's put a lot of it. Last 20 years has been on primarily on science. Yeah. Well in the intro I mentioned the United Nations Sustainable Development Goals or SDGs.
00;06;27;29 - 00;06;54;00
And our listeners are pretty savvy. They probably know about those, but I'm not savvy. So what are SDGs and how do they speak to global health and humanity in the in the in the mid nineties the the United Nations. And when I say the United Nations, I mean many of the United Nations constituent entities and agencies obviously were very concerned about what we generally call global challenges.
00;06;54;00 - 00;07;18;29
And in the area of health and other forms of well-being, the environment, climate, food security and safety and so on and so forth. And that led to a consensus that there needed to be, quote unquote, you know, how's this for a cliche? We have to do something. So that we have to do something resulted in the Millennium Development Goals, which were, as you can imagine, launched on the year 2000.
00;07;19;02 - 00;07;44;01
And they set forward these goals to to address challenges. And that that 50 years went by pretty quickly. And that then led on to a similar mechanism where you identify a challenge, you define a response to it, and then you allocate specific targets within that and get everyone to sign up to that and off you go now.
00;07;44;03 - 00;08;12;18
So that then that broad approach was repeated for the United Nations SDGs, the Sustainable Development Goals, of which there are 17. And they cover the headlines that you'd imagine between poverty reduction, hunger reduction, improved health, a life below water, life on land, addressing obviously biodiversity, climate and many other areas. And then we're in the middle of these now.
00;08;12;21 - 00;08;45;10
But already the world is turning its attention to the post SDG agenda. And this is where this probably where we are now. The United Nations is organizing the summit of the future September 2024, and that I suppose you could characterize that meeting rather I do as a a banging of heads together because there is a sense of crisis, there is a sense the SDGs are not being achieved, that progress towards the attainment of the SDGs is insufficient.
00;08;45;12 - 00;09;07;19
It is exclusive. It excludes many constituencies, many countries, and again, I won't enumerate them here, but I just present that as as the scenario. So there's now a lot of momentum behind what we know. What do we do next? Why old humble viewers? I don't think it's going to be a if you like, a goals oriented process. I think that's too simplistic.
00;09;07;19 - 00;09;41;01
The world. I think as we found out, is much, much more complex. And I think the issue of inclusion and equity are issues that are present in a way that they were not when the Millennium Development Goals and the Sustainable Development Goals were designed 30 and 50 years ago, respectively. And I think this equity dimension is going to give a far stronger voice to less developed nations.
00;09;41;01 - 00;10;07;05
And just on the back of an envelope calculation, I think if you take the OECD countries and change, you've probably got 30 nations that we could call a developed. And then I suppose the big questions that what about everybody else? And that is becoming a very stark consideration, which was not there. And this needs to be addressed in terms of inclusion and equity to a much, much greater extent than is currently the case.
00;10;07;05 - 00;10;37;01
And arguably then will lead to a more successful approach to whatever succeeds the SDGs, the SDGs. I'm interested in the mechanics behind that because I'm just kind of reading between the lines of what you're saying and it's like for this thing to have true accountability and for these goals to have any teeth at all. There does need to be a someone accountable, be a very good grasp of who the participants are going to be and some form of deadline.
00;10;37;04 - 00;11;01;19
Absolutely correct. Mike And that that was that the plan A the problem with that in in in in a word is it doesn't really work you've so many moving parts you've so many constituencies that it's you know, having this set table of goals and table of targets and allocating milestones know simply doesn't work. Now, why doesn't it work?
00;11;01;21 - 00;11;29;07
I believe in my view it is that many less developed nations don't have the wherewithal to achieve these SDGs. One needs investment, one needs skills, one needs training, one needs cooperation, one is finance. I mean, these are all requirements to make change it, particularly in the area of or particularly in every area. But if you look at health, if you look at energy transformation, if you look at digital transformation, they don't happen without moolah, without money.
00;11;29;14 - 00;11;48;22
So the question is, well, where's I coming from? The answer, I'm afraid, is it's not. And that leaves a lot of they again, when I say lesser developed nations, I mean that is the majority that's 150 nations on the on the on the on a rough calculation. And they're not they don't feel involved. They don't feel they're taken seriously in terms of support for the investment.
00;11;48;24 - 00;12;13;12
And I think they're looking looking at the developed world and they're saying, well, okay, you benefited from carbonized development then and now we're supposed to do on carbonized development and how is that going to work for us? And there's no answer to that. So I think it's extremely complex. And as you say, trying to build consensus around this is extremely difficult because any move forward does require political consensus as very, very hard to get these days.
00;12;13;12 - 00;12;30;16
I mean, you can you can look at Ukraine, you can look at you can look at the Sahel, you can look at many parts of the world where consensus are at a political level. It's very difficult, if not impossible. And then you factor into that, well, how do you then adopt action plans? How do you adopt roadmaps? Again, extremely difficult.
00;12;30;16 - 00;12;54;14
So I in my view, the the SDGs have come a bit unstuck because of the inability of developed nations to provide the necessary wherewithal, including funding. And therefore, of course, the other side of that coin is the inability of of many, many nations to advance those objectives, to achieve the goals that have been set out to reach those targets.
00;12;54;14 - 00;13;32;09
And that simply is not happening. And on SDG eight in the High-Level Policy Forum in July of this year and the the process of reporting on SDH was abandoned for reasons which I think are quite obvious, and no one had anything to report. So I point to that specifically. And also I was with a number of African nation ambassadors for dinner in Brussels two weeks ago, and they pointed out that they've stopped wearing their SDG lapel pins, you see.
00;13;32;11 - 00;13;56;13
And there's two reasons for that. One is in protest at the slow progress towards the SDGs, and secondly, because of, as they see it, their exclusion from the decision making process associated with the SDGs, which, as you can imagine, has a, you know, an annual review mechanism and and and all that sort of stuff. They feel excluded from that.
00;13;56;13 - 00;14;27;04
And my own view is they are for the reasons I've I think I've mentioned or alluded to and this brings this this promotes exclusion and inequity. And again, to repeat this, this wasn't in fashion 50 years ago to the extent that it is today. Now, it is a very, very strong policy and political force. And the institutions, the multilateral institutions that take leadership on these issues now have to find ways to to address that and to build inclusion in a very, very significant and meaningful way.
00;14;27;04 - 00;14;50;08
It's not just the family photo opportunities. It's making sure that these communities, that the stakeholders feel they're involved and they are involved. They're seeing the benefits. And I suppose to that extent, it's it's you know, it's politics as usual. Boy, those those challenges are just huge. It's it's quite an undertaking to to pursue those. But I guess that's what also makes it exciting as well.
00;14;50;10 - 00;15;11;10
Since this show is called Research and Action, we do talk a lot about the need to knock down barriers and support research, but research has several stages from basic all the way through clinical. What is especially important about supporting basic research and getting that right? What are those benefits? I suppose so. Simply put, you know, that's where it all starts.
00;15;11;10 - 00;15;45;05
And when we talk about basic research, we talk about basic research, but I would also call it pre competitive research. So that's a start for, you know, is everybody's friends and everybody is collaborating before they before they apply for a patent or before they discover discover something they can monetize or exploit or innovation in whichever way. And I think a very important aspect of this is the fact that it's by and large government funded, and this gives it a very important dimension, not to mention is seeding the potential for innovation.
00;15;45;07 - 00;16;08;28
And I often reflect that if you if you the government plays a huge role in science and technology. And now I don't have the details in front of me, but, you know, as far as I understand it, about a Tesla Enterprise wouldn't be where it is today without a small business loan from the US government. And of course, Mr. Gates was a beneficiary of government contracts at a very early stage in the development of Microsoft.
00;16;08;28 - 00;16;30;01
So just to point there to the importance of government funding across the board with respect to the government investment in science and technology in the pre competitive space, there's a clear recognition that without a synchrotron or without the government investing in synchrotron or large scale science facilities, then I think we're not going to have stakeholders who can build those.
00;16;30;03 - 00;16;52;12
So it simply simply won't happen. Many, many outcomes I think are evident in terms of the investment and in science and technology. You know, basically we have an advance in knowledge. Basic research seeks to understand the fundamental principles underlying various phenomena. And I think the curiosity driven research around this then leads to much innovation. But of course you don't know that at the beginning.
00;16;52;12 - 00;17;10;28
So I think there has to be a very strong political commitment to Blue skies research. And again, I stress the word political committee because it is a policy decision for a government, any government to invest in pretty competitive research, in science, capacity building, which is predominantly pre competitive and on in there in basic science. So I think that's that's hugely important.
00;17;10;28 - 00;17;34;11
Just to point to the policy dimension, I think that then leads to various innovations and that that that is applying. So you see a very clear narrative between basic research, innovation and applied research. Many groundbreaking innovations and technological advancements have emerged from the discoveries made in basic research. And I think this needs to be spelt out very often when a policymaker gets up in the morning.
00;17;34;18 - 00;17;56;18
That can be a complicated narrative. You know what I want to be getting from this? Why spend vast sums of money on basic research, blah, blah, blah? But I think when you look at the evidence, I think then the case is is compelling. But of course, that needs to be understood continuously, primarily by policymakers. And it does bring long term benefits, The outcomes of basic research might not lead to immediate benefits or applications.
00;17;56;18 - 00;18;25;27
However, these insights often lay the groundwork for future breakthroughs, which could and very often do have significant societal, economic or technological impacts over time. Problem solving is another reason to fund and do basic research educational value. Basic research plays a critical role in educating the next generation or generations, indeed, of scientists, researchers and thinkers. It provides a training ground for students to learn research methodologies, critical thinking and analytical skills.
00;18;26;00 - 00;18;52;06
And these values have multiple applications, multiple applications. And then we have cross-disciplinary insights. I think this is self evident. Basic research often leads to unexpected connections between different fields of study. These interdisciplinary insights can spark collaborations and innovations that otherwise wouldn't come to the fore. Intellectual curiosity, I think, needs also to be highlighted. Then we have the benefits coming from scientific advancement.
00;18;52;10 - 00;19;26;18
So I think Mike, there are many, many, many benefits in that. And I'd just like to point to really one example of basic research. You may not be a follower of radio astronomy or you might be about South Africa won a global competition to build the square kilometer Array telescope, the SKA, and that was a global competition in 2011 against the UK, against Chile, China, Brazil and Canada.
00;19;26;18 - 00;19;50;25
I believe there may be one or two other countries there as South Africa won the right to host and to build the UK and it is now doing that. It's probably a 30 year project. But here you have an example of of an African nation competing to build a hugely complex scientific instrument in the middle of the Karoo desert.
00;19;50;25 - 00;20;30;21
Now why do that? Many reasons to do it. But one of the compelling reasons that I learned from exposure to the project is the enormous commitment that the South African government and now, of course, to have partner countries, including Australia, that huge commitment they have made to education and training the next generation through the scale. And you will see in the system you'll see that many US multinationals, the Dell Corporation, IBM, Microsoft have very strong project association and collaboration with the UK and South Africa.
00;20;30;24 - 00;21;00;04
When the Economist wrote about the UK in 2016, I believe it was, they said this is the world's largest science project. And I think, you know, just it's worth reflecting on that. And this has enormous, enormous future potential. It has existing benefits to the scientific community and of course it is a huge flagship idea that provides a lightning rod for scientific collaboration across Africa and across the world.
00;21;00;11 - 00;21;26;13
At a very practical level, it brings many scientists to visit the facility to work with African and South African collaborators. So this is an ongoing benefit. I think a wonderful example of what our research infrastructure is, what basic science is, and why it should be funded. Yeah, what you just described is an enormous success story. But, you know, candidly, my optimism is challenged because so much of this does rely on government participation.
00;21;26;19 - 00;21;54;08
Yet it feels like as long as money and politics is in the picture, those are the anchors that can weigh things down. And against that backdrop is the science summit. So how did the science summit become a reality and was there any resistance to it or did anybody think this wasn't a good idea or not worth doing? The as far as I've learned, I mean, the response has been universally very, very positive, extremely positive.
00;21;54;11 - 00;22;26;03
And that's because the science summit is designed aimed to advance a greater awareness of the contribution of science to the SDGs. Now, how do you do that? You do that by bringing folk together. And those folk are not just the scientists. I mean, we're not organizing an ecology conference, we're not organizing a radio astronomy conference, we're organizing a science engagement process with U.N. leadership.
00;22;26;06 - 00;22;54;09
And more than that, we are showing how science needs to be inclusive. So to that end, we have a very strong narrative around inclusion. We have a very strong narrative around development, finance for scientific education, for science, performance and investment in science. And through doing that, we are education policymakers. We are engaging with policy makers. And I need to stress this invariably is it is a process.
00;22;54;16 - 00;23;15;28
But at the end of the day, policymakers that I have engaged with at many levels in Africa, Europe and the United States, they want to make the world a better place. I don't think there's any any doubt about that at very often in that quest, they are very remote from the outputs of science for the evidence that is there that shows that science delivers.
00;23;15;28 - 00;23;38;28
Of course, it's in the system. But very often the political system of political decision making is very human. It's a very natural process. It's not always empirical. And I think as you know, and possibly in in the Western world, we see that policy making is becoming more political with a small P. So it's into that environment that we are going and showing how science makes a difference.
00;23;39;05 - 00;24;08;26
Practically. We're showing how science delivers on the SDGs, we're showing how science delivers on the future challenges. And with reference to a very important aspect, we're also highlighting the the importance of enabling access to data now, and this is you'll probably be familiar with the European Union's General Data Protection Regulation, and there are other regulatory regimes in in the United States and Canada, Japan and Brazil and and elsewhere.
00;24;08;28 - 00;24;33;19
And now we are looking at the evolution of regulation concerning artificial intelligence. Now, these regulatory processes as one outcome have impacts on access to data and the use of data for scientific purposes. There is no global regulator, there's no global policymaker. How do we address a global coordination on these issues? And that's something we want to raise within the context of Science Summit to ensure that science is data enabled.
00;24;33;21 - 00;25;00;25
When we talk about science capacity building, essentially we are talking about improving the flow of data, access to data, use of data from machine learning and AI and other purposes, and extending that capability globally. And when that can happen, then you will see dramatically improved outcomes in terms of health research at the environment, biodiversity, energy and many, many other areas.
00;25;00;29 - 00;25;44;06
But we're not there yet. That very much is in the future. So we're trying to align the debate around the objective of creating these new innovations with the need for aligning energy policy, energy technology and other information technology around alignment on regulations. That's huge, huge importance. So we see that. We see the opportunity after the United Nations General Assembly to talk to governments, to talk to political leaders, to talk to Balsillie was to talk to diplomats, to talk to regulators, to talk to bureaucrats and show them what this is, how this matters, and very importantly, how they can include optimized policies to support science in future policies at the bloc level, at nation level.
00;25;44;06 - 00;26;13;20
And we have many, many meetings bringing forward scientists to show what they do, what's necessary in terms of government regulation and support to enable. So we're talking about creating the enabling policy and regular Tory environment for more and better science. And funnily enough, we don't say that's more that's about more money. We don't feel that. We don't think that what there is, is more opportunity and a great need for alignment at government and policy level.
00;26;13;23 - 00;26;39;06
And if every country in the world goes it alone in terms of creating regulation and creating policies, then we're looking at extreme fragmentation. There is much, much untapped potential for governments to work together, and that's one reason we're very happy to be working with Oracle, because, you know, from there, you know, as a company and, you know, forgive me if this is too simplistic, but they, they they create these machines that can communicate data.
00;26;39;06 - 00;27;07;29
And this is a this is a vital and vital a vital need globally. And how they do that and future, I think, will point to many, many future opportunities, which is a very important consideration, because with the science summit and at the level of the U.N., there's there's a huge recognition of the need to work with industry players and the importance of working with industry to deliver innovations, because it's not going to be a university center in it.
00;27;07;29 - 00;27;33;27
With the greatest respect to Cork University in Ireland, they're not going to be making the mess that's going to come through a company. So and industry. So this collaboration opportunity between academia, between governments and industry, I think is ripe for transformation, I think has enormous potential to address global challenges. So can you give us kind of a feel for what kind of speakers and sessions can be expected at the summit?
00;27;34;04 - 00;28;02;24
Yes, Michael, we've got a very inclusive approach to the summit, so we're covering a lot of things, but I suppose I would accept that we have a bias towards health on the health research. On the 13th of September, we have an all day plenary on on One Health, which is a perspective that brings together planet people and animal health into a, if you like, a one world view.
00;28;02;27 - 00;28;26;10
We have a lot of amazing speakers from the five continents who will be coming to that meeting. And what we want to do then is this is relatively rare. It's a relatively new area. By that I mean it's a relatively new or a policymaking. So where want to advance policymaking in this area? We want to also promote interdisciplinary research and show how research matters across these three areas because they cannot be addressed in isolation.
00;28;26;12 - 00;28;56;06
And we'd argue at the moment, by and large, that they are. If you look at national funding systems and national priorities and all the rest of it, they look at animal health or they look at human health or they look at biodiversity. But looking at all three I think is vital. That's our that's our flagship session on Wednesday the 13th on the 14th, Thursday the 14th, we're going to focus on on pandemic preparedness and we're going to bring together the leadership from the National Research Foundation in South Africa, from the African Union Commission, from the European Union.
00;28;56;06 - 00;29;33;16
Delighted to have Irene North steps. The director for the People Directorate in Brussels is coming to join us. For three days. We have Professor Cortes at Lucca from the Medical University of Graz, who leads many European Union research initiatives. But he was the main instigator of the European Union's biobanking research infrastructure, of biobanking, of molecular resources. We should infrastructure, which does pretty much as it says on the can, and we're looking to create a UN version of that, if you like, And look at how this capacity for biobanking is going to contribute.
00;29;33;16 - 00;29;57;01
So and pandemic burden, it's very, very important that we also have President Biden's science adviser, Dr. Francis Collins, former director of the and I and the in the United States, Then we will also have representatives from Dr. Sao Victor. So from the U.S. Academy for Medicine, National Academy for Medicine. He'll be presenting the US approach to pandemic preparedness, which is called 100 days Mission.
00;29;57;06 - 00;30;22;17
What you Need to Do in the first hundred Days. We're very excited about that and very, very much looking forward to using that as a template for a global approach. And while there's been a lot of focus on global strategies, which we obviously very much support, we want to take that global strategy approach to the level of action in terms of what capacity is needed, where's that capacity needed, How can the capacity be delivered?
00;30;22;19 - 00;31;09;02
So very much looking forward to pandemic preparedness as a highlight of the summit. Then on Friday, Friday the 15th of September would have a one day plenary on genomics capacity building with a focus on Africa. But the approach will be global, But bring it forward. Will How does the capacity work for pandemic? Sorry for genomics and has been led by global industry in terms of Illumina and it's been led again by data experts, and that really looks at a future for genomics capacity building in Africa, without which we are going to be or Africa is going to be extremely hampered in the development of medicine and related therapies.
00;31;09;04 - 00;31;37;12
So there are three of the sessions. We also have the Obama Foundation having a meeting on the on the 17th of September. We're going to bring philanthropic organizations together, are for lunch on the 15th. We are going to have a number of sessions around the Amazon with the Brazilian Fapesp, the Rio National Research Agency, and they'll be looking at the future of Amazon from the perspective of collaborative research and development and science.
00;31;37;15 - 00;32;06;00
We will be working with a number of legal experts with the law firm Ropes and Gray, who will bring together experts to identify scenarios for an enabling regulatory environment for genomics that's going to take place on the afternoon of the 16th. We are going to have a number of focus days. The government of of government of Ethiopia will be joining us and they'll be presenting how the Ethiopian government presents or approaches the SDGs.
00;32;06;00 - 00;32;27;18
From the point of view of enabling science. We have a similar approach from the government of Ghana. We will have the nice people from Mongolia, the government of Mongolia. They will be presenting a regional approach from the roof of the world, and we would have the same from Nepal, from India, from Japan, from Brazil and many other nations.
00;32;27;23 - 00;32;58;22
And that national approach is very, very important because again, we want to highlight the need for synergies, highlight the similarity between national approaches and then how they can be brought together and benefit from one another. We will also have a presentation from the editor of Nature, Magdalena Skipper at They'll be presenting a what they call a storytelling evening, and that's that's designed to inform and show how science careers evolve.
00;32;58;28 - 00;33;27;05
So so the community can get an understanding of of how that has worked in a number of individuals so very much at look at looking forward to that. I think that personal aspect is is very, very important. And we will be having a number of sessions with with investors how they are approaching investing in science and technology, how that investment can be better aligned between governments, industry, not for profits, philanthropy.
00;33;27;05 - 00;33;50;18
And we're feeling we're seeing that a lot of these organizations have similar objectives. So there's enormous potential to see how they can be more aligned, work together for common objectives and thereby increase possible benefits and outputs. So very much look forward to dose those discussions. In terms of our principal outputs, what we want to do really is three levels.
00;33;50;18 - 00;34;12;01
First is we want to increase participation and collaboration. So we want to bring people together. And one of the main outputs of the science summit last year, researchers discovered each other. They went away and they started collaborating. That wouldn't have happened if they hadn't met at the science. So that's one level. Second level is what our agenda is.
00;34;12;04 - 00;34;44;27
So the United Nations will convene the summit of the future in 2024. So the question we're asking everybody is what should the science agenda for that meeting look like? And we want to compile it. And with the 400 odd sessions we're running, we want to work with them and see how can they contribute to that, What priorities can they put forward and how do they look in terms of a specific objective which the United Nations can support in terms of energy attainment or the post SDG agenda?
00;34;44;29 - 00;35;22;06
And the third element we want to advance is better policy making, make better policies. We will have tennis knocked and Dennis is the chair of the Inter-Parliamentary Union Science Committee. The Inter-Parliamentary Union is a global organization and represents 138 parliaments around the world. This dialog is hugely, hugely important. So we're going to be working with Denis to see how his members so those legislators in those 140 odd countries can incorporate better global ideas into policymaking at a local level.
00;35;22;06 - 00;35;52;29
And I'm talking about I'm talking about Nepal, I'm talking about Ghana, I'm talking about Kenya, I'm talking about many, many countries. And then what we what we hope that that will achieve is real sustained change. And as we move towards the end of this decade, that's going to be hugely, hugely demanding. But I think if we build this global momentum and we drive this cooperation and instill a sense of cooperation among scientists globally, and also we say that, you know, scientists in fact, are policy policymakers.
00;35;52;29 - 00;36;10;12
I don't see this divide between policymakers and scientists. I think scientists have a huge amount to contribute to policymaking. So, in fact, they're the policymakers. They know a lot about health, They know a lot about what policies are needed to deliver better health. And we want to give them a voice. Well, as I mentioned, Oracle will be speaking and participating at the summit.
00;36;10;12 - 00;36;37;01
And you touched on it a little bit. But when you think about the role for industry players, especially technology giants like Oracle and what's needed to pursue the SDGs, we've talked on the show a good bit about the concept of open science and increasing access to scientific data. It feels like big advances in global health can't happen if those developing or lower middle income countries are kept at arm's length from data.
00;36;37;04 - 00;37;00;02
Absolutely, Mike. Absolutely. Very, very well said. And as I've outlined, is that one of the main impediments potentially to this is regulation by advanced nations, which impacts on less developed nations. So I think an industry has a huge role to play in that because, you know, industry and providing the wherewithal to to advance this data exchange. So we very much look to industry leadership.
00;37;00;02 - 00;37;16;20
And I think Oracle is going to be very instrumental there in showing and leading the way in terms of how data is enabled and how data systems can allow access to data use of data, and of course the use of data for machine learning. And I think that's something we need to learn a lot about, particularly in developing nations.
00;37;16;23 - 00;37;35;25
I also think that the United Nations Global Sustainability Report, the latest version of which is available in draft, and I think the final version will be published at the end of this month. Points to a huge role for for industry. My own view is that I think industry need to be much more at the table at this U.N. table.
00;37;35;25 - 00;37;56;24
I'm delighted to see that Oracle is joining us in this quest, because I think we need to build a narrative and I think it'll be for industry are going to be a very credible partner in terms of telling governments what is necessary, what's needed in terms of creating the space for data to do what data needs. And again, in particular in the countries that are going to be challenged in their quest for access to data.
00;37;56;27 - 00;38;33;03
And that presumes that they have the capacity to have the infrastructure. Many don't, but they're going to need to have that and the industry going to be critical in delivering that. And I think that's that's terribly, terribly clear. So that role for industry in delivering, I think, spans the optimization of policy, the optimization of regulation, the deployment of technology, the maintenance and sustainability of that technology, and of course for the advancement of that technology into different areas in its application, particularly in ICT application, in the areas health and energy and the environment, biodiversity, climate and so forth.
00;38;33;06 - 00;38;55;25
And I think this is something that provides a gives me a lot of optimism in future. And I think also almost we're looking at a, if you like, a post, arguably a post regulatory model where where technology will allow us to define the the remit of Data Act access. I don't think we're there yet, but I think this is this is possibly in future.
00;38;55;27 - 00;39;16;01
And again, Oracle and the colleagues from Oracle will be engaging in a number of discussions on the regulatory side, on the technical side, on the access to data side that's going to help the communities understand not necessarily the solution, but at least define the questions. I think define the questions. Then we have a much greater opportunity in obtaining the answers.
00;39;16;03 - 00;39;39;17
Well, also in my intro, I mentioned that you are founder and managing director of ISC Intelligence and Science. Tell us about that endeavor. What does that do? Well, that that mainly is devoted towards building body types, capacity and advising governments on science. Capacity Building that many faces is based around scientific infrastructures. And of course they come in in many, many flavors.
00;39;39;22 - 00;39;59;29
But ours really is around the design of research infrastructures that that tends to be quite a long, competitive, drawn out, complicated process. Of course, for any funding, there is a there is a competitive process. This takes a a number a number of years, very often for an award, then a subsequent number of years for a design phase to be completed.
00;40;00;05 - 00;40;21;02
Before then you move into construction and operation. Our primary focus is on the design phase and we've done that in in Africa. We do it in India, in in North America, Latin America. And one of our main reasons for focusing on this area is because it means the capacity is there to to allow science to do what it does.
00;40;21;02 - 00;40;46;01
I've mentioned the case of the SKA and in Africa there are many others. But I would say hitherto there's been a lot of differentiation between science capacity. And of course this is this is quite understandable. But I think increasingly in future that capacity will be effectively one big data machine. It won't matter what flavor of science you're doing, you're going to be dipping into a common data reserves.
00;40;46;01 - 00;41;23;05
Now, there's some caveats around that, such as a a synchrotron, for example, or a light source. I think these are, as you can imagine, specific unique instruments. But we're looking forward very much to have the director of the Office of Science in the United States, Dr. Esmond Barrett, talk to us about how this can work on a global level and what are the challenges and how the US experience in building these science infrastructures and capacities can then help many, many other countries to to advance towards not net, not necessary do the same, but at least be on a path to access such capacity.
00;41;23;05 - 00;41;52;08
So ESI has been very, very involved in that and also involved in the regulatory aspects of the impact of updated regulation on science is something we're very exercised about. If we feel that the scientific community historically, by which I mean maybe over the last 15 years have been very slow to understand the implications of regulation of science, but equally the regulatory bodies at national level, equally have been very slow to understand the impacts of science because their primary concerns are not science.
00;41;52;13 - 00;42;23;27
The primary concerns are as they see them is the protection of individual data, etc., etc., etc. and that's very worthy and noble. But then once you pull the thread, you see that that has aspects and implications for scientific endeavor. So we're working in that interface, ensuring or trying to ensure or trying to increase respective awareness and visibility. And now this is has a very sharp focus in the advent of a EIA, the Artificial Intelligence Act in the European Union, which will be defining for reasons we mentioned earlier.
00;42;23;27 - 00;42;43;12
Also, we are very active in that space and we're very particularly active and, and how this seen, how this impacts on less developed nations. Well, Declan, again, we appreciate you being on the show today. If people wanted to learn more about the science Summit or ISC intelligence and science, how can they do that? Main ways. The website for the Science Summit is Science Summit.
00;42;43;15 - 00;45;13;24
It is sciencesummitunga.com the company website is ISC intelligence dot com and then you'll find the usual links to Twitter and all the rest there. Very good. We've got it. And if you listen are are interested in how Oracle can simplify and accelerate your own scientific research. Just take a look at Oracle dot com slash research and see what you think and of course join us again next time for research and action.
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How is computer vision being used to spot autism symptoms much earlier in children? What is augmented cognition? And how can you use AI to make data models work even with small data sets? We will learn those answers and more in this episode with Dr. Sarah Ostadabbas. Dr. Ostadabbas is an associate professor in Electrical and Computer Engineering at Northeastern University, where she is also the director of the Augmented Cognition Laboratory (ACLab), which works at the intersection of computer vision, pattern recognition, and machine learning. Before joining Northeastern, she was a post-doctoral researcher at Georgia Tech and earned her Ph.D. at the University of Texas at Dallas. A renowned expert in the field, her research focuses on the goal of enhancing human information-processing capabilities through the design of adaptive interfaces based on rigorous models using machine learning and computer vision algorithms. With over 100 peer-reviewed publications, Professor Ostadabbas has received recognition and awards from prestigious government agencies such as the National Science Foundation (NSF), the Department of Defense (DoD) as well as several private industries. In 2022, she received an NSF CAREER award to use artificial intelligence for the early detection of autism, which she is working on with Oracle for Research. http://www.oracle.com/research --------------------------------------------------------- Episode Transcript:
00;00;00;00 - 00;00;26;15
How are computer vision and contactless techniques spotting signs of autism much earlier in children? What is augmented cognition and how can you use AI to make data models work, even with small datasets? We'll find all that out and more in this episode of Research in Action. Hello and welcome back to Research in Action, brought to you by Oracle for Research.
00;00;26;15 - 00;00;50;10
I'm Mike Stiles, and today we have with us Dr. Sarah Ostadabbas, an Associate Professor in the Electrical & Computer Engineering Department Northeastern University, where she's also director of the Augmented Cognition Laboratory (ACLab), which works at the intersection of computer vision, pattern recognition and machine learning. Before joining Northeastern, she was a postdoctoral researcher at Georgia Tech and got her Ph.D. at the University of Texas at Dallas.
00;00;50;13 - 00;01;24;04
Her research looks at how we can enhance human information processing capabilities by designing adaptive interfaces based on rigorous models using machine learning and computer vision algorithms. With over 100 peer reviewed publications. Professor Ostadabbas has received recognition and awards from government agencies like the National Science Foundation, the Department of Defense and several private industries. In 2022, she received an NSF career award to use AI for early detection of autism, and she's working on that with Oracle for Research.
00;01;24;04 - 00;01;43;26
Dr. Ostadabbas, thank you so much for being with us today. Thanks for having me. I'm excited to be here and feel free to call me Sarah. Well, listeners, get ready because we're going to get all into computer vision, machine learning, augmented cognition and wherever else I can get nosy about. But first, let's hear about you, Sarah, and your background.
00;01;43;26 - 00;02;12;08
Your passion for technology and physics kind of started back in childhood, right? Yes, that's correct. Actually, physics was my favorite subject in middle school and high school. I was so passionate about it that I even went through the whole volume of Fundamentals of Physics by David Halliday and Robert Resnick in I believe it was in 10th year of my high school, and I was seriously considering to pursue the continuous PhD in physics even before graduating from high school.
00;02;12;10 - 00;02;39;09
And alongside my love for physics, I was always also fascinated by technology, especially computers and programing. I started coding in a language called Basic, which some of your audience may not even heard about that. Why I was in middle school and loved it. Data Analytics capabilities of computer and how computers are giving advanced processing power to human no matter where they are.
00;02;39;11 - 00;03;12;14
I was still living in Iran at the time and experiencing technological advances at that time, such as Internet and cell phone, and they were all very much interesting. And fast forward, all of this led me to pursue a natural combination of my interests, which was an electrical and computer engineering degree with a double majoring in biomedical engineering. And now when I look back, it's actually heartwarming to see one that one seemed to be diverse.
00;03;12;14 - 00;03;41;17
Interesting collection of interests now have shaped my academic journey so far. Was it unusual for someone, you know, at your age, at that early age of middle school, to be coding and thinking about technology and physics and looking that far into the future? I was actually going to date if school, middle school and high school at that time was designed for for math and science.
00;03;41;17 - 00;04;06;00
So no, I had a lot of of my classmates going and exploring different science topics. So it wasn't unusual. I mean, it was unusual when I was taking these heavy books to my gathering at parties, at my family, but not at the school. So I'm glad. And it was 200 of us, 200 girls at and now all of us are all around the world.
00;04;06;06 - 00;04;28;02
Most of us have PhDs. And yeah, it wasn't unusual, but it, it was something that I cherish. Yeah, it's great that you had a school that focused on things like that. So let's kick things off with your NSF CAREER Award focused on developing machine learning algorithms towards the early detection of autism. Tell me if I get this wrong.
00;04;28;02 - 00;04;53;08
But this is about using computer vision to predict autism a lot earlier in children. And what does what does that research involve and what does Oracle for Research have to do with it? You're certainly right. As I mentioned, my academic background revolves around electrical and computer engineering, focusing on data processing. And these data sources can be signals, images and videos.
00;04;53;11 - 00;05;21;06
How might a specific focus a work on computer vision began when I joined Northeastern University as an assistant professor in 2016. As you may know and have heard of over the past decade, deep learning models have been driving advancements in many AI topics, including computer vision. But these algorithms often require a large amount of training data. They are very data hungry.
00;05;21;08 - 00;05;48;24
So my National Science Foundation CAREER Award aims to leverage this advancement in computer vision for a specific health related domain that suffera from limited data. And I'm in particularly focusing on detecting autism in infant even before the first birthday. And this is true processing videos that is collected from them when they are doing daily activities, which is not a lot of things that they do.
00;05;49;01 - 00;06;16;13
They are sleeping, playing or eating. And as I mentioned, my algorithm, they are designed to be data deficient because I'm working on the area that the there are not a lot of data due to this privacy and security reason, but adapting these complex networks, these complex neural networks which are which are building blocks of deep learning necessitates powerful computing resources.
00;06;16;20 - 00;06;44;25
And that's where our collaboration with Oracle become highly valuable, allows me to make this model adapted to this specific application. So you have videos, video cameras, monitoring the kids and kind of like an in the wild get capturing of data. And then the computing power is needed to crunch all that video and that pulls out certain patterns that reveal autism earlier.
00;06;44;25 - 00;07;07;14
Is that how it works? Yeah. I mean, you can say that you put that on the simpler words. Yes, exactly. I'm a simple man. No, no, no. I'm just it's a good I mean, it's a good, good way to describe that. Yes, that's correct. So what we do, we actually leverage these computer vision techniques and contactless video processing algorithm to predict autism, as I mentioned, from daily activities.
00;07;07;19 - 00;07;35;17
And these are daily activities captured by commercial video recording messages. Imagine like a baby monitor or even parent's cell phone cameras. Every parent's love to record videos from the day of their child. So they focus on this specific developmental sign. How will that that relates to motor function, which means that relates to infants posture, muscle tone, body symmetry, and they balance and range of movement.
00;07;35;18 - 00;08;04;05
So these are specific markers that actually has been shown to be early visible warning signs of more developmental disorders such as autism. And they appear actually interestingly, long before the core feature of autism that you may have heard of and these are actually very known, such as social or communication difficulties as well as repetitive behavior. So we are focusing on these early signs.
00;08;04;08 - 00;08;29;11
However, currently the standard approach to monitor this motor function is through visits to child doctor, pediatrician and how is it, unfortunately, over half of these visits are missed. You could imagine often due to the lack of transportation, for parents, it's hard to take time off from work and also lack of child care for other other kids set at home.
00;08;29;13 - 00;09;12;29
So half of these visits are missed and a lot of this early sign has been overlooked. So to address this in equitable access to actually to clinical assessment and a lot of practical constraints, we are trying to to make a home based a I guided in monitoring tools that can track early motor function development very unobtrusively, like just a video that is watching like a baby monitor is rolling and then be the process this video on the back end and track this specific developmental sign and hopefully be we help for the early detection of autism.
00;09;13;02 - 00;09;40;15
I want to also point the fact that it's actually important, very important and crucial to have timely detection in the autism case, because early intervention, it's actually shown that is most effective before the age of four. Yet the average age of autism diagnosis is still around four and a half. So we are hoping to make a clear detection tools better intervention outcome.
00;09;40;18 - 00;10;00;06
It's really interesting to me that body symmetry is a hallmark of development. I guess my question is why would that be and how is Body Cemetery being addressed in your research? That's a very good question. So we are as I mentioned, a motor development is very important. If early signs offer any visible sign of something that may not working out right.
00;10;00;09 - 00;10;32;14
So one interesting aspects of motor function that has been identified as an indicator of neurodevelopmental health is body symmetry. You can imagine that symmetrical movements and posture are crucial for supporting independent movements such as sitting, crawling and walking, especially infant. Then an infant is typically developing movement posture. Actually, you start asymmetric and then gradually they become more symmetrical as our sensorimotor coordination develops.
00;10;32;16 - 00;11;05;06
And during the first year of life, infants could go through the various milestones, such as days rolling over, sitting up, standing so little by little watching, and all of these movement progressed from less symmetric to more symmetric movement and then also study, they have been looking at the infant movement. They have a map showing that the position is symmetry in their movement can be indication of disorders like autism.
00;11;05;09 - 00;11;28;09
However, if we want to have motor functional function assessment in infant, especially body symmetry in larger scale for a long period of time, our for health care provider is going to be very expensive. I mean, somehow impossible and very challenging because imagine if you have 10 hours of videos, how long does it take for you to watch that?
00;11;28;09 - 00;11;54;10
10 hours. I mean, it's going to take 10 hours. But what we want to do, we want to have these computer vision tools apply on these videos to automatically evaluate them all to a function and is start having something in home that people can use and start escorting to one of the mutual developmental indicators, escorting them the symmetry.
00;11;54;12 - 00;12;23;06
So the idea is that we are actually using infant pose estimation algorithms that we have already developed in the lab to assess postural asymmetry based on differences in joint angle between opposing the arms, between the left side and right side. So the effect the the difference is more than 45 degrees, which has been suggested by Esposito in this study in 2009, in the we can call it asymmetric.
00;12;23;12 - 00;12;50;15
We have also come up with our own measure, which is a data learned based assessment on using Bayesian assets to collect aggregation that we could actually come up with two different angles. But how that these are all allows us to do to process the beat you automatically. And then the video is called the whole movement of the infants based based on all of this processing symmetric or asymmetry.
00;12;50;15 - 00;13;12;01
And then physicians can look at that and see that it is something alarming or not. And then as the process of the science and research goes on, well, I've talked to enough researchers to know that recruiting is usually a challenge for any experiment. But with this, the target population is children like babies. How did you manage to get your patient population?
00;13;12;01 - 00;13;39;15
Were there any privacy, access or ethical concerns? It's a very good question and also absolutely an important matter. When recruiting for our experiment, we noticed that the challenge of targeting infants subject under the age of one, parents are already overworked, sleep deprived, and imagine asking them to to be part of yet another task. So it's very hard, however, to be able to overcome this this problem.
00;13;39;18 - 00;14;16;20
We leverage the fact that many parents already are using baby monitoring systems, so they just want to wash them. I mean, a lot of these baby monitors, even the one that they call smart, they don't do anything. It's just a trigger. If the mat the baby's crying or they are moving. So we are aiming to develop this normal system that not only allow the parents to observe the child, but also offers this long term monitoring capability to track the child's developmental process and provides alert if some abnormalities are detected.
00;14;16;26 - 00;14;38;14
So this may be a good incentive for for parents to take part in our study. And as one of the points that you mention about the privacy and ethical concern, we have taken several measures to make sure to address these concerns. We are collaborating with health care professional that they are more familiar with to dealing with the human subject.
00;14;38;17 - 00;15;15;14
And also we are working closely with a Northeastern Institutional Review board known as IAB to make sure our data collection protocol has strict security and privacy standard. We make sure that the parents that they are participating in our study are fully informed about the purpose of the research. And also we get they consent to to use some some part of these data for public use and public release for scientific and technological advancement, because a lot of them these days, how to win is shared in other a study can be built on top of that.
00;15;15;14 - 00;15;37;19
So but we make sure that parents are that the parents that they are part of this study, they are they are aware, fully aware of that. And I want to emphasize that our priority is to preserve the privacy and confidentiality of them, the participant to out the whole process, although they are looking and working on very important and impactful research.
00;15;37;19 - 00;16;05;12
QUESTION But this is also very important at the top of our list. Yes, security and privacy data for data that is important. Is that why a tech concern like Oracle Cloud that obsesses over things like privacy and security kind of speeds up the research? That's very good. Good point that you brought up. That's true. As I mentioned, security and privacy of the data, especially in our field based on the sensitive nature of data that we are collecting, is important.
00;16;05;16 - 00;16;50;21
We are working with them with personal health related information. So we required some sort of robust measure to to protect confidentiality and prevent unauthorized access. And working alongside part industry partners like Oracle ensures that we are actually having a huge safeguard on our sensitive information. The team that I am working with, Oracle has this huge expertise in data management and security practices, and this allows us to then when we are storing, processing and analyzing data in a in a protected environment, we can focus on our research objective while having a partner that gives us confidence in the security and privacy of the data that they are handling.
00;16;50;21 - 00;17;22;04
So it's a very useful and necessary collaboration. So your lab Augmented Cognition Laboratory or the A.C. Lab works with Computer Vision and machine learning. How did that lab come to be and what exactly is augmented cognition? This is actually brings back many fond memories for me, I think. Tell you the story behind the name, Why I was interested in physics, computers, math, and even literature.
00;17;22;04 - 00;17;53;11
I mean, this is specific. Interest by itself can be another podcast session, but not now. I always had a vision of becoming a university professor and leading my own research lab. I remember clearly that I wasn't seen earlier for my Ph.D. when I started to look at look for names for my future lab to reflect the into intersection of engineering inspired artificial intelligence because I was farming, doing school and data analytics.
00;17;53;18 - 00;18;28;25
But also I wanted to emphasize the positive impact of A.I. in human life rather than replacing them. So I came up with the name Augmented Cognition. Augmented Cognition. I actually represent the core idea that I have about enhancing human information processing capability through the design of adaptive interfaces guided by A.I. algorithm, especially machine learning and computer vision. This is specific definition is actually opening of my my web page when I started at my my position at Northeastern University.
00;18;28;28 - 00;18;59;00
This also highlights my focus on utilizing these advanced tools to augment human ability, especially in the data processing domain. Imagine what I'm doing here as part of my NSF CAREER and what I want to to give physician parents the power of processing hours and hours of data and then let them to extract the information that is needed to to make sure to make the informed decisions.
00;18;59;02 - 00;19;23;13
I often have this phrase that at the ACLab we use artificial intelligence or AI to do human intelligence amplification or IEEE. So I do more Iot and A.I.. Your work relies a lot on machine learning and computer vision as tools to generate truly augmented intelligence solutions. How do you leverage the recent advancement of AI in your work?
00;19;23;13 - 00;20;02;06
Because you've probably been watching it for years, but for most of the public, this A.I. thing came on like a tidal wave. So how does that get applied to computer vision? That's true. I mean, I it's the main wave, and I believe in my my opinion that the main a wave and also success is started from with the introduction of deep learning in 2012 2015 and the actually expand the recent advancement in AI to tackle challenges in understanding and predicting human behaviors from vision sources.
00;20;02;06 - 00;20;43;22
As I said, images or videos, I am focused my my work focus on representation learning in visual perception problems such as object detection, tracking and action recognition and using all of these these tools, we want to estimate the physical, physiological or even emotional states of the individual under study. So to be able to do a robust estimation, the algorithms that we are developing at the Sea Lab utilizes this concept called Pose, which is a low dimensional embedding that captures the essential information in the state of the human that we are monitoring.
00;20;43;28 - 00;21;10;14
For example, body pose, facial pose. You could imagine that you could from that to you can get body symmetry, you can get the emotional feeling of the the human. So help me that I want to emphasize the fact that many of these human data focus application that I work on belong to this small data domain. But the data collection and labeling are limited or restricted, such as healthcare application or even military application.
00;21;10;21 - 00;21;42;26
So to address the data limitation, my algorithm also integrate explicit domain knowledge into the learning process through the use of a generative AI model. We actually built our genitive AI model that this model, they are all data efficient machine learning while incorporating valuable insight from domain experts. So this allows us to to use less data. But on the other hand, we have all of these backing from from the experts that allows us to to make our model work.
00;21;43;04 - 00;22;18;24
This means collaborating with professionals from various fields such as physicians, psychologists, even physicians and neuroscientists are very much important and ensures the practical relevance of many of the models that we are developing in the lab. I definitely see use cases for improving health care and data analysis and augmentation. But for the clinical space, are you a let's go for it person when it comes to AI or more of a cautious person and there is a responsible way to apply, I think that your question comes from all of these debates happening.
00;22;18;24 - 00;22;43;25
Is AI for good or for bad? I mean, what we do, to be honest as a researcher working at the intersection of AI and health, I have been trying to keep a balanced perspective on this overall impact of AI. I am an optimistic optimist when it comes to the potential benefit of AI for health care, particularly for the data analysis and intelligence augmentation.
00;22;43;25 - 00;23;05;06
As the name of my lab, we then come back. I believe that A.I. has the potential to change the healthcare and improve diagnosis, personalized treatment, enhancing patient care, and expanding access to care, as I mentioned. I mean, you can actually make an air power system at your home and get the monitoring and the diagnosis that that you need.
00;23;05;08 - 00;23;35;10
And it can help clinician to make more accurate and timely decision leading to better outcomes for patient health. There is not that I'm just only say is the best and now we don't need to to think about other aspects. I also approach the use of AI in the clinical space, especially with caution. We have to be concerned and to address this concern related to privacy, security and ethical use.
00;23;35;12 - 00;24;02;29
We have to be transparent and accountable and ensure that a AI system are fair, unbiased and trustworthy. These are useful for on on human subject. So proper validation and rigorous testing are necessary to make sure these models are reliable and robust. Also, it's very essential to involve health care professionals, patient and other a stakeholder in the development process.
00;24;03;05 - 00;24;29;20
It cannot be inside AI sitting the lab and come up with something as okay, this is perfect. Let's so let's put that in every baby monitor around the world. We have to make sure the system is safe. A specific needs in inside the health care domain. So in one sentence, I believe that with responsible development and implementation, AI has the potential to significantly improve improved health care outcome.
00;24;29;22 - 00;24;59;11
And I'm hoping this balance will that of you, especially in the clinical setting, allows us to to work more to make better and stronger and more robust AI model while addressing the concern and challenges that comes with its use in the clinical space. Well, I know based on what you said, and because I cheated and researched you before you came on the show, that you you believe that AI, as long as it's good, should be able to augment our capabilities.
00;24;59;11 - 00;25;24;04
And again, you're saying not replace human capability, but augment capabilities. So as you mentioned, the average age of detection for autism is about four and a half years olds. How much and you mentioned about one year old, that's how much sooner than that you think the research could detect autism. And if you do detect it that much earlier, then what Can we actually improve developmental growth?
00;25;24;06 - 00;25;54;17
So before I proceed, I want to make it clear that I don't have any formal academic training in the health care domain. Power through my extensive collaboration and engagement, I have come to understanding the significance of the early detection in neurodevelopmental conditions such as autism, and also how timely intervention can improve the developmental outcome. So as you mention and that's right, the current average age of autism detection is around four and a half years.
00;25;54;20 - 00;26;27;02
But through our research, we want to aim to significantly reduces this age and we are hoping to make it on the age of one because we are able to detect this specific neurodevelopmental model signs unobtrusively, automatically and long term using our computer vision algorithm. And let's remember that the fact that the brain exhibits its highest level of neural plasticity during the first year of life.
00;26;27;04 - 00;27;14;09
So intervening during this sensitive window can have profound impact on long term. So the sooner that we can catch some of these not neurodevelopmental disorder, then the rehabilitation can start. And also intervention can be much more accurate. Also detecting a system that can track and quantify infant development aside from autism can can be used to detect and test other hypotheses related to a motor function hypothesis that based on my collaboration with other health care professionals related to this, a liberal policy congenital tool to coalesce list out that all of this stuff that has some motor representations, but they are not catch early.
00;27;14;09 - 00;27;43;09
You know, because infants are at home. Parents are especially new. Babies have a lot of work so they they missed a sign and then the number of visit is very limited if not missed. So by advancing the age of detection and enabling early intervention, I am not only hoping to have the individual outcome, but also the whole idea is studying other and testing other hypotheses in their developmental science.
00;27;43;09 - 00;28;12;17
So hopefully that would be a tool that empower researcher, physician parents in the field to study these motor related developmental condition much earlier and less expensive and much more on up to the CV. Well, research does need data for exploration and reproducibility, but a lack of data sharing in the research community is kind of a hot topic. There are several people that just doesn't want our collective knowledge to collect.
00;28;12;20 - 00;28;48;13
So why is data sharing vital to advancing science and getting to new discoveries and treatments? For sure, I'm not among those group that they don't share. I think I believe the data sharing plays a very important role in advancing scientific research. So essential for reproducibility, transparency and collaboration. So by sharing data research, it can not only validate what you have done, reproduce that, but also they can build upon your finding and start building new and new discoveries.
00;28;48;15 - 00;29;14;03
So rather than everybody start from scratch. So sitting on your data and not sharing that, it's I don't see that is a scientific manner. This is very fundamental. We do, we do actually share the data on both the data and code in our lab, in the computer science and engineering field is is known that people share data. They could, but in the medical domain, this data is very protected.
00;29;14;06 - 00;29;44;06
And it's I understand all of their privacy consent. But in our data collection procedure, we make sure that we inform at the participant about the value of data sharing. So we get they consent to share these data is pieces of the video that they are collecting. And then I am hoping that collectively we can add best knowledge, at least address complex challenges related to data specific types of a question that we are addressing.
00;29;44;06 - 00;30;16;28
And ultimately we want to improve human health and well-being well-being and enhance the quality of life for everybody. Do you think some of that reluctance has to do with concerns about intellectual property and researchers thinking about, you know, the marketability of what they're doing? Absolutely. Absolutely. That's the case. But I have a counter argument for that. So this is not 2000 years ago that we we come up with an idea and write it down and then buried so nobody can find it after after us.
00;30;17;00 - 00;30;40;22
So I think by sharing with the acknowledgment of that there the research and who came up with that is important. But if we keep this strain of sharing thoughts, sharing ideas, sharing data, which data nowadays holds a lot of intelligence insight inside that, then we can actually build and everybody get into the training of the is Discovery new discovery.
00;30;40;29 - 00;31;13;07
So if we want to keep that it's possible and then in industry because now the line between industry and academy is not as the strict as before because there are a lot of collaboration happen which we're very much I admire. But yeah, we have to to make sure to acknowledge both sides, industry and academics, to acknowledge their contribution, but then share the data and see and be happy on the growth, be happy about advancing the knowledge and the complex problem cannot be solved if we just keep it to ourselves.
00;31;13;09 - 00;31;41;09
Well, our audience of researchers is pretty bright. So is there anything else you'd kind of like them to know or for them to think about that we haven't touched on yet? Just something that you wish people paid a little bit more attention to. Oh, thanks for asking. Yes, I think that this in this podcast you talk about my research related to the use of AI in computer vision for for autism.
00;31;41;11 - 00;32;07;08
A study, as I said, that I don't have any any health care background. However, in my my lab doesn't only work on the autism patients, we are actually interested in developing computer vision and machine learning solution for a wide range of application dealing with the small data problem. The data, it's the the bread and butter of us because the intelligence, especially in the era of deep learning, it's all hidden in the data.
00;32;07;10 - 00;32;34;07
So I work on the rehabilitation, animal monitoring, even autonomous driving scenarios that is hard to collect. Data is expensive, is dangerous to collect data or is impossible. Sometimes, for example, it's very hard to to collect data from animal in this specific pose or conditions. So that's one thing that's enabling these advancements, especially advancement in computation and machine learning in this small little domain is important.
00;32;34;09 - 00;33;05;00
So rather than to do not be afraid or shy, if you think that, okay, this specific application needs a lot of detail, we don't have that. So let's not use let's abandon all of these advancement that we have because we don't have a lot of data. No, it's possible. And in our lab we are working on that to enable these advancement in the domain that rather than having millions and millions of sample, you have only 100 samples, you have only 20 samples of that in Central and all that.
00;33;05;02 - 00;33;28;04
So in my lab we are looking at the problem time to size. First we want to see that if we can make our machine work with less amount of data as I mentioned earlier, how we can do that, we should actually make research a space for the parameters of the model, make it more constrained by bringing some outside domain knowledge inside the model.
00;33;28;07 - 00;33;47;08
So rather than be say that, look, I don't want to hear anybody else's idea. I just want to look at the data and see what's happening. We only take them. They are data driven models. We are putting in some understanding of about the physics, about this specific phenomenal behind that, about the specific types of movement that we are looking for into the model.
00;33;47;13 - 00;34;15;21
So to make the model work with a less amount of data. On the other hand, we we were thinking about this in digital expanded this data is called synthetic data generation. So we are looking at a lot of simulators, even game engines, to see that if we can use them and make an avatar of infant, for example, fall from the bit better than looking at videos or waiting for infant fall of the bit, we actually see that picture can be simulated.
00;34;15;21 - 00;34;35;10
These data can be simulated driving in a very low trouble stability environment rather than asking actually a driver to go to do that. So these are also use of their simulators and synthetic data generation. So we expand the data as much as we can in the synthetic domain. And also we make our model to work with less amount of data.
00;34;35;16 - 00;34;55;27
So hopefully in future we are not abandoning this specific application and the use of AI in there because we don't have data. And if our audience does want to learn more about you or your research or the lab, is there any way they can do that or get in touch with you? Yes. My email, I'm actually very fast and responding to email.
00;34;56;00 - 00;35;41;19
You can find my email at my web page. And also you can find me a LinkedIn, send me a message there we we share our news in different platform but yeah the best way contacting me send me an email we do have them also even high schooler at our school right now that I'm talking with you Mike I have three high schooler they are collecting data from an avatar in fact in completely virtual world and they are just we are we want to use that to train our model to detect how intense to reach and grasp.
00;35;41;21 - 00;38;06;24
Gosh, that's great. So, Sarah, thank you so much for being on the show with us today. And to help people find you, I'm just going to spell your last name for them. It's Ostadabbas. So that's the way you can look up Sarah. And if you are interested in how Oracle can simplify and accelerate your research, check out Oracle dot com slash research and join us next time on Research in Action.
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How do the latest technologies impact epidemiology, clinical research, and public health? What kind of progress has there been in collaboration, open data, and citizen science? And in what ways can digital health appropriately supplement healthcare with the human touch? We will get the answers to these questions and more in this episode with Christine Ballard, a professionally trained epidemiologist specializing in clinical research and a Research Advocate at Oracle for Research. Christine has her Master of Public Health and is currently pursuing her Ph.D. in pharmacoepidemiology at UNC Chapel Hill. Her vast experience includes stints as an assistant professor and clinical research roles at Wake Forest Baptist Health, the University of Rochester Medical Center, and the New York State Department of Public Health. You can learn more about Oracle for Research here: http://www.oracle.com/research
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Episode Transcript:
00;00;00;00 - 00;00;24;21
What challenges do epidemiology researchers face in getting solutions to the public? What kind of progress has there been in collaboration, open data and citizen science? And in what ways can digital health appropriately supplement health care with the human touch? We'll get the answers to these questions and more on this episode of Research in Action, brought to you by Oracle for Research.
00;00;24;23 - 00;00;57;18
Hello. Welcome back to another episode of Research in Action, brought to you by Oracle for Research. I'm Mike Stiles, and today we have Christine Ballard with us. Christine is a professionally trained epidemiologist, specialized in clinical research. She has her master of public health and is working on her Ph.D. and pharmacoepidemiology at UNC-Chapel Hill. Her rather vast background includes stints as an assistant professor and clinical research roles at Wake Forest Baptist Health, University of Rochester Medical Center, and the New York State Department of Public Health.
00;00;57;20 - 00;01;26;08
She's currently a research advocate at Oracle for Research. And we're going to learn what those research advocates do and get into a lot more. Thanks for being with us, Christine. Thank you so much, Mike. I can't wait to dive into this. Oh, yeah. I'm looking forward to it as well. And I am going to ping you with questions about clinical research, epidemiology, pharmacoepidemiology as I keep tripping over that word, probably where is what kind of shape health care is in.
00;01;26;09 - 00;01;48;12
We're going to talk about that and some other stuff. But first, what got you as a person interested in this line of work? Kind of give us a little history lesson on Christine. You know, growing up, I lived in rural upstate New York, so I lived right outside of Rochester, right up on Lake Ontario, in a really small town of Albion, New York.
00;01;48;14 - 00;02;17;09
And, you know, there really wasn't a lot there in terms of researchers and health care access, to be quite frank. And, you know, I was diagnosed with type one diabetes at a really young age. I was diagnosed at eight and it I had a couple options When I got diagnosed, I could either face it head on or I could kind of sorrow in getting diagnosed and, you know, kind of letting it take over my life.
00;02;17;09 - 00;03;05;17
And I chose truly to jump two feet in. And I was so interested in being kind of up to date with all of the newest, latest, greatest technology and research updates. And I would find myself as a young kid trying to Google once Google became available, what certain words meant and really kind of educating myself about it. But quickly, growing up in a small town, not having that research access and really not having access to health care providers that even necessarily were familiar with that technology, my parents got me connected with the University of Rochester, and that's where I had a lot of my care growing up.
00;03;05;20 - 00;03;34;21
And really got to to learn and grow as as a kid alongside some of the brightest scientists in the field and it truly inspired where I wanted to go and was so excited when I entered college at the University of Rochester and really getting to work more hands on than you would as an eight year old kid and really just fell in love with the field.
00;03;34;21 - 00;04;06;24
And so I didn't know what epidemiology was even entering college and quickly kind of figured it out. During my studies. You know, like a lot of kids at the University of Rochester, you kind of go in premed, everyone's going to med school. And unfortunately I got rejected many times. And so when I got my MPH, I really fell in love with that and really getting the opportunity to dive into AP research.
00;04;06;24 - 00;04;59;01
And I did a little bit of that at the New York State Department of Health, but really got to spread my wings at the University of Rochester in the Department of Neurosurgery, really exploring health outcomes for patients and really understanding how do we make patients first in research and it kind of set me on this journey. So this past year, I got accepted into UMC Chapel Hill's PHARMACOEPIDEMIOLOGY program, where I get the opportunity to start to understand how pharmacy or pharmacology so all of the treatments that patients are receiving impact their care in certainly looking for ways to continue to always drive patient care and continuing to accelerate new discoveries.
00;04;59;03 - 00;05;23;28
And I absolutely love it and love that. Oracle's giving me the opportunity to do both things, work full time, and also be a full time PhD student. Yeah, I think that's kind of common. I've known several friends from high school who, you know, their path into medicine was a result of something that they experienced themselves, whether it was getting put back together after a car wreck or a disease that they have.
00;05;24;01 - 00;05;50;24
How does your personal health journey with Type one diabetes influence the way you approach research and your job at Oracle now? Because it is kind of a different lens than someone who's just coming at it. Purely academic, purely scientific. Yeah, I think I kind of have to wear both hats to be totally honest, but I think the way that I approach clinical research is really with patients in mind.
00;05;50;29 - 00;06;32;17
Patients have so much knowledge and experience that they can kind of engage in that research process and really understanding how to combine the patient perspective with the traditional research perspective has really been super rewarding and really engaging and allows me to bring my experience as a patient and certainly as a patient advocate forward. And now with Oracle get diving headfirst into the health care space, it really allows me to kind of bring a bit of that perspective to our researchers as well.
00;06;32;19 - 00;07;05;27
And always talking about the new discoveries that they're doing. But how can we relate it back to improving patient care and accelerating discoveries, understanding really how digital health can also revolutionize the way that we've been doing that versus I was that kid that would always bring Excel sheets to doctor's appointments. But I think, you know, I think digital health really is the opportunity to combine new technologies with accelerating the way that we're doing research, which I'm really excited about.
00;07;06;04 - 00;07;30;22
Well, you were talking about how when you were younger, you were making yourself an expert in your condition and probably, you know, seeking answers rather aggressively. Were you happy with the degree to which you were being listened to or did you just keep running up against a brick wall? MM That's a really good question. I have to say I was so lucky as a kid.
00;07;30;26 - 00;08;05;09
My physician was or I should say my nurse practitioner was a type one diabetic herself, which honestly gave me a completely new perspective on life and on the trajectory of the disease. To have somebody who's treating your condition, who is super busy as all of our advanced care practitioners and our MDs are so busy all the time, to see her living a life like that truly impacted where I wanted to go.
00;08;05;13 - 00;08;41;06
Going forward, I will say there were times where I felt like it would not just with my diabetes care, but, you know, with health care in general where you're experiencing something or feeling something and you're like, just listen. And I think that's really where being able to have that patient interaction and research is going to be really critical to understand the unique nuances of health things present in individuals because everybody is different, which I think is really going to help accelerate discovery a lot a lot more as well.
00;08;41;09 - 00;09;11;01
Well, what exactly is a research advocate, especially as it relates to being one for a company like Oracle? Why? Why is that important to advancing research? I think each one of us take on a slightly different role, but really the research advocate is to work alongside researchers to help them navigate huge corporations. And, you know, a lot of us are used to navigating the academic setting because that's what we're familiar with.
00;09;11;01 - 00;09;45;22
That's what we've experienced. But when you throw in a huge company like Oracle, you kind of get a little overwhelmed. And so as a research advocates role, I can I've got the research experience and have navigated the academic setting, but I also have the experience navigating industry through Oracle and so it's really helping the researchers translate what they're doing for their research and how that translate in the academic or nonprofit setting to the industry setting and helping them.
00;09;45;22 - 00;10;14;15
If there is projects that I can help with, we do everything from digital humanities to quantum physics and everything in between. And I am certainly not an expert in everything, but in the health care and the clinical research in the epidemiology space. If there are research areas that I can really work alongside researchers and help them accelerate what they're doing, that's really my role with Oracle for Research.
00;10;14;17 - 00;10;49;10
What attracted me to Oracle for Research was that ability to have that collegiate experience and also provide that researcher to researcher experience as well. A lot of times you get assigned somebody that may not have a research experience or may have heard the word research, but really hadn't lived it with their career. And so I was so excited to be able to kind of bridge that gap, especially coming from academia into Oracle, which was a bit of a learning curve for me.
00;10;49;10 - 00;11;16;23
But to really help, help the researchers get what they want done for their projects and be able to help make really impactful changes to their given fields. But even though you have plenty of laurels to rest on, like you said, you're at the same time getting your PhD and Pharmacoepidemiology at USC. Not an easy thing to do. What is that and what kind of research are you doing?
00;11;16;23 - 00;11;47;04
And and how is that? How does that help us get toward something we can bring the public health as a whole? And so if any of you ask that I or Mike, I feel like I talk to my my parents, they're like, what is it that you do? My dad's just like, I don't know. She's in school. So Pharmacoepidemiology is really the the marrying of pharmacology and pharmaceutical science with epidemiology.
00;11;47;04 - 00;12;31;23
So looking at how patient treatment impacts their overall health outcomes. And so really with that, I've been excited to explore different types of therapy is that are already available on the market to really look at how can we use or repurpose drugs for treating rare diseases and in my focus has been in brain tumors. And so not only with UNC-Chapel Hill and doing all of my PhD work, but I've really been able to dive in with a lab in focus on my own research, looking at how do we improve patient outcomes with brain tumors.
00;12;31;26 - 00;13;09;07
And we do that through a whole host of different tools. Some of it is real world data, and that could be real world data from registries like the Medicare SEER Registry, as an example, where we look at brain tumors or any sort of cancers, and then also be able to take a look at prevalence, meaning the number of cases in total of a certain cancer or looking at incidence, the number of new cases of a certain type of cancer or utilizing other electronic health record data.
00;13;09;08 - 00;13;36;17
So look at continuum of care for health and then also doing firsthand collection of data through clinical trials or clinical research studies that are initiated either by industry or by clinicians. And so really the field of clinical research is is huge. My PhD touches a little bit on that when we take a look at just the treatment side of it.
00;13;36;20 - 00;14;26;05
But my hope ultimately coming out of this Ph.D., I guess what I dream to do is really be able to marry some of my genomic experience using genomic data to also drive precision medicine with our pharmacology, to really be able to start to make an impactful transition for patient care. And my specialty and my focus has really been brain tumors to date, but certainly really interested in the rare disease in oncology space because I think there's a lot of a lot more work that we can do to be able to continue to spread awareness about these different types of cancers, but also a ton of headway to really improve patient care.
00;14;26;07 - 00;14;52;04
Yeah, and you touched on the fact that, you know, the health care overall seems to be driving toward more personalized approaches to treating people. We are all individuals, like you said, Lord knows I like to think I'm special. I don't know. But there are so many environmental and biological variables in the research equation. The kind of research you're talking about sounds incredibly complex to me.
00;14;52;04 - 00;15;20;07
So what epidemiologists have to deal with in terms of procedure and ethics as they do research and try to get something usable out there for the public. That's a loaded question. So with epidemiology, there's a whole host of things to look at. You know, growing up in undergrad and certainly in my graduate studies, the focus has really been on the bio psycho social model, really looking at all effects that could impact a person's health.
00;15;20;07 - 00;16;02;13
So as you touched on environmental, biological, psychological effects, mental health, all of these really contribute to an overall person's wellness. And so epidemiologists have to look across a multitude of different factors to really understand the certain disease that they're studying. I can tell you in the brain tumor space, we've looked at across a multitude of factors, including environmental, including pharmaceutical, including biological, including mental health, to really understand where we can make the biggest impacts.
00;16;02;15 - 00;16;40;14
And then thinking about the ethics associated with research, everything has to be done in certain there's all sorts of procedures that you have to follow. But thinking about our clinical research and our clinical trial data, where we're collecting real world data from patients, it's incredibly important to make sure that the patients are in agreement with sharing their data with the researchers and really understand what the study is looking at and what the benefits or maybe no benefits may be for their particular care.
00;16;40;16 - 00;17;08;02
And so I think, you know, having those procedures in place ensure that the patients are protected, which is truly key. But it certainly is something that I think all of us really strive to hold ourselves accountable for is making sure that patients are front and center as they are truly the ones that are contributing this data. And in allowing us to do the work that we're doing.
00;17;08;05 - 00;17;35;01
Well, I do want to ask about clinical trials because modern medicine means, I assume, collaboration across a range of medical professionals. So how does an epidemiologist work, supplement or partner in clinical trials? What does that interplay usually look like? You know, I've been so fortunate in my career to have supportive physicians and clinicians to work alongside with, but I am not a medical professional.
00;17;35;01 - 00;18;05;19
I don't have my my M.D., I don't have my R.N., I don't have my my degree and physician assistant. So I don't have the firsthand knowledge of treating patients. And so really, epidemiologists are in that supportive role to help drive research. But allowing us to have that interaction with clinicians is key to be able to make sure that the questions we're asking are relevant to patient care.
00;18;05;21 - 00;18;41;05
And what we're finding also is relevant to patient care, because really that's ultimately what we're all trying to do is is improve patient care. So depending on the setting that you're in depends on what your team may look like. But I can say that a lot of times as part of my research teams, we have a physician or some sort of clinician on our team alongside an epidemiologist, a biostatistician who is far better at doing statistical analysis than me.
00;18;41;07 - 00;19;18;06
Sometimes computer scientists who may be helping with the coding, although I do a lot of my own statistical programing myself, but sometimes we'll have the luxury of having a computer scientist on there and then obviously having an IRP that oversees it. An IRP is an institutional review board that makes sure the decisions that we're making in terms of the design of the study and how we're conducting a study is done in an incredibly ethical manner and meets all of the standards that we should.
00;19;18;09 - 00;19;39;22
And so having that oversight is also really helpful to make sure that, again, patients are front and center and we're we're doing the best science we can for regular listeners. I know I keep bringing up Amy Docs or Marcus on the show. She's a Pulitzer Prize winning journalist from the Wall Street Journal and she was a guest. We talked about her book, We, The Scientists.
00;19;39;28 - 00;20;07;16
But it's such a compelling look at patients, scientists, doctor collaboration and how that citizen science is being used in the fight against rare diseases. It's a truly new way of thinking that still honors scientific rigor. What are your thoughts on citizen science and is it gaining traction? I mean, we talked a little bit about it earlier about patients being listened to more, but this kind of kicks it up a notch.
00;20;07;19 - 00;21;01;02
Yeah, her book was fantastic and certainly very insightful of how citizens science should be done in the health care space. In this day and age, all of us have all sorts of devices that are collecting data about all of our lives. I know I'm wearing an Apple Watch and I'm sure many of our listeners are as well. And what I think is interesting is, you know, several years ago, before citizen science in health care really became a thing in the diabetes landscape, folks were using technology to continuously record their glucose readings to be able to get more of a handle on avoiding hypoglycemia, meaning high blood sugar or hypoglycemia, meaning a low blood sugar level
00;21;01;04 - 00;21;45;00
to really help improve their overall care and improve their health outcomes. And so thinking of citizen science, it makes sense to make that leap from what a lot of folks are already doing by tracking their steps or tracking their EKG monitors, tracking their blood glucose level, etc. to be able to incorporate that into that holistic picture of what their daily lives look like from a care standpoint, it certainly helps give physicians a clearer picture of their life, of what they're doing in their day to day life, but also be able to provide more, more personalized care.
00;21;45;03 - 00;22;20;13
But in the research space, it gives you a multitude of data points that otherwise wouldn't have been able to be collected without a huge burden on the patient. And so one of the things I think we have to consider with citizen science is how do we make citizen science approachable for everybody that wants to engage, to engage, and then also be able to allow patients an easy time to find those engagements if they can.
00;22;20;15 - 00;22;48;14
And so when I was at Wake Forest Baptist Health, one of the interesting studies that they did in partnership with Oracle was the Community Research Partnership for COVID 19. And so it really provided patients who, during the heart of the COVID pandemic, maybe at home, working from home to collect data and let us know how they're feeling about everything.
00;22;48;14 - 00;23;12;15
So how are they feeling about the Thanksgiving holiday? How are they feeling about seeing people? When it came time for that Thanksgiving holiday, what were their daily symptoms? Did they receive a vaccine? If they didn't, Why? If they were comfortable sharing that, to be able to understand how do we start delivering care that fits a multitude of different needs?
00;23;12;18 - 00;23;45;18
We were so fortunate with that study to have thousands of patients that were so diligently collecting those pieces of data or sharing those pieces of data with us on a daily basis for over two years. And so seeing that sort of project really starts to open up your mind to what else can we do in the rare disease space in particular, I think that patients are so eager to be able to make advances.
00;23;45;20 - 00;24;19;20
But also if you take a look at traditional data sets that we may use to do analysis for rare diseases, the data is so small that it makes it really difficult to make meaningful discoveries. And so by having patients that are eager to engage, that are advocating on behalf of themselves, or a lot of times others that they're caring for, it provides a whole new perspective that as a researcher I may not have even considered.
00;24;19;23 - 00;24;53;22
And so I think it's really exciting to see how do we start to bridge that gap between patients and scientists. I think we've done a start with that. I think the Robert Wood Johnson Foundation has started to do some of this or other phenomenal grant organizations that have bridged the gap between traditional research grants by having a focus with patient advocates on those particular grants committees or their project committees to really start to bring that in.
00;24;53;22 - 00;25;32;04
And we're starting to see health care bridged the gap as well by creating patient advocacy groups and patient support groups to be able to do that. But I think, again, digital technology is really making that difference and providing apps that can provide that support in a positive manner to patients wide and far. So you may not have your next door neighbor who may be in the same boat, but you can log on to your phone and have somebody who at a couple clicks of a button that may be able to be there to support and really create those those communities for years.
00;25;32;04 - 00;26;02;06
I can say in the diabetes space, we certainly have done that successfully. But being able to bring that to research I think is really making a difference, but also making an option for treatments to truly develop an unapproachable manner for patients. Because if I have to tell you, you've got to do these 35 steps to get to what what would improve your health, you'd probably look at me and go, When do I have time to do all of that?
00;26;02;06 - 00;26;33;06
And so really taking that into consideration and having that first hand patient knowledge is truly going to be key, I think, for continuing to improve our health overall. Well, it is actually technology that's enabling these types of new interactions, especially cloud technologies. You went through a lot of the main benefits of digital health. I know I'm going to floor everybody with this statement, but technology has its drawbacks too, so we can't lose sight of ethics, safety, efficacy.
00;26;33;06 - 00;27;19;01
And I think people still see health care as an in-person human engage. But so in what ways can or does digital supplement that human touch without replacing it? What's the right balance? I think technology has the ability to bridge the gap between inpatient care in not inpatient care, especially in situations where obtaining inpatient care is incredibly difficult. Growing up in a rural, underserved community, my parents would take half a day or full days off of work to take me to Rochester for care, and I was so fortunate that my parents had the ability to do that with their jobs.
00;27;19;04 - 00;27;57;28
But not everybody does. And so really having an opportunity to provide high touch care in a digital setting allows for folks to get access to care that they may not have. It also allows for huge improvements in care. I know in Rochester, for instance, they've got a mobile stroke unit that was having the ability for paramedics to connect with neurologists in the field to be able to reduce the door to needle time with stroke patients, which is critical because time is brain.
00;27;58;01 - 00;28;22;00
And so instead of having to get carted from your house to the emergency room and then do diagnostics to determine if you're having a stroke, that could all be done in the field. And so, yes, there needs to be oversight. Yes, there needs to be some some sort of standards. And yes, there needs to be ethical reviewing of this technology.
00;28;22;00 - 00;28;57;08
But the huge advancements that technology is is truly making for folks is is phenomenal in certainly making health care a bit more approachable. I've always struggled with the whole concept, especially coming from a middle class, underserved health care, almost health care desert in some aspects. It's so nice to be able to make that connection for patients that may have that specialty care offer without having to take hours or days off of work to get it.
00;28;57;13 - 00;29;28;28
And so being able to connect physicians to physicians or patients to physicians outside of their typical catchment area, I think is what's driving improvements in health overall as well. Well, every research, discipline and project is unique, but aren't there some commonalities when it comes to okay, pretty much everybody can use a technology like this. What are some of the biggest technology roadblocks and benefits that you see today's researchers dealing with?
00;29;29;01 - 00;29;58;25
MM I think one of the biggest blocks for research is truly getting access to high powered computing resources that they that they now need because we're collecting data and more and more and more data, it's important to have high powered computing resources to analyze it. I often joke with with researchers when I first started out, I remember getting what we called big data back then.
00;29;58;27 - 00;30;33;17
You know, it was a couple million lines of rows and my poor little laptop that was probably, you know, five years old just could not handle that. But those few million rows now are few billion rows and so it's important to have those high power computing resources to truly be able to analyze the data effectively and efficiently. And that's what I've loved about my role is really being told to give out those resources to help researchers at least break down that barrier.
00;30;33;19 - 00;31;13;05
I think some of the other barriers from a patient perspective is the multitude of different apps that are out there, the multitude of different like telehealth platforms, you name it, you know, we've got it. And how many times have we had to say to somebody, unmute yourself on Zoom as an example, over the last three years? And so I think one of the things that we've kind of got to start putting our heads around is how do we create a fully immersive research platform and what does that look like for patients, I think is I can't even tell you if you told me today, I have to download these five apps and then do this
00;31;13;05 - 00;31;31;08
and that, you're going to lose me. And I'm in the in the field, right? So think about our everyday patients that you're having to say download these five apps and click this and log stuff here. It would be nice if it was all at one click of a button, and I think we're probably not far off from that.
00;31;31;10 - 00;31;58;16
I would say I hope that we're all thinking about that in the same way, but I think that's truly going to make at least getting access as a patient to participating in research a bit more accessible, especially in the technology space. And then for researchers thinking about how can we accelerate the collaboration beyond our typical walls of our institution is also going to be key.
00;31;58;16 - 00;32;21;17
And I think technology getting away from having to share data sets on prem to being able to put things in cloud is really the wave of the future to allow researchers from around the world to collaborate, to really drive change together as well. Well, I know Oracle's been thinking a lot about research data. Like you said, it's a ton of data already.
00;32;21;17 - 00;32;41;27
It's only going to grow exponentially. That's great. We can do a lot with that data, but there is the complexity of it and regulations. So how do you see the data landscape for health care and clinical research? Are we more than we can handle or are we at just right? Hmm. I don't think we're at more than we can handle.
00;32;42;00 - 00;33;29;14
I think what's going to be really key and I think Oracle is certainly becoming a leader in this space is really to connect with the industry standards in working together with researchers to define what those standards should be as we continue to accelerate more and more data growth. I think that with all of our wearables and with all of the multitude of ways that citizens science projects can can continue to grow, we've got a lot of data, but there's also a lot more that we can collect and a lot more that we can continue to grow both both as researchers and as as patients and research participants.
00;33;29;17 - 00;33;58;11
And so I think together with patients and with industry standards and with ethics review boards, everybody can come together as to really define what those standards should look like, both within our own countries as well as internationally, so that we can all start to really make progress together. I can say, I think in the research space and this is one of the things I love the most is, you know, research doesn't really happen in a box.
00;33;58;13 - 00;34;35;19
You certainly can sit in for all room and talk to nobody and you make some small progress. But I think really benefit to research is truly through those collaborations. And so I think as industry continues to dive into this and we get new industry partners like Oracle for the cloud, you know, having them be able to be front and center in helping to learn about what needs to be done in the data space to ensure we're keeping patient data secure is in mind is incredibly important.
00;34;35;19 - 00;35;05;28
And so I, I think we can see that through some of Oracle for research is partnerships with like the Research Data Alliance as an example of really wanting to extend working groups to figure out how do we best treat genomic data, which is something that the industry is just starting to get into. Genomic data is a whole host of tons of data, but truly something that standards haven't been fully developed yet for that.
00;35;05;28 - 00;35;30;23
And Oracle's leading the charge with the research data alliance at trying to define what those standards could and should be. And I think that's going to be where we need to continue to go in the future. So closed data and open data are different things. Thus the two different names, Discovery Research thrives on open data for Explorer and reproducibility.
00;35;30;23 - 00;35;59;28
But for whatever list of reasons, data sharing in the research community is still kind of limited. Why is data sharing important for things like aligning with you? Say the fair principles, all these new NIH policies that are coming out? Yeah, so let me kind of define pain in the health care space or what allows data to be open and what allows data to be closed, because I think that's really important for listeners.
00;36;00;05 - 00;36;46;00
So open data is totally de-identified data. And what I mean by that is in the United States, we've got a principle called Hippo, and there's a, I believe, 20 some odd identifiers that include names, date of birth addresses, dates of service, etc. that can be used to identify patients. And with that, because we want to keep patient identity incredibly secure, because we don't want to share personal data when data is shared in an open space, all sorts of identifiers are stripped from the data so that you cannot track a patient back.
00;36;46;00 - 00;37;13;00
So I can't look at a data set and go, Yeah, that's me, you know. And so that is one data set includes data that is some in-between of that. And that's really defined by an individual institution or organization of what they feel their standard should be. And there's use cases for both for open data and for close data.
00;37;13;02 - 00;37;38;26
Open data is so important for reproducibility because I should be able to take a data set that Mike, you've ran an analysis on and be able to use it to repeat it so that I can say, Yep. Mike, you're your results are right and I'm going to take this algorithm and I'm going to now apply it to a new data set, and it should function the same way.
00;37;38;28 - 00;38;08;02
And that's where I think NIH is really getting at, is to be able to ensure that the research that's being done is done in an open manner so that folks can truly be able to collaborate and grow from what folks have already done. You can continue to accelerate that forward. Closed data is also super important depending on what the researcher is, is trying to determine.
00;38;08;05 - 00;38;35;15
So for instance, if we want to look at a health exposure in a given area, we may need to use closed data to look at a patient's zip code or a patient's census track to really hone in on environmental factors, for instance, in a given vicinity to be able to determine what do we need to do from a public health intervention to reduce that particular exposure.
00;38;35;18 - 00;39;18;08
So really, depending on the institution, will define what may be in that closed data set for that particular research question. We would have to have zip code, but that's something that we probably don't want to share as part of open data. So I think that's where the nuances are going to be. I think we have a lot to figure out in terms of what those standards are for open and closed and how we can come together as researchers and industry to be able to make continue make data open and accessible to people, but also keeping security and patients rights and wants protected as well.
00;39;18;08 - 00;39;41;21
And so I think that's something that Oracle is certainly exploring. And I know a multitude of folks are also exploring. And I think NIH, by putting in these new principles, are truly is truly taking a step in this direction as well. And it'll be interesting to see how we can kind of grow from there over the next couple of years.
00;39;41;24 - 00;40;02;27
Well, I can't let you go without asking about A.I. and the use of these large language models For all the accompanying caution and fear they do show promise you've probably been thinking about, okay, what does this mean for scientific research? What excites you about AI and what makes you a little nervous? Well, I'll start with what makes me nervous.
00;40;02;27 - 00;40;32;20
I think I can do a lot of things and I think we've seen I do a lot of things. And I think one of the the thing that makes me the most nervous about AI is some of the assumptions that can be inherently baked into AI models that are unintentional consequences of a particular model that may have folks come to the wrong conclusion about a certain disease or a certain entity.
00;40;32;22 - 00;41;15;10
But I certainly think AI has a whole of use cases in the health care space that can truly start to add a little new element of precision medicine to given patient care. We've got researchers that are using AI to improve image detection in colonoscopy, in MRI's, to really start to take some of the nuances which radiologists do an incredible job, but to be able to give them another tool to help them as they're reviewing more and more MRI's and all sorts of radiography in a given day.
00;41;15;13 - 00;41;43;16
And so I think AI is going to have a new set of tools for us to be able to do that from the research space. I am excited about AI being able to provide a standardized way of, for instance, analyzing tumor volumes on based on MRI's and looking at time series progression, some tumor volumes to be able to understand how a particular treatment is improving or not.
00;41;43;18 - 00;42;07;27
Particular tumor growth. So I think there's a whole host of of use cases, but I think we all need to be a little cautious and certainly look into the nuances of particular models and algorithms before we we kind of jump to fit in to make sure that we're not inadvertently making assumptions that may not be great for research overall.
00;42;07;29 - 00;42;33;02
Well, Christine, thanks so much for taking the time to be with us. Really good stuff. And what we've talked about is write down our listeners, Ali, But if they want to learn more about what you're doing or get in touch with you, can they do that? Absolutely. So folks can certainly reach out to me on LinkedIn. I’m Christine Pittman Ballard on LinkedIn, and I look forward to connecting with you all as well.
00;42;33;04 - 00;44;44;10
Very good. Well, if you are interested in how Oracle can simplify and accelerate your research, check out Oracle dot com slash research and join us again next time on Research in Action.
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How do you connect the needs of researchers to the capabilities of technology? What are the main stages of research and the challenges faced at each stage? And will AI and machine learning speed up research and get solutions to market faster? We will learn those answers and more in this episode with Dr. Mark Hoffman, the Chief Research Information officer for Children’s Mercy and the Children’s Mercy Research Institute, a position he has held since 2016. Dr. Hoffman earned his doctorate in Bacteriology from the University of Wisconsin-Madison. He later joined Cerner as a software engineer where he advanced to the role of Vice President for Genomics and Research. Dr. Hoffman was also part of the faculty at the University of Missouri Kansas City (UMKC) in the Departments of Biomedical and Health Informatics and Pediatrics. His formal training in research and experience in software development has prepared him to connect the needs of researchers to the capabilities of technology. His work is focused on identifying the best capabilities possible to meet rapidly changing requirements in genomics, public health, and big data. Dr. Hoffman is an inventor of 22 issued patents, a member of the American Academy of Inventors, a TED talk alumnus, and an award-winning healthcare product developer. You can learn more about Dr. Hoffman and Children’s Mercy here: https://www.childrensmercy.org Learn more about Oracle for Researcher here: http://www.oracle.com/research
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Episode Transcript
00;00;00;00 - 00;00;26;02
What are the three main stages of research and the challenges each are facing? How are researchers handling the new federal policies around data sharing? And will AI and machine learning speed research and get solutions to market faster? We'll get those answers and more on this episode of Research in Action. Hello and welcome back to Research in Action, brought to you by Oracle for Research.
00;00;26;02 - 00;00;49;21
I'm Mike Stiles. And today our guest is Dr. Mark Hoffman, who is the Chief Research Information Officer for Children's Mercy and the Children's Mercy Research Institute. That's a position he's held since 2016. Dr. Hoffman earned his doctorate in bacteriology from the University of Wisconsin-Madison and later joined Cerner as a software engineer, where he went on to be Vice President for genomics and research.
00;00;49;24 - 00;01;17;11
Dr. Hoffman was also part of the faculty at the University of Missouri, Kansas City, and the Departments of Biomedical and Health Informatics and Pediatrics. Now, because he's had formal training and research and real-world experience in software development, he's kind of uniquely qualified to talk about what researchers need when it comes to technology. His work focuses on identifying the best capabilities to meet requirements in genomics, public health and big data that are always changing.
00;01;17;14 - 00;01;38;22
He's an inventor of 95 issued patents, a member of the American Academy of Inventors, a TED Talk alumnus, and an award-winning health care product developer. And honest to gosh, that's about the shortest intro I could come up with for someone who is so accomplished. So, we're glad you are with us today, Dr. Hoffman. Well, thanks, Mike. I look forward to talking with you.
00;01;38;24 - 00;02;05;06
Our audience is going to be particularly lucky that they decided to stream this episode because there's a lot to cover. But first of all, what got you into research to begin with? Kind of what led you to each step along the way to where you are now at Children's Mercy? Well, it's a long story, but, you know, I think as a kid, I was always curious and I enjoyed Legos and, you know, taking things apart.
00;02;05;06 - 00;02;36;00
And so, in hindsight, I see all the foundations. And that took me a while to realize that my interests are really split between doing science and building technologies. And so, I see myself as very fortunate to have a role that lets me keep one foot in each of those areas of interest. So, you went when you made the decision to go to Cerner and go into that software development world.
00;02;36;02 - 00;03;05;24
What inspired you to do that? It's interesting. When I was in graduate school studying bacteriology, I was funded by an NIH program that if you're in the life sciences, you were required to take coursework outside the life sciences. I chose to do that in computer science. And then the other requirement was you were required to do an industry internship one summer.
00;03;05;26 - 00;03;31;27
Most of my peers chose to do that in pharma. I chose instead to do my internship at a software development company that does bioinformatics software development. Realized how much I liked that type of work and building things that get used in the real world. It's funny, but to this day, some of the features that I developed are still part of their application suite.
00;03;31;27 - 00;04;04;27
So, I learned from that that I enjoy the software and technology and development process. When there was the opportunity to join Cerner as a software engineer. I jumped at it and happened to be in their microbiology product line, so I was able to talk with the clients about what they were struggling with in the lab, understand that, and then translate that into whatever changes were needed in the software.
00;04;05;00 - 00;04;26;28
Did you expect that to be the case that you would be able to keep a foot in both sides on both the technology and the research side? Or was that something like you never thought that could happen? I didn't plan it this way, but I feel very fortunate that I'm able to exercise so many of my different interests.
00;04;27;00 - 00;05;12;19
So obviously children's mercy benefits from your professional expertise, but behind that you've got a real personal commitment and passion for the work that you're doing that kind of increases your value even more. If you're willing, tell us about that personal connection. And just in general, both Cerner and Children's Mercy are based in Kansas City. And as a parent, while I was working at Cerner, over time, both of our children have needed inpatient care at Children's Mercy Hospital and just the compassion and caring and quality of care and the creativity that we often saw with some of our children's physicians.
00;05;12;22 - 00;05;55;21
The willingness to keep trying things until they could help our kids work through their different health concerns has made a huge impression on me. Now, when I walk through the hospital and see parents with their kids who are going through really some of the most difficult situations you can imagine, I try to take a moment and share a smile or, you know, hold the elevator for a parent. I'm just trying to even though I'm not involved in patient care, I just really am empathetic to those families and see that as really kind of my connection to purpose.
00;05;55;24 - 00;06;35;13
What are the unique differences between a children's centered health care provider like that and, say, a regular adult hospital? What are the biggest differences that the staff has to operate with? I think probably the key difference is with adult medicine, you're really working primarily with the patient and they're making their own decisions. In pediatrics, you're working with children and they're their care providers so that there's more voices involved, you know, with younger children.
00;06;35;14 - 00;07;08;04
It's really is the care providers who are making those decisions with teenagers and adolescents, they certainly will have their own voice into the decision making. So that's really a key difference in pediatrics. I think pediatric medicine is interesting because it's both very cautious but also very willing to innovate. And I find that often to be a really interesting dynamic.
00;07;08;06 - 00;07;33;07
So you were a fan, as it were, of Children's Mercy before you started working there? Absolutely. That was a big part of my decision-making process to come here. So how did that come about that you started working for Children's Mercy? And what exactly do you do there? So, I made the difficult decision to move forward in my career in 2013.
00;07;33;09 - 00;07;58;04
The step that I took was to join the University of Missouri, Kansas City School of Medicine, join the faculty there and form what we called the Center of Health Insights. Through those negotiations, Children's Mercy funded 25% of my role at the university. And so, I already had not quite one foot, but at least a few toes in the door.
00;07;58;06 - 00;08;26;19
And I spent a lot of time building relationships with Children's Mercy. About three years into that, there was some hiring of senior leadership for the Research Institute, and I was involved in that and made the case that I'm seeing other organizations create the Chief Research Information Officer role. That idea stuck and I was hired as our first chief Research Information Officer.
00;08;26;21 - 00;08;50;09
So it sounds like what you want, what you're kind of your North star is to make sure researchers at Children's Mercy can tap into the best technical resources and experts out there, because especially medical researchers, everyone expects them to find answers quickly. You know, there are waiting to be helped. So. What's a typical day like for a chief research information officer?
00;08;50;12 - 00;09;27;09
I tell everybody there really is no typical day. Sometimes I'm down in the weeds talking through technical issues and then in the next meeting can be talking with organizational ownership about high level strategy. Part of what I enjoy is the variety in my role. I don't support any single clinical area of research. So, one meeting just yesterday was with our neurology department, where we're doing research into telemedicine and that can support rural communities where children have epilepsy.
00;09;27;11 - 00;09;55;25
And so there was that meeting and then there was another meeting within the same 24 hours about long read genomic sequencing with our genome center. So just context shifting and you know, always with the theme though, of trying to find ways for technology to be an enabler. All too often my peers in research feel that technology sometimes creates a barrier.
00;09;55;25 - 00;10;25;08
And so, one of my goals is just to try to reduce the barriers and increase the opportunities. And for you, it seems like, you know, you actually see the faces of the people that this research is trying to help. Does that add yet another motivational personal element behind kind of your mission there? Absolutely. I think through the pandemic, the entire work model for people in technology in particular has changed.
00;10;25;10 - 00;10;55;26
I know many of us spent a long time working from home and when I was able to start coming back on site, I just find it very motivating to go to the hospital cafeteria or, you know, get out of my research and technology bubble and be among the patients and families. Well, you've met researchers of every kind all over the world, people just like those who listen to this podcast and you know how they define success and also know what challenges they face.
00;10;55;28 - 00;11;25;06
I'll get to what those are in a second, but let's kind of define research. The stages are basic, translational and clinical. What exactly are those stages and how do you maneuver through those to get to actual innovation? I look at those where I see basic research as working with either molecules, cells or even animal models to understand the biological process.
00;11;25;09 - 00;11;57;14
And then the first level of translational research is taking a subset of those basic findings and exploring whether they may have a role to play in clinical practice. So sometimes that can also be where things start to be defined in an animal model. And then you start when something looks promising, you start working through early-stage clinical trials for safety, and then you start working with patient populations.
00;11;57;17 - 00;12;32;08
And then ultimately, if something's successful and does seem to benefit patients, then it gets rolled into practice and then there's an additional layer that we call outcomes research, where periodically it's important to review whether, you know, those new interventions or new tests really are making a positive difference in patient outcomes. That's kind of how I like to conceptualize the different phases of both basic and translational research.
00;12;32;10 - 00;13;06;17
Well, I'm assuming the challenges and opportunities are different depending on what kind of research we're talking about. So, let's start with your world of clinical research. What makes life unnecessarily harder for clinical researchers and does technology offer any help? I think no matter who I spoke with, recruitment into clinical trials is a continuing challenge. And I do think that data and technology have a helpful role to play in that.
00;13;06;20 - 00;13;37;07
Some of our work, as well as some work within Oracle or Oracle Health, is focused on using large de-identified data sets to evaluate the feasibility of doing research at a particular setting. Do they have enough patients who might meet the inclusion criteria? And so, I do think that data and technology have a role to play in the recruitment challenge.
00;13;37;10 - 00;14;05;23
That's kind of interesting that that recruiting for some of these trials is so difficult. What's the reluctance? You know, people have these conditions, it seems like they would be more than willing to try, you know, something? Why the reluctance? I think there's a number of factors. One is sometimes the designers of a study are maybe overly optimistic about the population.
00;14;05;26 - 00;14;36;01
Sometimes they underestimate the concerns that patients and their families may have. So that's one factor. I think as a scientific community, we need to continue working on how we communicate with the public, especially now, you know, with what I think of as the epidemic of mis- and dis-information. Those may not be preventing people from joining studies, but certainly they impact the willingness to utilize the benefits of research.
00;14;36;04 - 00;15;19;10
Yeah. Do you worry about the level of trust declining in health care researchers? I mean, the pandemic probably we took a hit with that. It's you know, that's a really interesting topic because on the one hand, I often reflect on the pandemic and if it had been ten years ago how different and much worse it would have been, because it really would have been unheard of to have in lab diagnostic tests within weeks, at home, testing within months, and a functional and safe vaccine within a year.
00;15;19;12 - 00;16;16;09
Ten years ago, that would not have been possible. And that's exclusively because of our capacity and in doing clinical research. I think, though, there's a lot of challenging dynamics in play that as a scientific community, we just need to keep getting out into the public, explaining in accessible terms what research is about and why it matters. One thing that we're very intentional about here at Children's Mercy is we have both parent and youth advisory boards, and so we work with them closely as we develop new research initiatives so that they're at the table and they're also out in the community, in the community, sharing the work that's happening here, because that's in so many ways
00;16;16;09 - 00;16;44;18
far more effective to hear from your neighbors, your friends at work than it is to hear from, you know, those of us who are doing the technical work. Well, kind of same question for those at the basic or fundamental research level, what are their biggest headaches? And, you know, is technology being applied to those headaches? Yeah, I think I wouldn't necessarily call them so much headaches.
00;16;44;18 - 00;17;21;07
But, you know, all categories of research, of course, feel that funding is always a challenge. I think for basic research, the volume of data that many techniques, not all, but many generate, creates an exciting opportunity for people who work in data science. For example, genomic sequencing, you know, is highly automated now, but the volume of data that any one genomic evaluation can generate is massive as well as, you know, very complex.
00;17;21;07 - 00;17;48;14
And so, the informatics and data science opportunities to analyze these growing volume of data is really exciting. Yeah, it feels like even though there are different research stages, there's obviously overlap when it comes to some of the roadblocks and opportunities to knock those roadblocks down. I mean, what do you see as kind of the shared pain points? You mentioned funding, I guess that goes across all stages.
00;17;48;17 - 00;18;27;09
Yeah, I think especially in a clinical setting there, there's a very high focus on cybersecurity. So, the research community is not always as involved in that as they probably needed to be. So, you know, we even have a lot of considerations that we incorporate into making sure that our systems, our data are secure to the highest standards. So that also my team tries to insulate the researchers from that type of work because we want them to be focused on doing science.
00;18;27;09 - 00;18;53;28
And in many organizations, we see researchers who have to get their hands in some of these other processes and technology issues. So a key part of what I see as my role and my team's role is insulating the researchers from those types of concerns. Yeah, which I'm sure they greatly appreciate. Obviously, there is a lot of compute resources that are required.
00;18;54;00 - 00;19;28;24
So, I imagine one of your challenges is to make sure these folks have the kind of compute resources they need. Yeah, and that's really an exciting area. We have recently completed the migration for our Genome Center of their bioinformatics pipeline from an on-premise data center to a completely cloud-based system. And we're excited that we're starting to see that gain of efficiencies from that, you know, moving that to a complete cloud model.
00;19;28;24 - 00;20;01;12
We have other projects that are more of a hybrid model. We do have a data center and our new research institute building. So, I'm excited about the new world where we can really offer computational and storage resources at a totally different scale than was needed ten years ago or even five years ago. Well, I know you're part of the Oracle Research Industry Strategy Council, a group that talked about a lot of the same stuff, pretty recently.
00;20;01;12 - 00;20;24;14
Just this May actually. So, one of the topics of discussion was how some researchers who are federally funded are kind of I don't know if struggling is the right word, but dealing with new policies around data storage and data sharing. The NIH has gotten real serious about those policies earlier this year. Why are these policies like FAIR principles coming down now?
00;20;24;17 - 00;20;56;13
And how ready are researchers to cope with those new protocols? Plus, whatever else may pop up in terms of regulation? Yeah, I think the change in policy reflects a realization on the funders that, you know, despite the expectation that researchers would share all of most of their data that was generated with those taxpayer funds, that that wasn't happening at the consistency level that they expected.
00;20;56;14 - 00;21;33;02
So, the major change this year is that that expectation is articulated much more forcefully. And so now anybody doing federally funded research is expected to make any data that does not include protected health information available to the community. I think some researchers are already doing that. So again, in the genomics world, that's already a fairly common practice. But in other areas it will require some change and different ways of thinking.
00;21;33;04 - 00;22;06;12
I'm not seeing a high level of anxiety or concern about it. I think it's something that we can work through. It's a matter of right sizing the solution. So, we don't want to oversize how we accommodate the new regulations, but we want to make sure that all of our researchers are equipped to be compliant. The reluctance that there is to data sharing is that just concerns about proprietary stuff or researchers are thinking about going to market with this.
00;22;06;12 - 00;22;31;02
And, you know, they want to keep it close to the vest. Sometimes that's the case. I think sometimes it's also academic competitive concerns. So, if you're competing for grant funding with the same people who could download your data, are you giving you know, there's concern that you're giving them, if not a head start, at least the capacity to catch up faster than they otherwise would have.
00;22;31;04 - 00;23;05;04
Does technology help in any way to adhere to these new policies and facilitate that kind of data sharing? I definitely believe it can. There's a variety of portals that can enable researchers to share their data. I think many of these have features that researchers like so that you can track how often your data assets are downloaded. In some cases, you can get a sense for, you know, where are the downloads originating.
00;23;05;07 - 00;23;39;10
What I think will be interesting over the next few years. Right now, in academia, tenure decisions are made based on publications and how often your papers are cited and so forth. I think if we can see a movement towards rewarding, how often is your data downloaded and accessed and utilized and rewarding, you know, academics that do that. I think that will be a real important factor in changing the culture around that.
00;23;39;12 - 00;24;04;28
So, in a couple of past episodes, I actually did ask our guests about this concept of open science that's grounded in FAIR principles. From what I've learned, open science doesn't mean, you know, anything goes, everybody dive in. It's all chaos. There is still scientific rigor. What does open science mean to you? What's open about it and what's still closed about it?
00;24;05;00 - 00;24;48;24
I think data sharing is a key part of open science, you know, and this is where having one foot in technology and one foot in science is helpful because if you look at the open-source software movement, there was very similar cultural resistance to that. But then as people realized that if you put your software code out for the public and they find and fix bugs in that code, that similar process can start to occur with scientific data where maybe there is an inconsistency or maybe there's a pattern in the data that you didn't recognize as, but somebody else does.
00;24;48;27 - 00;25;16;08
So, I think there's a lot to be learned from the process that the open-source software world witnessed and experienced. I think certainly in both cases, putting your either your code or your data out there as a vulnerable feeling for a lot of people. So, helping create a comfort level to get past that vulnerability is really important for the success of both.
00;25;16;08 - 00;25;44;21
But I think when you look at the long-term benefits of open science, I personally believe that the quality of work will go up. And when you pull it back to pediatrics, I think some of the very interesting work in pediatrics revolves around rare disease. And so no single organization is likely to have the numbers of patients with these rare diseases that they can independently gain the insights they need to.
00;25;44;21 - 00;26;13;12
So, collaborating and sharing data is essential for so many areas of pediatric research in particular. Well, for all the acronym fans out there, we talk about FAIR principles. That stands for findability, accessibility, interoperability and reusability. So yeah, I guess on a scale of 1 to 10, how close do you think we are to being FAIR? It'll vary from place to place, but I would just pull a number out of the air.
00;26;13;12 - 00;26;36;29
On average, I would give us a six or seven. Okay, already. Good. But probably going to get better is how I kind of interpret that answer. Yeah. So, one of the guests I pestered with the open science questions was Amy Dockser Marcus of the Wall Street Journal. She wrote a book called, “We The Scientists: How a Daring Team of Parents and Doctors Forged a New Path for Medicine.”
00;26;37;01 - 00;27;10;13
And basically, it's about patient-scientist-doctor collaborations and how that approach could get us to solutions faster. Do you see these collaborations happening? Are doctors and scientists more open to listening to and including patients and their caregivers? Yeah, I'm really seeing, you know, exciting changes in that. I mentioned earlier that we have patient and parent community advisory groups that are increasingly engaged and active in our research strategy.
00;27;10;16 - 00;27;44;14
And it's really shifting from just sometimes those initiatives start with us just telling those groups about what we're doing. But now it's really shifting to how can we do it better and how can we work through these barriers to recruitment, How can we make sure that we're reaching underserved populations? So, I find this whole engagement model to be a really exciting development, and it's really gaining much needed momentum.
00;27;44;16 - 00;28;12;13
And I find it inspiring and motivating to hear, you know, parents of children who have gone through a very difficult health conditions share their stories because that motivates me as well and motivates my colleagues. So, it really is an exciting development that's really picked up momentum. Well, thinking about the technology part, researchers kind of have to figure out what the appropriate tools are and deal with.
00;28;12;14 - 00;28;30;28
Okay, is this data I need and legacy on premises systems or can I get to it in the cloud? And you touched on this a little bit earlier about how you have a cloud solution, but you still also have some hybrid situations. Are you a hybrid guy or do you think all things in the cloud is the way to go?
00;28;30;28 - 00;29;02;13
Which way do you lean? My approach to everything is what are your requirements? And then I will help you fulfill your requirements. And so increasingly we can fulfill many of those requirements with an exclusively cloud-based model. Where it's interesting is that not only are there functional requirements, but there's cost requirements. And so, the hybrid model can often still be delivered with lower cost than a cloud exclusive model.
00;29;02;15 - 00;29;34;06
So, we're trying to be sensitive to the budgetary constraints of especially some of our early career investigators and offer a hybrid model to them as a way to get started without incurring the sometimes high costs of working in any of the major cloud providers. So, everybody in nearly every field that there is thinking about and talking about AI now and how it could change things dramatically.
00;29;34;08 - 00;29;59;06
What are you thinking about AI and machine learning when it comes to scientific research? Is it all positive and will it speed discovery and solutions getting to market? Or are you also waving the caution flag and trying to manage expectations? Because I think about how the combination of open science and it could get really interesting.
00;29;59;09 - 00;30;33;14
Yeah, I currently take a nuanced and cautious stance on AI and machine learning. If you're using those resources for data analysis, I see a lot of value to them. There's so many as we deal with these rapidly growing large datasets, the capacity of our minds to do the pattern recognition is limited. And so, AI and ML are great at pattern recognition in data.
00;30;33;14 - 00;31;24;04
And so, I think as a tool to support data analysis, I'm very positive. I worry more about the application and clinical practice of AI. I mean, being a member of the Ethical AI Initiative of the Center for Practical Bioethics in Kansas City, and I'm very impressed with the approach that they take and they deliver a workshop that is focused on if you're either buying a system that reports to be AI enabled or building something, what are the variety of ethical considerations that you should be considering?
00;31;24;06 - 00;31;55;11
And a particular area of concern is around health equity. And because we know that so many of these systems are trained on data sets that are skewed towards non-diverse populations. So, if that's what you're training these models with, and they will reinforce the inequities in health care. So, I think for some of those larger scale applications, we need to have a deliberate, careful and intentional approach.
00;31;55;13 - 00;32;22;24
It's not to say that there won't be positive uses of AI and ML, but I do think as we get closer to patient facing application, we need to be more intentional and more deliberate. Well, I want to be in a really good mood for the rest of the day, so could you tell us about research that's going on right now at Children's Mercy and some things that you're particularly excited about?
00;32;22;27 - 00;32;59;02
Yeah, and again, as I mentioned earlier, I really enjoy and thrive on the variety of work here. So I'm fortunate to collaborate, for example, with Dr. Bridgette Jones, who does research on health disparity and asthma. I'm fortunate to work with our Genome Center for Genomic Medicine, where they have a very large community facing project called Genomic Answers for Kids and focused on identifying the genetic basis for rare diseases.
00;32;59;05 - 00;33;28;23
I'm fortunate to collaborate with a wide group of experts on some of my own research where we use large de-identified clinical data from Oracle Health. So, two recent things we evaluated were how often and this is at a national level, are youth and young adults who present in the emergency room with a migraine, how often are they treated with an opioid?
00;33;28;25 - 00;33;59;29
The ideal would be 0 to 2%. We noticed that more than 20% of those youth and young adults nationally are treated with an opioid. So that type of research can then lend to process changes that challenge providers to reflect on their ordering patterns. So, the variety of really exciting research that we do at Children's Mercy is just something that excites me a lot.
00;34;00;03 - 00;34;32;15
Yeah, and on the genomics side, how close are we to, you know, all the exciting articles we read about the entire genome being mapped to the extent that we can go on and find the marker that is causing this rare disease and switch it off. Well, the very last part is where things get hard. But we've made huge strides in the recognition of the genetic basis for different rare health conditions.
00;34;32;18 - 00;35;09;01
Sometimes just finding that can lead to the realization that it's similar to a condition that presents differently but has a treatment available. And then you can try that medication on the patient with that genetic variant. And so those are the initial successes. I think the gene therapy type interventions that you might be alluding to, they're starting to regain some momentum, but that's going to be a long process.
00;35;09;04 - 00;35;42;17
So do you think people like me who just ask the question that I asked have over or heightened expectations? It's like, what is that balance between where the public thinks we should be and where actual research really is? Yeah, I think and that gets back to the even some of the societal topics that we were touching on earlier, where on the one hand there's elements of society that want research to move faster and to do more.
00;35;42;19 - 00;36;19;15
And then there's other elements that are much more of the go slow. And so, again, as a scientific community, finding that right balance and how we communicate about our work is really critical. And it's something that we really need to put an increased focus on to, you know, on the one hand, make sure that the advances that are complete and ready are utilized, which, you know, we all want that and that the emerging advances that people are participating in studies that they know that it is safe to participate in studies.
00;36;19;17 - 00;36;46;16
And then when the results of those studies are completed, that they're comfortable utilizing the output of that research. Well, for the last question, we'll stick with that societal aspect. You are an Oracle Council member, so you already know this, but Oracle believes that for the good of global health and humanity, we must understand and serve the needs of research and researchers at every level.
00;36;46;18 - 00;37;13;10
And it feels like we're facing bigger things like food security, disease prevention. Nobody needs another pandemic. What's your view on how research is only going to get more vital? And the pressure on research is only going to go up for kind of holding the earth and the species together? Yeah, that's a great question. And I am an optimist about research.
00;37;13;10 - 00;37;47;13
I believe that the work we do in research matters to the public and to the world. The examples you gave of food security, climate change, pandemics are all the, you know, major emerging concerns that all types of research are going to play a role in the solutions to those problems. And then I would pull us back to the question of how different would things have been if the pandemic had been ten years ago.
00;37;47;13 - 00;38;23;03
And to me, the research into many vaccines and rapid molecular diagnostics, those are all things that made the response to the pandemic. What it was, again, far from perfect, but much more effective than it would have been ten years ago were it not for all of the research that supported those developments. And I think that same mindset would apply to the other large scale problems and challenges that you mentioned.
00;38;23;05 - 00;38;44;00
Dr. Hoffman, thank you again for joining us today. You know, a lot of times our listeners will want to learn more about what you talked about or even get in touch with you. Is there any way they can do that? Sure. I'm on Twitter at Mark Hoffman K.C. I'm also on LinkedIn and my bio is available on the Children's Mercy website.
00;38;44;03 - 00;40;56;11
Great. We appreciate that. If you are interested in how Oracle can simplify and accelerate your research, you can check out Oracle dot com slash research. And join us next time on Research in Action.
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How can researchers who have developed innovative solutions begin to commercialize? What makes a great research-entrepreneur? And how are universities and organizations helping to bridge the research-to-commercialization gap? We will learn those answers and more in this episode with Laure Haak. A neuroscientist by training, Laure has a BS and MS in Biology and Ph.D. in Neuroscience from Stanford University, and she did postdoctoral work at the National Institutes of Health. Her career includes diverse experiences: serving as founding Executive Director of ORCID; leadership roles at Thomson Reuters, The US National Academies, and Science Magazine. She is currently founder and CEO of Mighty Red Barn, a consultancy that supports impact-based organizations building digital infrastructure, and helping research innovators go from discovery to startup. Laure carries on this work as a Research Scholar at the Ronin Institute, and Board Chair of Phoenix Bioinformatics and the Green Bay Chapter of SCORE.
You can learn more about Laure and Mighty Red Barn here: https://www.mightyredbarn.com
Learn more about Oracle for Research: http://www.oracle.com/research
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Episode Transcript
00;00;00;00 - 00;00;26;12
How can researchers who have developed innovative products begin to commercialize them? Why are digital persistent identifiers important to researchers? And who are some of the partners that can help researchers get their products to market? We'll get those answers and more on this episode of Research and Action. Hello again. Welcome back to Research in Action, brought to you by Oracle for Research.
00;00;26;12 - 00;00;47;27
I'm Mike Stiles. And our guest today is Laure Haak. Laure is a neuroscientist by training. She has a B.S. and M.S. in Biology and a Ph.D. in neuroscience from Stanford. And she did her postdoctoral work at the National Institutes of Health. She's done a lot over the course of her career, including serving as founding executive director of ORCID leadership roles at Thomson Reuters,
00;00;48;00 - 00;01;14;09
the U.S. National Academies, and Science magazine. She's currently founder and CEO of Mighty Red Barn. That's a consultancy that supports impact-based organizations that are trying to build their digital infrastructure. And it also helps research innovators like many of our listeners, get from discovery to startup. Laure carries on this work as a research scholar at the Ronin Institute and Board chair of Phoenix Bioinformatics and the Green Bay chapter of SCORE.
00;01;14;09 - 00;01;38;01
Laure you're obviously a very busy person, so I'm really glad you're on the show. Well, thank you for the invitation. I'm really looking forward to this conversation. Us as well. So we're going to talk about innovation to commercialization, because we do have listeners who are researchers and PhDs. They've got the research discovery part down. But starting and leading a startup, that's a whole different thing.
00;01;38;02 - 00;02;02;28
But before we do that, what did you want to be when you grew up and what motivated you at each step from Stanford, to ORCID, to Mighty Red Barn? Yeah. And so, I think whenever people ask about careers, it kind of depends on what you had for breakfast, how you answer the question. So, I think the best way to explain my career is that I never grew out of the childhood fascination with how things work.
00;02;02;28 - 00;02;24;19
I never stopped asking why, which has it's endearing and annoying qualities, depending again on what you had for breakfast. I was and still am fascinated with how the brain works. And after college I started graduate school in neuroscience during what was then the decade of the brain. It was a big deal. So I studied hibernation. I studied sleep wake cycles.
00;02;24;19 - 00;02;51;12
I studied how our bodies internal clock responds to light. I was also at the same time involved in the Association for Women in Science as well as Women in Neuroscience, where I managed a quarterly or a quarterly newsletter back in the day when you actually mailed things using stamps in the Postal Service. You know, we couldn’t look at how many people opened, but we had a list of about a thousand people were sending out to.
00;02;51;15 - 00;03;21;14
So during my tenure as president of Women in Neuroscience, that particular group was folded into the Society of Neuroscience. And it is still an active initiative today, which is really awesome to see. So from my postdoc with that portfolio of three years of these newsletters, I joined the Next Wave team at Science Magazine and triple-A US, which is now called Science Careers, and I worked on post-doc policy and career development for science graduate students.
00;03;21;14 - 00;03;39;15
And there's so many really smart people that are so focused on their research, they couldn't see the vast opportunities for applying their passion and skills. I think this gets back to your question, Mike, about, look, there's folks that do research, but how can I be an entrepreneur and start something? And part of it is kind of looking up.
00;03;39;18 - 00;04;04;07
So when I was at the Next Wave team, I helped to support the founding of the National Postdoc Association and then went on to be a study director at the National Academies and working with esteemed scientists to research and produce reports on research workforce issues, including interdisciplinary research, international students. And on the last report I did when I was there was on women in academia.
00;04;04;10 - 00;04;28;15
So from the academies I again moved to something completely different and a tech startup where when I started there was no job description and no job title. It sounds like a tech startup. Yes, but you have to really you know, I came out of academics in that I went to two places where there is a lot of structure, right?
00;04;28;17 - 00;04;53;26
So the tech startup was like, okay. And I was also the only peer there. So I crafted my job and my job title and became the chief science officer. And I help the company build an analytics consultancy that brought the data that they were kind of collecting and munching together to these pressing research policy issues where, you know, you could kind of look at some amount of data.
00;04;53;26 - 00;05;15;07
We didn't have, you know, a lot of it that we needed to really answer these pressing issues. So this was this time was right as compute power was really starting to take off. So I have to admit, during graduate school, we had a computer that took up the size of a room. We had an old one of those things.
00;05;15;09 - 00;05;35;29
And so now a few years later, you can now crunch terabytes of data in hours rather than weeks. And I know these days you can do petabytes in microseconds. But, you know, we're getting there in the machine, sit on a desktop, Right. So this is like this wonderful period of time when people are like, oh, my gosh, what can we do?
00;05;36;01 - 00;05;55;01
And one of the wonderful things we did was work with the National Institutes of Health on a number of program evaluation projects. We had data on grants, we had data on papers, we data on people, we had data on patents. We brought all that together to help the NIH understand what is the impact of their funding in certain portfolio areas.
00;05;55;03 - 00;06;30;27
One of the projects we did was with the NIH leadership, and it was to examine what was thought to be potential bias in the awarding of research grants, a hot button topic and lots of anecdotes. So we were able to bring to bear the compute power and the data that we had to a study which led to a publication of a paper in Science magazine demonstrating a substantial gap in the likelihood of award for black NIH grant applicants, other measures being equal that spurred the NIH to examine their review process.
00;06;30;27 - 00;06;53;26
I'm really, really proud of this work, and I'm proud that the NIH took action, both partnered with us on the work and took action to try to remedy or at least further study and remedy the situation. So some of the stuff I've done, so at the same time all this was happening, startups, right, like to go through and sell and, you know, get money for the investment they've made.
00;06;53;26 - 00;07;24;26
So I was actually part of the startup's management team that was pitching for our acquisition and we were eventually purchased by Thomson Reuters. And overnight we went from a team of about 50 people to a team of about 50,000 people. It is a really big change and I'm the kind of person that really likes the scrappy energy of startups where you can be super nimble and change your mind and oh, maybe we should do this today and started looking for an opportunity to build something new.
00;07;24;26 - 00;07;44;25
So I did the kind of spin in, you know, with the the group. So I did the spin out with the National Post Association. I did the spin in with the evaluation team and analytics team at Discovery Logic, Thomson Reuters. And then it was like, okay, I want to try something else. And this would actually be Let's start a company from the beginning, right?
00;07;44;28 - 00;08;12;29
And I had the phenomenal opportunity to come on board at as ORCID was just starting. And so I became the founding executive director and I was the first staff hire. There was already a board and bylaws and all these other things, but they didn't have any staff. So I became the founding executive director and it was just awesome. I cannot tell you how wonderful that it was, just every day on my hip pinch myself.
00;08;12;29 - 00;08;46;06
I can't believe I have this. Jobs is great. So I helped to. I have to build the operational infrastructure. I built a team and with the team, a globe of community and technology infrastructure for researcher identifiers. So ORCID is essentially a digital name for researchers that connect us with all of our professional activities and contribution. So in eight years we managed to reach financial sustainability is this is a nonprofit and we had over 10 million registered researchers, a thousand members and national consortia in 40 countries.
00;08;46;13 - 00;09;07;28
I was delighted, but it was also time for me to move on because we got where I wanted to get to. It was built and now we had to move into more of a maintenance mode. Then let's build, build, build, right. I was ready for my next build project and I stepped out in 2020 to create Mighty Red Barn, which is, as you said, a consultancy for social impact startups.
00;09;07;28 - 00;09;32;05
So here we are. Well, I'm worried that you're going to go start another company before this podcast is over, but your role at ORCID seems like a pretty big deal when you think about how critical digital persistent identifiers are. Tell me what you're trying to get done at ORCID or what you were working on at ORCID. Why digital identifiers are so important.
00;09;32;08 - 00;09;53;09
Yeah, So I guess the way to explain that is, you know, as you move from print, you know, people going to the library, when I started graduate school, we would go to the library, have a lot of time at the photocopy machine, photocopying stuff from journals. You know, people don't do that anymore. And everyone's looking for stuff on the Internet now.
00;09;53;09 - 00;10;14;06
You can't find things on the Internet unless you have a good key for finding things. Right. And for researchers, anybody with the name notices in my name, I have a fairly unique name, but it's not unique enough to be able to find all of the things that I've done and attach them to me. Even Google still gets me wrong.
00;10;14;06 - 00;10;47;00
I get messages every three weeks saying, Could you please update your record? So what ORCID does is it provides individuals with essentially this digital name, a unique digital persistent identifier that they can use as they're going through their regular workflows. Right. So for example, when you're applying for a grant, when you're registering as a new graduate student, when you're submitting a manuscript or a dataset to a repository, part of that transaction is you including your name and your digital name, your ORCID I.D, as you're going through that workflow process.
00;10;47;06 - 00;11;11;10
So it's not asking you to do any additional work other than basically using ORCID single sign on to go log into these systems, the systems, collect your ID and then attach that ID to the transaction. So now your paper includes your ORCID ID, now your grant includes your ORCID ID, your record at your university, includes your ORCID ID, etc., etc..
00;11;11;10 - 00;11;34;24
So part of that workflow and one of the things I was really, really big on since graduate school was this idea that research outputs are so much more than just journal articles, right? This huge motivation for me, articles are how we talk about the work we do, right? But there's datasets, there's software code, there's instruments made. This committee is mentoring, teaching.
00;11;34;24 - 00;12;05;14
All of these things are integral parts of the research process. So ORCID was not just about, Here's my ORCID IDs. I publish a paper. It was a way to say to the individual, here you have power in determining what to include in your professional body of work. This is your idea. You decide when and where to use it, and you can also decide what is available on your ORCID profile for public view or sharing with trusted parties.
00;12;05;14 - 00;12;34;03
We were all about providing that power and agency to the individual and based on this presupposition, that individual should control what information is shared publicly regarding their digital reputation. And yeah, so I'm I'm proud that ORCID was has been and continues to be part of the story of providing a way for research as an agency over how they are viewed on the Internet and how people can find and see what they've been doing.
00;12;34;06 - 00;12;58;24
Yeah, it sounds like the way an artist would sign their painting, right? Except providing a digital way, a digital recognition of that. Right. And you started to see more artists using digital identifiers at DMS, things like that, to say, this is my work and essentially coded in the back end. So you can't steal or repurpose the art without some recognition or citation of the artist.
00;12;58;24 - 00;13;22;07
That's all of what this is about. Yeah, the applications go way beyond researchers. Yes. Yes. Now, as promised, we need to get these folks from research to commercialization. I've never seen science and research move so fast as it did during the pandemic, and of course, with good reason, we didn't have a lot of time to putz around with red tape and bureaucracy as we had to get a product to the market.
00;13;22;13 - 00;13;46;22
Now it feels like on university campuses around the world, there's a sense of look up our support and resources because we might have to do that again or produce spin outs. What does that framework look like today and what is the level of support? Yeah, and so I think, you know, part of this is how do folks in academics do commercial work, right?
00;13;46;23 - 00;14;14;22
And so I think starting off with how do we talk about ownership? And one of the big differences between academic and commercial research, of course, is intellectual property rights. Who owns the research output shapes how information is shared and how and what can be moved into a product, right? So for me, during COVID, one of the most impressive demonstrations of the power of open collaboration is the National COVID Cohort Collaborative.
00;14;14;22 - 00;14;46;04
Also known as NC three. And I love identifiers. They used open identifiers including ORCID and dyes and organization identifiers to attribute who made what data contribution, which is really awesome. And they also coupled that with this this really strong metadata framework that enabled the combination and the combination of contributed datasets and components of dataset. Talk about awesome. This is not something you could do in one company.
00;14;46;04 - 00;15;33;05
This requires a collaboration across labs and across corporate. This work was instrumental in driving early data sharing during the pandemic, so you couldn't have gotten the product without that data sharing, right? And part of that data sharing happened, at least in part because everyone who contributed data to the collaborative knew they would get credit, even if another group did the analysis and knew that if some missed study that was contributed or some dataset that was contributed was later withdrawn, that that data could be withdrawn from their analysis as well because of the way that persistent identifiers in metadata had been that that framework had been set up at the get go in NC three.
00;15;33;12 - 00;16;00;12
So the group managing the collaborative actually won the inaugural Data Works and Challenge Prize for data sharing earlier this year, and I encourage you to check it out. Is really phenomenal piece of work. And I personally think that's the way we need to start thinking about getting product to market is the step before that which is how do we enable data sharing that allows people to collaborate on these problems?
00;16;00;14 - 00;16;18;28
Yeah, after this, I think you should go work in Hollywood because, you know, you are you see these screenplays that were written by about 11 or 12 people and it's like, okay, who contributed what? Right now that industry kind of has the same problems of people being, you know, the collaborations and what was mine versus what was else's.
00;16;19;01 - 00;16;58;05
Right. But, you know, the world needs solutions. And the younger you are, the more you've gotten used to near instant gratification. We're used to seeing things happen. So have expectations and research shifted as well, or our research institutions moving as fast to commercialization as they can? What's driving that need to commercialize? Yeah, I mean, you've got the by dual act that shifted everything, at least in the US and there's been a strong push ever since then was in the mid-eighties right of where universities set up tech transfer offices and you know have patent attorneys on staff advising people.
00;16;58;05 - 00;17;23;14
There's a number of universities that have spin out incubators, things like that. If I don't think it's getting faster, if anything, I think some universities are realizing there's a huge amount of effort and money that they're putting into these centers that they may not be recouping there. It hasn't been a fast win for many universities in this space, but it's certainly active.
00;17;23;17 - 00;17;49;08
I think, again, coming back to my previous comment, I think in addition to these spin outs and commercialization, where academic IP intellectual property is acquired by a commercial entity, I think what I would love to see is more people considering this collaborative model, right? One in which there is incentive baked in for data sharing by all parties.
00;17;49;08 - 00;18;16;24
Right. And I like to see this civilly. Is it science fiction? Right. We can look at how high energy physics is done, right? There's this large inter-country collaboration at CERN using shared equipment and management. And, you know, researchers can openly access this facility, you know, by applying to work there. And three, this a covered example I just mentioned proved this concept in biomedical sciences.
00;18;16;24 - 00;18;43;18
Right. What I see that similar in both of these models is both the intent to collaborate on big Thorny and of course, expensive like really crushingly. You need to answer the question right now. Problems. There's also the willingness to fund at the highest levels. And I think this might be what is changing a little bit where you see and an agent and a NSF starting to fund these larger collaborative efforts.
00;18;43;18 - 00;19;09;27
I'm really happy to see these things happening. And then also what, NC three and to some extent CERN and others have done is operationalizing attributions using these open and persistent digital identifiers, not just for people, not just for the papers, but for all of the things and the places that are involved in the project so that you can kind of deconstruct and tease apart and understand, Hey, I did this part and I did that part right?
00;19;09;27 - 00;19;35;15
So everyone participating gets credit. Whether you build a detector, develop the methods, collect the samples, perform the analysis, curate the dataset, or even fund the initiative or house the researchers and the equipment. Right? All of that. Everyone understands your different part of it. And I think there is room in this collaborative model for academic and commercial and government entities to work together.
00;19;35;18 - 00;20;02;18
Collaboration. It reduces the upfront development costs for companies, It enables broad talent sharing, which is pretty awesome. It allows, like the postdocs in the academic lab to get some corporate experience working in these collaborations. And it also leverages the strengths of each sector the ideas, the innovation product to market, which most people in academia never think about product to market as well as risk reduction.
00;20;02;18 - 00;20;31;14
Right. Which again, most people in academia are thinking about risk reduction. And I would love to see more research groups looking into these cooperative business structures as an option for bringing products to market. We provide recognition, operational frameworks and I think also really important is this idea of equity for all of the parties involved in this. And you asked for some practical examples and there's actually a co-op accelerator program at START that co-op.
00;20;31;14 - 00;20;52;24
So it's not like you can only get startups through a venture model. You can also get or a venture for profit model. You can also get startups moving through these accelerator programs that are really focused on the co-op structure. So something to look at. If you've met a lot of startup founders, you start to see they have a unique set of talents and drivers.
00;20;52;24 - 00;21;20;16
You know, research entrepreneurs, PhDs may not be like them. That may not come naturally. They've got to learn product market fit, funding strategies, sales, marketing, regulatory compliance, business skills. It's kind of not fair. It's like that, Is it not enough? I'm not a research genius now. I have to be Richard Branson on top of that. Right, Right. So our grad schools, are anyone helping train them to be entrepreneurs or is it assumed they probably don't need to be?
00;21;20;17 - 00;21;42;02
Yeah. And it's funny because, like, our entrepreneurs are actually trained to be entrepreneurs is like, where does that come from? Well, it's almost natural inside me, right? I'm going to say it probably wasn't natural. Looking at any number of things is exposure to certain ideas and concepts and ways of thinking and doing that happen. Right? And so I'm going to tell a story.
00;21;42;02 - 00;22;05;08
I can tell a story here. So back in the day when I was at Science magazine, working on Next Wave, working on postdoc policy, that was when my first kid was born. Okay, fast forward 20 years, several stops later in my career, and I returned to pursue our policy in an early career workforce conference sponsored by the National Bureau of Economic Research.
00;22;05;08 - 00;22;27;04
This is like two years ago. So the very same issues were on the table. And I just like, Oh my God, I feel like I stepped into the Wayback Machine, right? There's perceived poor career prospects by the postdocs. They felt stuck long terms in low paying apprenticeships, no substantive change in the ability to attract and retain diverse talent into science careers.
00;22;27;04 - 00;22;52;28
It was really frustrating even to just sit in the room and listen to the the economist talking about this. I'm like, I can't believe things haven't changed in the last 20 years. This is insane, right? So one of the key skills of researchers is our ability to focus on a problem and give it all we've got. Even if it looks hopeless, we give it all we've got.
00;22;53;04 - 00;23;17;08
And to some degree, that's a parallel skill with entrepreneurs is just like hammer away and make it happen. Right? But it also means it's really hard for us to look up and around and see what else might be good or fun or wise for our career, right? It's even more difficult to do this when the culture of science is driving for speed above all else.
00;23;17;08 - 00;23;39;27
We've got to answer this question right now. Right? Publish or perish. Publishing is so important, right? And because of that, people hold their findings really close for fear. If they're going to be scoops they don't want to share. They're not they're actually disincentivized from sharing. And they're, you know, in their cubbyholes working on their stuff. It's really not a great way to think about how can I be an entrepreneur, right?
00;23;40;04 - 00;24;06;07
So when the structure of science does not prioritize credit for all the people and it doesn't include the necessary components of the research process and what you get credit for collaboration and career development more in your question is not the outcome. So we do need entrepreneurial researchers, whether they spin out a product, run a lab, work in research policy, run a nonprofit.
00;24;06;09 - 00;24;35;06
All of these things are good skills such as team management, data sharing, budgeting, strategy and operations are all essential. And of course, looking at business, these are the same skills. Entrepreneur Sorry, entrepreneurs need to start a business to right? So these you have to have these skills, but it's not what you learn at the university, right? So the big questions are who provides the training and when is this training provided?
00;24;35;06 - 00;24;58;06
And then how? If you have the training, how do you get researchers early career and the supervisor is to prioritize participation in the training. You're supposed to be in the lab. What are you doing outside the lab? How dare you? Right. So one shining light here is the National Institutes of Health launched a program called Best Broadening Experiences in Scientific Training.
00;24;58;06 - 00;25;23;18
And this is one example of a science agency actually providing incentives through a funding program for these training experiences for grad students and postdocs. And I can tell you, I was on the review panel for one of these best sessions, and it was really interesting listening and reading what the universities were trying to do to get people just to come to the training courses that are part of their training program.
00;25;23;18 - 00;25;50;20
As a grad student and a postdoc, it was incredible the amount of resistance that there is in the university setting for having researchers do anything other than their particular experiment. There's a massive cultural challenge there. I mean, it sounds like because you're right, again, the research is doing the research because that's their passion. And it's the old thing of, you know, if I just don't think about this other thing, maybe it'll go away, right?
00;25;50;23 - 00;26;11;20
If I don't think about the fact that there's not a job for me at the end of this, maybe it'll materialize magically. Somewhere in there. Yeah. Okay. So I'm a university dean that could never happen. But just play along with me for a minute. I come to you and I say, Laure, I want to build programs and a culture around turning research into innovative product.
00;26;11;25 - 00;26;34;20
What resources do I need to make available and how do I build a supportive community around that? And I guess that speaks to the challenges of fighting that resistance, you know, getting community to pull people in. Right, Right. And so I think, you know, the other question at universities is anywhere is always cost rate. How much more do I need to invest to create these programs?
00;26;34;20 - 00;26;58;02
I think the great and wonderful answer here is that universities don't really need to invest a whole lot more to create a program. So there's a number of universities. Many, many of them already have something called a small business development centers. These are associated with the Small Business Administration, and they're staffed by business and technical advisors that can help problem solver access capital and help with business planning.
00;26;58;04 - 00;27;20;04
Woo Right. You know, I think anything new, it's already there. And they provide services to people at the university and actually at SCORE are we we collaborate with folks in the SPDC as well and we can send people from the community over to these groups at the university to get the technical assistance they need. That is beyond the scope of what we do in this program.
00;27;20;04 - 00;27;45;13
So I think it's less a matter of the university setting up more resources. It's really more connecting entrepreneurs with the resources that are already in the community. And I mean, frankly, we run into the same challenge with data sharing. There's tons of resources available through the university library, but researchers often have no clue to reach out to the librarian for help with data sharing.
00;27;45;16 - 00;28;18;21
So I think all of us researchers have myopia, but so do research administrators and services like SDB sees and score as well. Right? How do we reach and run the workshops, walk the halls? Right. We have to be really proactive and go out and engage with the researchers, meet them where they're at, and engage with these groups of people about entrepreneurial skills, practices, meeting with mentors, things like that.
00;28;18;21 - 00;28;37;01
So I think all of us need to do better at looking up and out, asking for help, listening. And, you know, it's not just product market fit. It's like the focus groups that we always tell entrepreneurs to do. I think the services that are out there for entrepreneurs also need to do the same thing. I think about biotech and medical research entrepreneurs.
00;28;37;01 - 00;29;09;15
They've got like an extra bucket of problems because they have to work with the health care industry. Highly regulated, very complicated, not big risk takers when where innovation is concerned, can the sharing of data be a difference maker in all that? What data should the researcher bring to the table and how to smooth process? Yeah, so there are two wonderful sets of guidelines that are out there and people are working on implementing them and they have really great acronyms.
00;29;09;15 - 00;29;31;29
One is called CARE and the other is called FAIR. Right? So I think this this comes back my to your question, there is no one way to answer that question. I think the ways you answer this question is by providing a framework that allows people to use a framework to answer the question for their particular situation. Okay, So FAIR stands for findable, accessible, interoperable and reusable.
00;29;31;29 - 00;29;48;27
And it tells us how to share. It tells you how to create your data set, use persistent identifiers, you know, make sure that this is there is some way for people to request access to your data set, whether that it's in a repository of a landing page, make sure it's interoperable, that there is a good set of metadata.
00;29;48;27 - 00;30;10;29
Well, describe to explain what the heck's in your dataset. Right. And then make sure it's reusable, right. That there is some way to pull it down into a file, share it. It's already in a database or our code, whatever it is, right? That that's all there. So that's FAIR. How do I create and curate my data set so that it is accessible and usable by other people?
00;30;11;01 - 00;30;37;02
But there's also another component that is as important, and these are enshrined or encompassed in the CARE principles, and these were developed through the lens of Indigenous data sovereignty, and they provide a framework for what to share, right? So CARE stands for collective benefit authority to control responsibility and optics. And like when you're working with biomedical data, you know you can't share personal level data, period.
00;30;37;08 - 00;30;58;10
That is ethically wrong. To share personal level data, you have to identify it. So that's a component of, for example, what you could put in CARE. Do you have the authority to control the data that you're sharing, or does somebody else have the authority? For what benefit are these data being shared? These are all really important questions to ask when you're when you're sharing data.
00;30;58;10 - 00;31;18;01
So as gets to like, I'm really big on attribution, right? So I think and I don't think it's even I think I'm just going to make the bold statement that we have to recognize the rights of the people from whom data are collected. I think for too long we've only recognized the rights of the people who are collecting the data.
00;31;18;06 - 00;31;42;15
Right. And I don't think that finders keepers should be the ruling ethos for how we share data. I think we can do a lot better and the CARE principles get us there with that collective benefit authority, control, responsibility and ethics framework. And so between CARE and FAIR, we address for people and purpose, and together the guidance is share your data as openly as possible and as closed as necessary.
00;31;42;15 - 00;32;06;28
So there isn't just open data shared with everybody. It's like, let's really think through what's in this data set. Do I have authority to share it? What is my responsibility for protecting the information that's in this data set, and how can I collectively benefit the community by sharing? How can I do this in an effective way? And I really, really love how these two sets of principles work together and foster this way of thinking.
00;32;06;28 - 00;32;35;02
This framework about intellectual property that is intentionally respectful for the full set of stakeholders and rights holders of the data that's represented in the data set. So that may not be as specific as an answer as you want, but I think that's the best way to address this is using these frameworks. It does. It sounds like it. Oracle for Research has actually provided research to commercialization support for a handful of researchers like University of Bristol biotech spin out Halo Therapeutics. Is that a good role for a big old tech company like Oracle to play? Is that appropriate? Oh my God. When I met you guys at the Research Data Alliance meeting, I was so excited to know that there's Oracle for Research exists and that you guys are providing tech support for founders. I think it's awesome.
00;32;54;07 - 00;33;23;23
I do. And this is part of the collaboration I'm talking about. You have skills and resources that startups don't, and to be able to share those resources is for the collective benefit of all the parties. Awesome, right? So I think, you know, this small grant funding and technical support that you guys have done with the community, support those folks that are our need to use or want to use cloud computing, super important community building is also a big one for me, obviously, right?
00;33;23;26 - 00;34;00;19
Bringing together aspiring entrepreneurs to share their stories, to meet with mentors, to meet with other entrepreneurs. It may be a little bit farther along the pathway. Super important to do that and you're starting to do what you're doing that a bit right? Supporting collaborations. One of the things I've heard over and over again in this data space is, yes, there's these cloud computing services, but one of the big challenges is the middleware that's needed to enable access to the data in the cloud server that's respectful of privacy and any like data sharing challenges that you might have.
00;34;00;19 - 00;34;25;28
Right. In that that federated sign and piece is really challenging for a lot of folks building these data infrastructures. So there may be some some role that you can play in helping to support collaborations to answer some of those questions. And it's not saying that there's a particular product that you guys can build, but maybe say, hey, here's some options, here's how they can be implemented, here's some folks doing it right.
00;34;25;29 - 00;34;52;09
Why don't we have a meeting or something to help others figure out how to also implement those? And then the thing you guys have been doing, again, partnering. We talked about research, data Alliance. I think you also participate in these giant and TNC meetings looking for opportunity is to work with research networks and identity federations and data sharing alliances in developing these cross-platform solutions that work on a global scale.
00;34;52;15 - 00;35;22;04
All of those are great. So I think when I look at this, is providing some hope right. We have this great idea as an entrepreneur and is like, Oh my God, how am I going to do this Right? Providing some hope to those of us who who want to start developing a tech-based product for the research community, that someone out there is willing to share some resources to help us test our idea.
00;35;22;04 - 00;35;51;10
I think that that would be the way I would think about it. Yeah, well, technology as a driver, it's an enabler for nearly all research entrepreneurs and biotech founders. There's no way around that. But as we're seeing with AI, technology appears to pop up and move at incredible speed. So what do you think researchers should be doing to make sure they understand what the right technology is and how to use it for things like cost, performance, security, flexibility, scale, those things?
00;35;51;13 - 00;36;14;02
Yeah. And so I was thinking about this and, you know, tech is necessary for everyone, as you know. Right. And, you know, I work with a lot of small businesses through my SCORE mentoring volunteer service. Right. And these are people starting restaurants and hair salons and retail outlets. And, you know, they're like, how do I do this? They also have to use cloud-based solutions, right?
00;36;14;02 - 00;36;38;18
Accounting, e-commerce platforms. They have internal external communication platforms like the storage slack and other things like that, discord on customer management systems out there. All of these things people think of tech and they think of cloud computing and massive compute resources that you need for time. Actually, yes, you need that, but you also need these other cloud solutions.
00;36;38;18 - 00;37;00;14
If you're going to run a business, you have to have all of these other kind of operational pieces as well. Right? And there's other things like, Oh my God, I have to look at mileage tracking and receipts management, inventory control, all the things no one wants to think about, but they're all essential parts of running a company. And all of these to also have cloud-based solutions.
00;37;00;14 - 00;37;20;21
You don't have to do stuff on a spreadsheet that's only on your computer. You can have it in the cloud, you can move around. This information comes with, you can easily share, you can collaborate on documents. And I think Mike, to some degree, I think people need to pay attention to this as well, right? They have to do this as well.
00;37;20;23 - 00;37;42;06
Things like SCORE, right? Used to be only face to face mentoring now is almost I think over 90% of mentors now in the space of three years shifted from face to face to virtual meetings and like it was like, oh, I didn't do this earlier. An orchid was run as a virtual office From the very beginning. We never had a building, never.
00;37;42;10 - 00;38;12;28
And my consultancy is also virtual, right? So it's how do we use these wonderful cloud-based resources to really expand how we can do our work, where we do our work and open up time that we didn't have before because we were running around or trying to share documents through email or trying to collect all these things that the cloud is made possible for us that really enable collaborative work I think is great.
00;38;12;28 - 00;38;34;14
So your question, what tech do you use? And this is a question that can't be answered easily. Again, it depends on the stage of your company, the size and scale of your team where you're operating and of course your product, right? So I will always take an iterative approach, have a conversation. Where are you in your evolution as a company?
00;38;34;14 - 00;38;55;19
What is your product? What are your needs? And then also make sure my big advice is make sure when you pick a technology for whatever it is that, it is something you can evolve and adjust and iterate with. Then, you know, if it's one particular platform, make sure has an API, make sure you can get your data in and out of it.
00;38;55;23 - 00;39;18;21
So as your needs evolve, you can transition to something else if you need to. That better suits you need as a company. Don't get locked into a particular solution because you'll find like if you get locked into one, I don't know, customer relationship management system or fundraising system. And then you can't move as your company gets bigger, you're kind of screwed.
00;39;18;27 - 00;39;44;25
So you have to make sure you you plan for, in my opinion, to plan for flexibility from the very beginning to allow you to grow and evolve as a company. And then that last thing, it comes back to experience at work. It ensuring privacy. What did you actually need to collect? Right? And if you have to collect personal love with data, make sure that you're ensuring the privacy of the people you're collecting it from.
00;39;44;25 - 00;40;06;10
So that's always a big one for me. And that's where Cloud Solutions not putting this stuff on your laptop are. So, so important. Well, we talked a good bit about partners and partnerships. Some people like to try to partner with our friend, the federal government. Federal funding is critical for academic and nonprofit researchers, the NIH as a funder.
00;40;06;17 - 00;40;28;16
It's driving change in the research space with things like the updated data management and sharing policy. And that policy is that researchers now have to plan and budget for the management and sharing of data when they apply for a grant. Are these mandates going to lead to real and meaningful changes or is it window dressing? What's your take?
00;40;28;18 - 00;40;50;25
Oh, another story. So one of the early community stories we did, ORCID had a question about mandates. There are always these conversations about mandates and the folks that would do put in place the mandatory oh, we couldn't possibly put in place the mandates or just irritate the people who would use it like the publishers can't put in place mandate because then the authors won't come to our platform.
00;40;50;25 - 00;41;18;20
We'd want to put up any barriers to, you know, to people using our stuff. But we did the survey and one of the questions on it was, Hey, would you want work it to be mandated by publishers? And since surprisingly, something like 80% of the respondents said mandate organ, we're like, okay. And that in turn, the funders and publishers are like, Oh, I had no idea people would be into this.
00;41;18;20 - 00;41;40;14
So that, you know, it was like researchers asking for a mandate in in a way with the researchers were asking for was would the publishers and funders please use ORCID? Please just use it so we can use it as researchers and gain the benefit. It was an interesting kind of reverse way of doing the mandate. So I think now we see these two stories about mandates.
00;41;40;14 - 00;42;08;28
You know, no one ever mandated Google search, right? It was remains as elegant and easy solution of finding things on the Internet. People still use it in droves, even with problematic privacy frameworks or revenue model. Right. It's because it's so easy. This just does what supposed to do. You get in and out your data, right? So why do we need to resort to mandates to get people to use things and do things that should be good now, which gives me to my second comeback, right?
00;42;09;02 - 00;42;32;21
Things like ORCID and data sharing are usually promoted or marketed as quote unquote good for us. It's like eating broccoli. Some people like broccoli. A lot of people don't like broccoli or they will not go out of their way to eat broccoli like a guy eats broccoli because it's good for me. But given this choice between green vegetables and I don't know, chocolate, I'm sure most people will head for the chocolate.
00;42;32;24 - 00;43;08;16
So why don't we design things and workflows and incent dev structures that provide the sweets that people want? Right? So these research policies that are enforced by mandates are usually ways getting researchers to do things that, you know, I like broccoli, I got to eat my broccoli. And then if they don't work very well because the systems haven't been designed in the workforce, haven't been designed to make it a delicious experience for the researchers, where you might I actually need to use the mandate because everything just works well.
00;43;08;19 - 00;43;47;10
Right. And the other problem here is that the culture of research is also about kind of protecting experts in this. Right. And so when you're talking about data sharing, if there isn't something that's done with data sharing that makes it attractive to share data, not just you must do it, but it's actually, hey, this is going to help me in my career, then the mandate, you know, it's just going to be this that people put up with and will find ways of getting around and delaying because they don't see the benefit to them in actually sharing the data.
00;43;47;16 - 00;44;32;19
And some people actually see harm. And that's a lot of the conversations that are happening at NIH today and over the past couple of years. It's like, what is that, that harm reduction that can be done to kind of reduce the barriers to data sharing. And so one of the projects I worked on that my consultancy was with the Federation for American Societies of Experimental Biology, also known as Faseb, putting together a program that kind of worked side by side with the NIH to see how can we as fast of this Federation of society is support the community in sharing data and make it an attractive prospect for researchers, not a grudging thing to do.
00;44;32;20 - 00;45;04;15
Right. So that gets back to I mean, you guys talk about this all the time, I'm sure. How do we work with our communities to design products and workflows that work for them, that are seamless, that are delicious, that provide a benefit? This is all user centered design. And I feel like sometimes what happens in the research community is people forget some of these basic design principles and they use these sticks through the form of mandates to get stuff accomplished because those design principles just aren't practiced in the community.
00;45;04;15 - 00;45;25;19
And so again, coming back to NC three, that big COVID collaborative, it made data sharing easy for users with this metadata model that was partly automated and also a service to help researchers with the curation process. Instead of saying you must curate your data, they'll say, Hey, you need to curate your data and we'll help you with it.
00;45;25;21 - 00;46;03;14
Huge difference, right? And at facet of this Data works project actually provided a substantial award, $100,000 for two teams that could show their data sharing and the impact that data sharing on a community that's not just a $5,000 prize, it's not just a little ribbon you get. It's a substantial award. And they had over a hundred teams submit applications for these awards and get a fabulous recognition by the NIH and the broader community and can show the way for others, Hey, we made this work.
00;46;03;14 - 00;46;31;16
Here's how made it work. They become ambassadors in the community and provide that incentive and mentoring for other people who are interested in sharing data. So I think that's what needs to happen. So you asked about, you know, what will mandate help? Yes, it has raised the urgency of data sharing in the biomedical community. Right. There's still a gap between this desired state and operationalizing how we share data.
00;46;31;18 - 00;46;54;13
And there is this series of surveys called the State of open data that happen to be going on for four years now. They've found a consistent desire among researchers to share data, but also a consistent need for more and better pathways to do so that also embed this attribution and respect components we've been talking about. So I think that's where we need to go next with the competence will make progress.
00;46;54;20 - 00;47;25;15
We're already making progress. We need to celebrate success and we also need to collaborate on a user design system and mandates like NIH is doing could be part of the solution. But they're not the solution. They're not the only thing we do. I've convinced myself I like broccoli, so self-delusion is very underrated. Yeah, well, Laurie, this has been a great conversation, super useful to those listening that are in that place of I've researched an innovative product.
00;47;25;15 - 00;47;42;14
Now what you know, thank you so much again for making the time. And if people want to know more about you or what Mighty Red Barn does, is there any contact info for you? Yeah. So you can come to my LinkedIn profile. Probably the best way to get me. I mean, I have a Twitter profile ID at Hack Yack.
00;47;42;17 - 00;48;02;11
Probably the best way, however, to get me is through my website at www dot mighty red barn dot com and there's a contact us form on there and I'm happy to talk to folks where you can contact me through LinkedIn and you to send me message that way. So yeah thank you very much I really really enjoyed the conversation today.
00;48;02;11 - 00;50;14;27
Really good questions. That's great. Me too. If you are interested in how Oracle can simplify and accelerate your research, all you have to do is check out Oracle dot com slash research and join us next time on Research in Action.
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You can learn more about Dr. Bruning and his work here: https://researchers.adelaide.edu.au/profile/john.bruning
Learn more about Oracle for Research: http://www.oracle.com/research
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How can patients and their families become more integral in the research process and drug discovery? How can citizen scientists and patient-led research become more accepted in the scientific community? And who qualifies as a citizen scientist? We will tackle those questions and much more in this episode with Amy Dockser Marcus, a Pulitzer Prize-winning journalist and author of the recently published book, “We The Scientists: How a daring team of parents and doctors forged a new path for medicine.” Amy is a veteran reporter at the Wall Street Journal and won her Pulitzer Prize for Beat Reporting in 2005 for her series of stories about cancer survivors and the social, economic, and health challenges they faced living with the disease. She has covered science and health at the Journal for years, and she also earned a Master of Bioethics from Harvard Medical School. Learn more about Amy and her new book: https://www.wsj.com/live-qa/amy-dockser-marcus-on-her-new-book-we-the-scientists/4BFE8957-882E-4C93-B335-7151B8411310
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