Feb 6, 2024
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:
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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.
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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?
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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.
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So Chris, you're obviously a very busy person, so we really appreciate your time today.
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Thanks, Mike. I'm happy to be here.
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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.
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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.
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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.
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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.
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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?
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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.
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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.
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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.
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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?
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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.
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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?
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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.
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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.
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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?
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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.
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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?
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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.
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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.
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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?
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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.
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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.
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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.
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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?
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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.
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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.
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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.
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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.
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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?
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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.
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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.
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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.
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And that's just one example of how I think that we've seen progression in this particular space.
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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?
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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.
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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.
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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.
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And that's really sort of my core belief.
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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.
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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.
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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.
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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.