Research in Action

Where are the biggest opportunities to leverage AI in cancer diagnosis and treatment? What are the biggest barriers remaining to move away from a one-treatment-fits-all approach to treating cancer? And how are AI, radiomics, machine learning and deep learning helping to understand which patients will respond best to which treatments?   We will learn all that and more in this episode of Research in Action with Otavio Clark, M.D. Ph.D. and Principal Research Consultant at Oracle Life Sciences.   ---------------------------------------------------------   Episode Transcript:   00;00;00;00 - 00;00;26;16 Where are the biggest opportunities to leverage AI in cancer diagnosis and treatment? What are the biggest barriers remaining to move away from a one treatment fits all approach to treating cancer? And how are ready omics, machine learning and deep learning. Figuring out which patients will respond best to which treatments will learn. All that and more on research and action in the lead in the world.   00;00;26;19 - 00;00;48;02 Hello and welcome to Research and Action, brought to you by Oracle Lifesci Answers. I'm Mike Stiles, and today our guest is Ottavio Clark and Oncology and Specialty Therapeutics executive at Oracle Life Sciences. Now that's a field he's been in his entire career. He has his Ph.D. in oncology and specializes in all things evidence based research, real world data, real world evidence.   00;00;48;02 - 00;01;13;25 And what we're going to be talking about today, AI and the critical field of cancer research. Octavio, thanks a lot for being with us today. I might tinker for the end of the invite. It's a pleasure to be here. And we are really discussing a fascinating issue. That is how the ACA is changing the healthcare landscape. But before we start, I'd like to make a disclaimer.   00;01;13;28 - 00;01;45;27 We would discuss a lot about the study's findings, but we have to to have in our minds that these results that you discuss, they are still early. These findings. We have yet to be validated in prospective longer term studies, but we will discuss the only things that we have a clear direction of the trend. You added that things are going, so it's important for everybody to to think about this product by the cancer, something introductory.   00;01;45;29 - 00;02;10;17 So I think that's pointing towards trends but not about something definitive when you see something moving on in this direction. Okay. Okay. Yeah, that's totally understood and understandable that that would be the case. I do really want to dive right into this so we can make good use of our time. So what are some of the more impressive advancements that we've made in cancer treatment lately?   00;02;10;17 - 00;02;40;18 And does that mean success rates are satisfactory? Has personalized medicine helped to that? Where are those most promising opportunities to improve personalized medicine where cancer is concerned? It's a revolution in personalized medicine. It changes everything in oncology. And honestly, when I was in the medical residence in 1996, 1998, I did not think that we could see these during my lifetime spent This person.   00;02;40;25 - 00;03;15;05 The medicine has changed the way that we practice quality because it's today for many different types of tumors. We can pick treatments that are tailored to read their genetic profiles, and it enhances the precision and the effectiveness of the therapies. We left our scenario before Where do we use the same drug for everything? And now we can get the genetic profile of the patient of the tumor and try to find a targeted therapy that is limited to any specific type of cell.   00;03;15;06 - 00;03;42;03 Sometimes growth genes. This is wonderful. It has improved a lot. The outcomes of the patients have been becoming better and better in the last years, but we still have challenges here. The first one is that we don't have this kind of personalized medicine for all types of tumors, and one very important things. Not all patients respond to the personalized medicine as we would expect.   00;03;42;05 - 00;04;13;05 What it means. We still have patients that do very well, but we still have patients that don't do so well as we would want to to to have it. So the overall success rate in treating cancer with this personalized medicine approach have improved, but they are not yet 653 across all cancer types in demographics. We are still trying to see some improvements in upfront patients elections.   00;04;13;08 - 00;04;39;27 That is, how can I making this personalization even better by selecting out the fraud patients that have a similar genetic profile, but that they can I can identify those that. Do you have a good response to the therapy and those that will not get a good response to the therapy? If we could do this separation based split, we would have a much more effective treatment.   00;04;39;27 - 00;05;10;15 Of course, what are the opportunities and being able to select those patients who are most likely to respond to a particular treatment and identify those who aren't likely to respond? I mean, how might those kind of better patient classifications affect the current staging systems and the epidemiology of cancer? That's a long history. But let's start. If you if you can select patients, we will, of course, be able to do two things.   00;05;10;15 - 00;05;32;29 The first one is offering the patients that whom you will you expect to have a good response to the treatment, to give an effective treatment, and you split the basis that we expect that you not respond to that kind of therapy. To me, you try to offer them some sort of therapy or to select a clinical trial for these patients.   00;05;33;01 - 00;06;06;08 Well, how are we dealing with this? First, there is are there is an artificial intelligence to that we call radio omics today. These are the army is is is a technique that can extract huge quantities of information from medical imaging like key MRI scans and so on. And these really omics can analyze very complex patterns that we human beings can not see and it can give us an additional classification.   00;06;06;08 - 00;06;41;20 And this is something that will help us in dividing this patient, possible responders and possible night responders when we integrated these Arabian Sea tourists in deep learning machine learning technologies, we can identify the subgroups of patients that will really be more beneficial. There is a very interesting study that was recently published this year to the European Studies. This patient included 1300 patients with no small cell lung cancer without early stage disease.   00;06;41;20 - 00;07;17;16 You let these early stage stage one station through this model was able to predict three, six, seven, 6% accuracy. The patients that would be old in not have a nearly relapse just after the treatment. So they analyzed the data from 3000 patients they put inside of these machine learning system. And in this system the tools could be told that around 40% of the patients could have avoided treatment that was not effective for them.   00;07;17;19 - 00;07;44;25 40%. This number is huge and it reflects what we see in practice. Even in this personalized medicine, we still have 46% of patients that would not respond adequately. The problem is we don't know how how to split the patients to be, how to they try to station. So they and these new tools, these artificial intelligence tools, the omics machine learning, deep learning, they are offering the opportunity for this better selection.   00;07;44;28 - 00;08;17;05 And of course it opens huge opportunities for research and development because, okay, we have now these subset of patients that we respond, what do you do with those that don't respond? So it's brought to the need for developing new drugs and new tools that when you get to these subset of patients that are not responding to current treatment into new developments and new new forms of treatment, well, but it is complex and it is still in its infancy.   00;08;17;05 - 00;08;40;27 Everyone's still trying to figure out what it can and can't do best, what the best applications are, What are the complexities of bringing a high end to cancer diagnosis and treatment? And, you know, in what ways do we need to kind of be careful as we start incorporating it? Yeah, we need to be very, very careful with this because we still don't know everything about even the specialists.   00;08;40;28 - 00;09;12;16 They they really don't understand how these tools fully functions. Well, we can really spend a day discussing this topic, but I'd like to call attention to three important feature is here. The first line is we have to care about data, privacy and security because these systems, they use patient data to be treatment. You know, you have to teach the machine about what to do, about what to do, analyze, and we have to have data from real patient.   00;09;12;18 - 00;10;03;21 And often these training data sets that people are using in different approach. So we have to be sure that they have privacy of the data. The security of the data is is assuring and that we have a legal standards like HIPA and that can maintain the confidentiality and the trust of the patient in the system. The second and very important one is the bias in many of these A.I. systems that you see that we have today, because they way that they are trained and again, the machine is learning what we want them to learn and they can sometimes perpetuate or amplify biases if they are trained in data that is not representative of the food   00;10;03;24 - 00;10;32;17 of the food population. One One very good example of these is that the accuracy of some A.I. tools into the noses of a melanoma. Melanoma is that I see that has a black sheet, a black color, and it is very common in people. It can occur in white people and in black people, but they must the A.I. tools, they have a bias for the white people.   0

What is the MOSAIC-NLP project around structured and unstructured EHR data? Why is structured data not really enough for drug safety studies? And to what degree is NLP speeding up access to data and research results? We will learn all that and more in this episode of Research in Action with Dr. Darren Toh, Professor at Harvard Medical School and Principal Investigator at Sentinel Operations Center. www.oracle.com/health www.oracle.com/life  www.sentinelinitiative.org -------------------------------------------------------- Episode Transcript: 00;00;00;00 - 00;00;26;14 What is the MOSAIC and LP project around structured and unstructured data? Why is structured data not really enough for drug safety studies? And to what degree is NLP speeding up access to data and research results? We'll find all that out 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;26;14 - 00;00;50;14 I'm Mike Stiles. And today our guest is Dr. Darren Toh, professor at Harvard Medical School and principal investigator at Sentinel Operations Center. He's got a lot of expertise in Pharmacoepidemiology as well as comparative effectiveness research and real-world data. So, Darren, really glad to have you with us today. Thank you. My pleasure to be here. Well, tell us how you wound up where you are today.   00;00;50;14 - 00;01;26;22 What what attracted you in the beginning to public health? Good question. So I trained in pharmacy originally, and I got my Masters degree in Pharmaceutical Outcomes Research at a University of Chicago, Illinois, Chicago. And it's where I first learned about a field called Pharmacoepidemiology, which sort of very interesting to me because I like to solve problems with methods and data and pharmacoepidemiology.   00;01;26;22 - 00;02;00;29 It seems to be able to teach me how to do that. So I got into the program at the Harvard School of Public Health, and when I was finishing up, I was deciding between staying in academia and going somewhere and getting a real job. And that's when I found out about an opportunity within my current organization and I've heard great things about this organization.   00;02;00;29 - 00;02;29;26 So I thought I would give it a try. And the timing turned out to be perfect because when I joined, our group was responding to a request for proposal for what is called a mini sentinel pilot, which ultimately became the sentinel system that we have today. So I've been involved in the Sentinel system since the very beginning or before we began.   00;02;29;28 - 00;03;02;25 And for the past 15 years I've been with the system and the program and because I really like its public health mission and I'm also very drawn to the dedication of FDA, our partners and my colleagues to make this a successful program. Well, so now here you are, a principal investigator. What exactly is the Sentinel Operations Center? What's what's the mission there and what part do you specifically play in it?   00;03;02;27 - 00;03;52;26 Sentinel is a pretty unique system because it is a congressionally mandated system. So the Congress passed what is called the FDA Amendments Act in 2007. And within that FDA, the Congress asked FDA to create a new program to complement FDA existing systems to monitor medical product safety and more specifically, the Congress, US FDA, to create a post-market risk identification and analysis system that will be using data from multiple sources that will cover at least 1 million lives to to look at the safety of medical products after they are approved and marketed.   00;03;52;28 - 00;04;33;07 So in response to this congressional mandate, FDA launched what is called a Sentinel initiative in 2008 and in 2009 as I mentioned, FDA issued its request for proposal to launch the Mini Sentinel Pilot program, and the program grew into the sentinel system that we have today. So it's for my involvement. It sort of grew over time. So when I joined, as I mentioned, we were responding to this request for a proposal and we were very lucky to be awarded the contract.   00;04;33;09 - 00;05;04;05 So when it was starting, I serve as a one of the many epidemiologists on the team and I led several studies and I gradually took on more leadership responsibility and became the principal investigator of the Sentinel Operations Center in 2022. So I've been very fortunate to have a team of very professional and very dedicated colleagues within the operations center.   00;05;04;05 - 00;05;27;26 So on a day to day basis, we work with FDA to make sure that we can help them answer the questions they would like to get addressed. And we also work with our partners to make sure that they have the resources that they need to answer the questions for FDA. And most of the time I'm just the cheerleader in chief just to share my colleagues and our collaborators.   00;05;27;28 - 00;06;11;23 Now that's great. And and then specifically, there's the Mosaic NLP project that you're involved with. What is that trying to achieve and what are the collaborations being leveraged to get that done? So Sentinel Systems has always had access to medical claims data and electronic health record data or year data. One of the main goals for the current sentinel system is to incorporate even more data, both structured and unstructured, into the sentinel system and to combine it with advanced analytic methods so that FDA can answer even more regulatory questions.   00;06;11;25 - 00;06;40;09 So the Mosaic and NLP project was one of the projects that FDA funded to accomplish this goal. So the main goal of this project is to demonstrate how billing claims and data from multiple sources when combined with advanced machine learning and natural language processing methods, could be used to extract useful information from unstructured clinical data to perform a more robust drug safety assessment.   00;06;40;11 - 00;07;21;18 When we tried to launch this project, we decided that we would issue our own request for proposal. So there was an open and competitive process, and Oracle, together with their collaborators, were selected to lead this project. So I want to talk in broad or general terms right now about data sharing, the standards and practices around that. It kind of feels silly for anyone to say it's not needed, that we can get a comprehensive view and analysis of diseases and how they're impacting the population without it.   00;07;21;20 - 00;07;46;15 NIH is on board. It updated the DMS policy to promote data sharing. You know, the FDA obviously is leaning into this. So is data sharing now happening and advancing research as expected, or are there still hang ups? So I think we are making good progress. So I think the good news is data are just being accrued at an unprecedented rate.   00;07;46;17 - 00;08;28;21 So there are just so much data now for us to potentially access and analyze. There's always this concern about proper safeguard of individual privacy. And through our work, we also became very appreciative of other considerations, for example, the fishery responsibilities of the delivery systems and payers to protect patient data and make sure that they are used properly. So you mentioned the recent changes, including in data management, ensuring policy, which I think are moving us in the right direction.   00;08;28;26 - 00;08;56;23 But if you look closer at the NIH policy, it makes special considerations for proprietary data. So I would say that we have made some progress, but access to proprietary data remains very challenging. And the FDA, the NIH policy doesn't actually fully resolve that yet. When you think about the people who do make that argument for limited data sharing, they do mostly talk about what you just said about patient privacy.   00;08;56;23 - 00;09;25;20 IT proprietary data. Pharma is especially sensitive to that, I would imagine. So how do we incentivize the reluctant how can we ease their risks and concerns or can we? Yeah, it's a tough question. I think that this require a multi-pronged approach and I can only comment on some aspects of this. So I would say that at least based on our experience, the willingness or ability to share data often depends on the purpose.   00;09;25;23 - 00;09;55;29 That is, why do we need the data? Many data partners participate in Sentinel because of its public health mission, and our consideration is how would the data be used again, Is there proper safeguard of patient privacy and institutional interest? There are other ways to share data. For example, instead of asking the data to come to us, we can send analysis to where the data is.   00;09;56;06 - 00;10;34;22 And that is actually the principle follow by federated system like Sentinel. So we don't pull the data centrally. We send an analysis to the data partners and only get back what we need it. And it's usually in the summary level format. So that actually encourages more data sharing instead of less sharing. I would say that recent advances in some domains, such as tokenization and encryption, might also reduce some concern about a data sharing, a patient privacy concerns in academic settings.   00;10;34;29 - 00;11;24;26 We've been talking a lot about days, for example, for individual who collect the data and the people I propose to offer them authorship or proper acknowledgment if they are willing to share their data. But that is not sufficient in many cases outside of academic settings. If you look at what is happening in the past ten years or so, there are now a lot of what people call data aggregators that are able to bring together data from multiple delivery systems or health plans, and they seem to be able to develop a pretty effective model to convince the data provider to share that data in some way.   00;11;24;29 - 00;11;55;28 And a way to do that could be to help these data providers to manage their data more efficiently or to help them identify ind

How do clinical research funders operate? Why do patient-centered outcomes matter so much and improve the quality of research? And how is patient-led research being applied to clinical care? We will learn all that and more in this episode of Research in Action with Greg Martin, Chief Officer for Engagement, Dissemination, and Implementation at the Patient-Centered Outcomes Research Institute (PCORI).   www.oracle.com/health www.oracle.com/life  www.pcori.org/   --------------------------------------------------------   Episode Transcript:   00;00;00;00 - 00;00;21;14 How do clinical research funders operate? Why do patient centered outcomes matter so much and improve the quality of research? And how is patient led research being applied to clinical care? We'll find all that out and more on this episode of Research in Action.   00;00;21;16 - 00;00;45;16 Hello and welcome to Research in Action, brought to you by Oracle Life Sciences. I'm Mike Stiles and today our guest is Greg Martin, chief officer for engagement, dissemination and implementation at the Patient Centered Outcomes Research Institute, referred to as PCORI. Greg's been with the organization 12 years or so, and prior to that spent time as manager of State government affairs for the American Academy of Family Physicians.   00;00;45;19 - 00;01;05;09 And we're going to be talking about no big surprise here, patient centered outcomes. So, Greg, we really appreciate you being with us. Well, thank you, Mike. It's a real pleasure and an honor to be here with you. I've listened to some of the podcasts and greatly benefited from the insights and the advice that you're bringing to folks through this, through this series.   00;01;05;09 - 00;01;23;29 So really just a real pleasure to be a part of it. Yeah, the show is really picking up steam and audience and getting some legs under it. All right. I guess let's start off by just having you describe your specific role at PCORI. What's your primary goal every day? And kind of also tell us about the overall purpose of PCORI.   00;01;24;02 - 00;01;46;12 Yeah, that's a great question. You know, and I always kind of joke around with folks that, you know, my mom does the classic two Bobs question from office space here. Remember that movie when I asked you about my job? What what exactly, son, would you say it is that a chief officer for engagement, dissemination and implementation does and it's a limited it's an uncommon title.   00;01;46;12 - 00;02;15;27 But the way I simplify it is that, you know, I get to work with a great team that is focused every day on how it is that people can be involved in the work that PCORI does as a funder, how they can be involved in the work that PCORI has funded and also how they can use in their everyday lives the evidence that property is funded and that last bit they're around evidence that that's why we're here.   00;02;15;28 - 00;02;57;06 PCORI is a clinical research funder. We were authorized by Congress. And interestingly though, even though we were authorized by Congress, we are an independent nonprofit and we're solely federally funded to do one thing, really, which is to fund patient centered comparative clinical effectiveness research or C.R. for short and C.R. as a specific type of research that's looking at intervention and approaches to health and care that are common in practice in the US health care system that stacks those interventions are approaches up against each other to really try and figure out what works best for whom.   00;02;57;08 - 00;03;19;14 But that patient centricity part in our name we take very seriously and we apply that to the C.R. We fund because it's not just about what works best for whom. It's about what works best for home according to their preferences. And that's where you get to the patient centricity. We all want to be healthy. We all want to live well, but we also want to do it in our own way.   00;03;19;14 - 00;03;48;06 We have slightly different definitions and that gets to that, that personalization of care, where we want to understand, given the options, what what should I reasonably expect will happen to me or what can I reasonably expect may come out of this for my loved one? That's the Cory Sweet spot. That's where we sit. And so I work with a great team that finds ways for people to be involved in that work, both again, what we're doing as a funder and the work that we fund.   00;03;48;09 - 00;04;12;23 Where does your passion for this work come from? Was there something you saw long ago in your work at the Academy of Family Physicians that kind of grew your interest in patient centered outcomes and how important that is? Yeah, that that's a great question, Mike. You know, and it's not something that's born from any single source. You know, I think all of us bring different lenses, different perspectives, different experiences to the table.   00;04;12;23 - 00;04;50;07 And one of the reasons why I'm so honored to have this job with PCORI is the fact that we recognize that and we in a way celebrate that and experiences that brought me to this to this point include, you know, that time working for American Academy of Family Physicians. It was a great time with them thinking through and working on issues related to the primary care workforce, health system delivery, health system design, how we pay for health care, how we pay for the myriad of services that make a difference in people's lives.   00;04;50;09 - 00;05;16;14 Prior to that, I've been with the National Conference of State Legislatures and working with state legislators and legislative staff of all stripes, thinking through how it is that we design and arrange systems of care to meet the needs of the people. And then that's the professional lens. But also, candidly, on the on the personal side, we all approach health care as patients, as families, as carers for people.   00;05;16;14 - 00;05;47;17 And we see and we live and we experience the multitude of ways in which our system works or does not. And we see the ways in which questions that we have those dilemmas around the decisions that we're faced with in our health and care and our families. Health and care have answers or don't. Those are the things that really drive me every day when I wake up and I think, okay, how can we advance the ball just a little bit to make life a little bit better for the next person?   00;05;47;19 - 00;06;07;27 Yeah, there's no one that doesn't touch and there's no one who's not affected by the system, the success of it or the shortcomings of it, whichever those may be. But research and especially research that involves the general public, that's not easy. What what does bakery do to create and foster engagement with patients and communities that really work and that matter?   00;06;07;29 - 00;06;41;00 It's no one simple answer. You know, we tend to think of it in terms of recognizing and appreciating the different contexts in which people exist and thinking through, okay, how is it that we can create an approach to engaging individuals from this community or this community itself in a way that's humble, responsive, resonant with the way in which they live their lives and they experience care.   00;06;41;02 - 00;07;14;20 And we also think about it in terms of a few different domains of activities that we can pursue that can foster an environment or an ecosystem where we can start breaking down these silos and breaking down these barriers that may have traditionally existed between research and community, between patients and investigators, between all other members of the health sector payers, insurers, employers, purchasers of care, clinicians of all stripes, hospitals and health systems, etc..   00;07;14;22 - 00;07;46;04 So as we've figured out the array of different tools that we should have at our disposal at the quarry and that we encourage others to develop, we want them into some some domains, some buckets, one of which is you've got to fund the practice of engagement. You know, engagement does require resources. When we first set out at the quarry over a decade ago, we heard clearly from investigators, traditional researchers and enthusiasm for getting closer to community.   00;07;46;04 - 00;08;18;17 But we heard clearly that they didn't have support through their institution and that our requirements may be some sort of unfunded mandate. We also heard clearly from patients and communities a likewise enthusiasm and a likewise concern that they didn't have structural support for their engagement and research. And so you've got to you've got to think about how it is that you are going to resource financially the venues, the forums, etc., for communities to come together with investigators.   00;08;18;19 - 00;08;46;24 You've also got to think through what are the facilitators for driving meaningful and effective engagement. So that's creating different tools and resources. And PCORI has many of these available on our website that we encourage others to use. But also as you look at these, you'll see that many of them are community generated themselves. Sometimes the best and most durable solutions are those that bubble up from the participants themselves.   00;08;46;26 - 00;09;12;04 There's also another domain of work that is really this notion of convening that you really need to think through how it is. We can bring people together because there's no substitution for the human touch, there's no substitution for human interaction and thinking through what are the different modalities that we can support people in bridging diverse perspectives in a complex space.   00;09;12;06 - 00;09;44;12 How can we help them see where it is that they may be using different language to say the same thing or the same language to mean different things? Quite common for us to all just talk past each other when we're really driving towards the same goal, but then also thinking through and this is where we've don

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   -------------------------------------------------------   Episode Transcript:   00;00;00;02 - 00;00;27;22 What makes multidisciplinary collaboration the key to health care innovation? What is the effect of bundled, integrated solutions on the patient experience and how can we invest in what matters most while streamlining the entire process? We'll find all that out and more on Research in Action. Hello and welcome to Research in Action, brought to you by Oracle Life Sciences.   00;00;27;22 - 00;00;52;08 I'm Mike Stiles. And today our very special guest is Frank Bateman, a digital health data and technology executive. He's currently a senior health IT advisor and was a former chief information officer of the U.S. Department of Health and Human Services. Oracle Life Sciences has an e-book on the next phase of growth for the Life Sciences industry, and Frank was a really valuable resource for that.   00;00;52;08 - 00;01;22;00 He's got a lot of great thoughts on how pharma and biotech are investing in tech to support things like personalized medicine, improved clinical trials and drug safety tracking. That's why we wanted to get him on the podcast. So Frank, thanks so much for joining us. Thanks. It's great to be here, Mike. We appreciate it. Well, we got a lot of ground to cover, but I know you went into corporate strategy in the beginning of your career and through the bulk of your career, but obviously somewhere down the line you started crossing paths with government.   00;01;22;00 - 00;01;42;04 So what did that involve? How did that happen? Well, I've been lucky enough to pursue my interests wherever they took me. I hadn't expected to pursue a career in the life sciences and health care when I started out focused on nuclear arms control. But my interest in technology actually came about from my work on verification measures for a nuclear test ban.   00;01;42;21 - 00;02;09;05 Technology first took me to IBM Research and then under IBM corporate strategy, as you mentioned, when in in corporate, I oversaw the company's ten year outlook. And as a tech company, we saw high performance computing in the life sciences staring us in the face. We needed to be in it. And our chairman at the time, Lou Gerstner, accepted a recommendation that we invest 100 million to launch a business unit focused on the life sciences.   00;02;09;19 - 00;02;36;24 So I love the idea. You were actually serving in the Obama administration. White House Entrepreneur in residence. I love the idea of an entrepreneur in residence because one doesn't quickly equate government with speed, original ideas and innovation. Were you impressed by or frustrated by the speed at which you could bring things to full fruition in government? Impressed? Absolutely frustrated.   00;02;37;00 - 00;03;04;25 Yeah. Our times sometimes there are arcane processes that get in the way of novel solutions, but I always thought that had great admiration for the dedicated dedication the mission demonstrated by civil servants. Doing things differently was really a hallmark of the Obama administration. It wasn't just the Entrepreneur in Residence program you mentioned. Obama appointed the nation's first chief technology officer, the first chief information officer.   00;03;05;06 - 00;03;31;08 He launched the US Digital Service to provide agencies with a different approach to software development. He created challenge that guards as a means for agencies to seek innovations by awarding modest prizes as opposed to large government contracts. It brought new voices to light. I look at our current government a lot, like most governments, it's inherited its structure from the industrial age.   00;03;31;18 - 00;03;58;12 For the most part, it's organized by industry, by vertical. There's an Agriculture Department, energy, health, defense and so on. The congressional appropriations process is what exacerbates the problem in this information age. I really believe that Multi-disc culinary collaboration is what brings about solutions. And I don't have a background in biochemistry, but I worked with biochemists to explore therapies that made effective use in both of our disciplines.   00;03;58;25 - 00;04;23;21 If you think of Tesla for a moment, the company has innovations, it has inventions. But its real success was that of an integrator. It brought together knowhow from battery management, aerodynamics, automobile engineering, software development and legacy. Automakers had been working on these problems in building an EV for years, but their approach failed to deliver a car with mass market appeal.   00;04;24;00 - 00;04;47;06 And I think that's precisely what we need to do in the life sciences now, is bring the disciplines together and organize to solve problems. Now, I think the listeners are starting to see why you're such a fascinating person to have on the show. You've been exposed at high levels to nearly every component of health care, and through most of that you were tasked with being really a futurist and a trend spotter in it.   00;04;47;06 - 00;05;08;17 So just keep my head straight. I'm going to cover things with you in buckets now. The first being what the challenges and opportunities really are in life sciences. Fun fact for our listeners can bring up at their next dinner party. When things get dull, it takes about $2 billion and 10 to 15 years to get a drug to market.   00;05;08;17 - 00;05;30;27 Now, for most people who have gotten used to rapid advancement, getting things they want and need on demand, that sounds absolutely crazy. So can technology kind of change this equation soon? Mike I don't think that's crazy at all, and I really believe that we're on the cusp of change. One of the startups that I worked with, Empower Medicine, is a really great example.   00;05;31;11 - 00;06;04;00 What they're trying to achieve is a complex endeavor. It depends upon bringing together people from different disciplines to work across the universe of stakeholders. And going back to the Tesla example, GM and Ford built highly structured teams in engineering designed propulsion. But Tesla was a software company from the start. So I think the challenge is how do you, as a life sciences company, mimic what Tesla did to bring together the disciplines and focus on the entire process of drug development?   00;06;04;14 - 00;06;33;17 It's almost like if technology isn't the answer, what is? For instance, it's the only way really to capture the volume and sources of adverse events, right? We always look at adverse events and drug discovery thanks to that observation. Technology can do wonders, but it isn't nirvana. I it does great things, but I think it's always important to remember in health care there needs to be a human touch because health care at its core is about people.   00;06;33;28 - 00;07;02;27 Technology is already making waves in clinical trials and there's so much more to come. We're on the early stages witnessing that impact. Things like electronic patient reported outcomes and various sensors are beginning to gather data from patients during trials and during real world use. And this technology facilitates the capture of adverse events actively and passively, leading to just a wealth of data and deeper understanding of therapeutic effects.   00;07;03;19 - 00;07;31;23 This could uncover unexpected drug interactions or shed light and personalize or genomic attributes. Sometimes, though, adverse events are not obvious. And that's that's really another role that technology can play because of its ability to capture so much data, it may find unexpected things to match what's going on in the market. Actually, Oracle just merged its health care and Life sciences organization late last year.   00;07;31;23 - 00;07;55;24 Why do you think those two things are coming together? I know you talk about bringing things together and that's just like one example of it. Yeah, I think that's a really great example. I like to think of health as being all encompassing. The life sciences exist to support health. The same could be said for payors, providers, physicians, health systems, pharmacies, patients, Cros, even employers.   00;07;56;09 - 00;08;24;11 Each has their role to play. The vast majority of companies across the health sector have a mission or model that says something like Patients are the reason we're in business. Well, I'm not questioning it. In fact, I'm pretty confident people are involved, they're sincere. But if serving patients is your mission, I'd ask, when was the last time you took a look at your organization to see if it is optimally designed to address the needs of patients in this information age?   00;08;24;28 - 00;08;54;23 We know that siloed organizations underperform multiple disciplines and experiences are not considered. Information isn't shared in much. The way I spoke about HHS is being a reflection of the health sector by having a research component, by having a regulatory component, by having a provider component. I think that those companies that integrate health disciplines need to step out of their comfort zone in the same way that Oracle combined those pieces.   00;08;55;07 - 00;09;24;18 Now put I want to put that futurist hat on and tell us which innovations you think are going to have the most profound impact. On average, Mike's like me and say the next decade, What do you see coming? So I think it's importa

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    --------------------------------------------------------   Episode Transcript:   00;00;00;02 - 00;00;27;22 What makes multidisciplinary collaboration the key to health care innovation? What is the effect of bundled, integrated solutions on the patient experience and how can we invest in what matters most while streamlining the entire process? We'll find all that out 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;27;22 - 00;00;52;08 I'm Mike Stiles. And today our very special guest is Frank Bateman, a digital health data and technology executive. He's currently a senior advisor to Oakland's De Silva and Phillips and was a former chief information officer of the U.S. Department of Health and Human Services. Oracle Life Sciences has an e-book coming on the next phase of growth for the Life Sciences industry, and Frank was a really valuable resource for that.   00;00;52;08 - 00;01;22;00 He's got a lot of great thoughts on how pharma and biotech are investing in tech to support things like personalized medicine, improved clinical trials and drug safety tracking. That's why we wanted to get him on the podcast. So Frank, thanks so much for joining us. Thanks. It's great to be here, Mike. We appreciate it. Well, we got a lot of ground to cover, but I know you went into corporate strategy in the beginning of your career and through the bulk of your career, but obviously somewhere down the line you started crossing paths with government.   00;01;22;00 - 00;01;42;04 So what did that involve? How did that happen? Well, I've been lucky enough to pursue my interests wherever they took me. I hadn't expected to pursue a career in the life sciences and health care when I started out focused on nuclear arms control. But my interest in technology actually came about from my work on verification measures for a nuclear test ban.   00;01;42;21 - 00;02;09;05 Technology first took me to IBM Research and then under IBM corporate strategy, as you mentioned, when in in corporate, I oversaw the company's ten year outlook. And as a tech company, we saw high performance computing in the life sciences staring us in the face. We needed to be in it. And our chairman at the time, Lou Gerstner, accepted a recommendation that we invest 100 million to launch a business unit focused on the life sciences.   00;02;09;19 - 00;02;36;24 So I love the idea. You were actually serving in the Obama administration. White House Entrepreneur in residence. I love the idea of an entrepreneur in residence because one doesn't quickly equate government with speed, original ideas and innovation. Were you impressed by or frustrated by the speed at which you could bring things to full fruition in government? Impressed? Absolutely frustrated.   00;02;37;00 - 00;03;04;25 Yeah. Our times sometimes there are arcane processes that get in the way of novel solutions, but I always thought that had great admiration for the dedicated dedication the mission demonstrated by civil servants. Doing things differently was really a hallmark of the Obama administration. It wasn't just the Entrepreneur in Residence program you mentioned. Obama appointed the nation's first chief technology officer, the first chief information officer.   00;03;05;06 - 00;03;31;08 He launched the US Digital Service to provide agencies with a different approach to software development. He created challenge that guards as a means for agencies to seek innovations by awarding modest prizes as opposed to large government contracts. It brought new voices to light. I look at our current government a lot, like most governments, it's inherited its structure from the industrial age.   00;03;31;18 - 00;03;58;12 For the most part, it's organized by industry, by vertical. There's an Agriculture Department, energy, health, defense and so on. The congressional appropriations process is what exacerbates the problem in this information age. I really believe that Multi-disc culinary collaboration is what brings about solutions. And I don't have a background in biochemistry, but I worked with biochemists to explore therapies that made effective use in both of our disciplines.   00;03;58;25 - 00;04;23;21 If you think of Tesla for a moment, the company has innovations, it has inventions. But its real success was that of an integrator. It brought together knowhow from battery management, aerodynamics, automobile engineering, software development and legacy. Automakers had been working on these problems in building an EV for years, but their approach failed to deliver a car with mass market appeal.   00;04;24;00 - 00;04;47;06 And I think that's precisely what we need to do in the life sciences now, is bring the disciplines together and organize to solve problems. Now, I think the listeners are starting to see why you're such a fascinating person to have on the show. You've been exposed at high levels to nearly every component of health care, and through most of that you were tasked with being really a futurist and a trend spotter in it.   00;04;47;06 - 00;05;08;17 So just keep my head straight. I'm going to cover things with you in buckets now. The first being what the challenges and opportunities really are in life sciences. Fun fact for our listeners can bring up at their next dinner party. When things get dull, it takes about $2 billion and 10 to 15 years to get a drug to market.   00;05;08;17 - 00;05;30;27 Now, for most people who have gotten used to rapid advancement, getting things they want and need on demand, that sounds absolutely crazy. So can technology kind of change this equation soon? Mike I don't think that's crazy at all, and I really believe that we're on the cusp of change. One of the startups that I worked with, Empower Medicine, is a really great example.   00;05;31;11 - 00;06;04;00 What they're trying to achieve is a complex endeavor. It depends upon bringing together people from different disciplines to work across the universe of stakeholders. And going back to the Tesla example, GM and Ford built highly structured teams in engineering designed propulsion. But Tesla was a software company from the start. So I think the challenge is how do you, as a life sciences company, mimic what Tesla did to bring together the disciplines and focus on the entire process of drug development?   00;06;04;14 - 00;06;33;17 It's almost like if technology isn't the answer, what is? For instance, it's the only way really to capture the volume and sources of adverse events, right? We always look at adverse events and drug discovery thanks to that observation. Technology can do wonders, but it isn't nirvana. I it does great things, but I think it's always important to remember in health care there needs to be a human touch because health care at its core is about people.   00;06;33;28 - 00;07;02;27 Technology is already making waves in clinical trials and there's so much more to come. We're on the early stages witnessing that impact. Things like electronic patient reported outcomes and various sensors are beginning to gather data from patients during trials and during real world use. And this technology facilitates the capture of adverse events actively and passively, leading to just a wealth of data and deeper understanding of therapeutic effects.   00;07;03;19 - 00;07;31;23 This could uncover unexpected drug interactions or shed light and personalize or genomic attributes. Sometimes, though, adverse events are not obvious. And that's that's really another role that technology can play because of its ability to capture so much data, it may find unexpected things to match what's going on in the market. Actually, Oracle just merged its health care and Life sciences organization late last year.   00;07;31;23 - 00;07;55;24 Why do you think those two things are coming together? I know you talk about bringing things together and that's just like one example of it. Yeah, I think that's a really great example. I like to think of health as being all encompassing. The life sciences exist to support health. The same could be said for payors, providers, physicians, health systems, pharmacies, patients, Cros, even employers.   00;07;56;09 - 00;08;24;11 Each has their role to play. The vast majority of companies across the health sector have a mission or model that says something like Patients are the reason we're in business. Well, I'm not questioning it. In fact, I'm pretty confident people are involved, they're sincere. But if serving patients is your mission, I'd ask, when was the last time you took a look at your organization to see if it is optimally designed to address the needs of patients in this information age?   00;08;24;28 - 00;08;54;23 We know that siloed organizations underperform multiple disciplines and experiences are not considered. Information isn't shared in much. The way I spoke about HHS is being a reflection of the health sector by having a research component, by having a regulatory component, by having a provider component. I think that those companies that integrate health disciplines need to step out of their comfort zone in the same way that Oracle combined those pieces.   00;08;55;07 - 00;09;24;18 Now put I want to put that futurist hat on and tell us which innovations you think are going to have the most profound impact. On average, Mike's like me and say the next decade, What do you see coming? So I think it's important to have a framework to think about this. And and I've begun to craft a mind map to ident