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Over the past decade, the healthcare industry has undergone a series of technological changes in an effort to modernize it and bring it into the digital world, but the call for innovation persists. One person answering that call is Dr. Peter Lee (opens in new tab)<\/span><\/a>, Corporate Vice President of Microsoft Healthcare, a new organization dedicated to accelerating healthcare innovation through AI and cloud computing.<\/p>\n Today, Dr. Lee talks about how MSR\u2019s advances in healthcare technology are impacting the business of Microsoft Healthcare. He also explains how promising innovations like precision medicine, conversational chatbots and Azure\u2019s API for data interoperability may make healthcare better and more efficient in the future.<\/p>\n Peter Lee:\u00a0In tech industry terms, you know, if the last decade was about digitizing healthcare, the next decade is about making all that digital data good for something,\u00a0and that good for something is going to depend on data flowing where it needs to flow at the right time.<\/p>\n Host:\u00a0<\/b>You\u2019re listening to the Microsoft Research Podcast, a show that brings you closer to the cutting-edge of technology research and the scientists behind it. I\u2019m your host, Gretchen Huizinga.<\/b><\/p>\n Host:\u00a0<\/b>Over the past decade, the healthcare industry has undergone a series of technological changes in an effort to modernize it and bring it into the digital world, but the call for innovation persists. One person answering that call is Dr. Peter Lee, Corporate Vice President of Microsoft Healthcare,\u00a0<\/b>a new organization dedicated to accelerating healthcare innovation through AI and cloud computing<\/b>.<\/b><\/p>\n Today, Dr. Lee talks about how MSR\u2019s advances in healthcare technology are impacting the business of Microsoft Healthcare. He also explains how promising innovations like precision medicine, conversational chatbots and Azure\u2019s API for data interoperability may make healthcare better and more efficient in the future.<\/b>\u00a0<\/b>That and much more on this episode of the Microsoft Research Podcast.<\/b><\/p>\n (music plays)<\/i><\/b><\/p>\n Host: Peter Lee, welcome to the podcast<\/b>!<\/b><\/p>\n Peter Lee: Thank you. It\u2019s great to be here.<\/p>\n Host: So you\u2019re a Microsoft Corporate Vice President and head of a relatively new organization here called Microsoft Healthcare. Let\u2019s start by situating that within the larger scope of Microsoft Research and Microsoft writ large. What is Microsoft Healthcare, why was it formed<\/b>,<\/b>\u00a0and what do you hope to do with it?<\/b><\/p>\n Peter Lee: It\u2019s such a great question because when,\u00a0we were first asked to take this on, it was confusing to me! Healthcare is such a gigantic business in Microsoft. You know, the number that really gets me is,\u00a0Microsoft has commercial contracts with almost 169,000 healthcare organizations around the world.<\/p>\n Host: Wow.<\/b><\/p>\n Peter Lee: I mean, it\u2019s just massive. Basically, anything from a one-nurse clinic in Nairobi, Kenya, to Kaiser Permanente or United Healthcare,\u00a0and everything in-between. And so\u00a0it was confusing to try to understand,\u00a0what is Satya Nadella thinking to ask a \u201cresearch-y\u201d organization\u00a0to take this on?\u00a0But, you know, the future\u00a0of\u00a0healthcare is so vibrant and dynamic right now,\u00a0and is so dependent on AI, on Cloud computing, big data, I think he was really wanting us to think about that future.<\/p>\n Host: Let\u2019s situate you.<\/b><\/p>\n Peter Lee: Okay.<\/p>\n Host: You cross a lot of boundaries from pure to applied research, computer science to medicine. You\u2019ve been head of Carnegie Mellon University\u2019s computer science department, but you were also an office director at DARPA, which is the poster child for applied research. You\u2019re an ACM fellow and on the board of directors of the Allen Institute for AI, but you\u2019re also a member of the National Academy of Medicine, fairly newly minted as I understand?<\/b><\/p>\n Peter Lee: Right, just this year.<\/p>\n Host: And on the board of Kaiser Permanente\u2019s School of Medicine. So, I\u2019d ask you what gets you up in the morning, but it seems like you never go to bed<\/b>\u2026<\/b>\u00a0So instead, describe what you do for a living, Peter<\/b>!<\/b>\u00a0How you choose what hat to wear in the morning and what\u2019s a typical day in your life look like?<\/b><\/p>\n Peter Lee: Well, you know, this was never my plan. I just love research, and\u00a0thinking hard about problems, being around other smart people and thinking hard about problems, getting real depth of understanding. That\u2019s what gets me up. But I think the world today, what\u2019s so exciting about it for anyone with the research gene,\u00a0is that research, in a variety of areas, has become so important to practical, everyday life. It\u2019s become important to Microsoft\u2019s business. Not just Microsoft, but all of our competitors.\u00a0And so I just feel like I\u2019m in a lucky position,\u00a0as well as a lot of my colleagues, I don\u2019t think any of us started with that idea. We just wanted to do research and now we\u2019re finding ourselves sort of in the middle of things.<\/p>\n Host: Right. Well, talk a little bit more about computer science and medicine. How have you moved from one to the other<\/b>,<\/b>\u00a0and how do you kind of envision yourself in this arena?<\/b><\/p>\n Peter Lee: Well, my joke here is, these were changes that,\u00a0actually,\u00a0Satya Nadella forced me to make! And it\u2019s a little bit of a joke because I was actually honored that he would think of me this way,\u00a0but it was also painful because I was in a comfort zone just doing my own research, leading research teams, and then, you know, Satya Nadella becomes the CEO, Harry Shum comes on board to drive innovation,\u00a0and I get asked to think about new ways to take research ideas and get them out into the world.\u00a0And then,\u00a0three years after that, I get asked to think about the same thing for healthcare. And each one of those,\u00a0to\u00a0my mind, are examples of this concept that Satya Nadella likes to talk about, \u201cgrowth mindset.\u201d I joke that growth mindset is actually a euphemism because each time you\u2019re asked to make these changes, you just get this feeling of\u00a0dread. You might have a minute where you\u2019re feeling honored that someone would ask you something, but then\u2026<\/p>\n Host: Oh, no<\/b>!<\/b>\u00a0I\u2019ve got to do it now!<\/b><\/p>\n Peter Lee:\u00a0\u2026and boy, I was, you know, on a roll in what I was doing before, and you do spend some time feeling sorry for yourself\u2026\u00a0but when you work through those moments, you find that you do have those periods in your life where you grow a lot. And\u00a0my immersion with so many great people in healthcare over the last three or four years has been one of those big growth periods.\u00a0And to be recognized, then, let\u2019s say,\u00a0by the National Academies\u00a0is sort of validation of that.<\/p>\n Host: All right, so rewind just a little bit and talk about that space you were in just before you got into the healthcare situation. You were doing Microsoft Research. Where, on the spectrum from pure, like your Carnegie Mellon roots, to applied, like your DARPA roots, did that land? There\u2019s an organization called NExT here I think, yeah?<\/b><\/p>\n Peter Lee: That\u2019s right. You know, when I was in academia, academia really knows how to do research.<\/p>\n Host: Yeah.<\/b><\/p>\n Peter Lee: And they really put the creatives, the graduate students and the faculty,\u00a0at the top of the pyramid,\u00a0socially,\u00a0in the university. It\u2019s just a great setup.\u00a0And it\u2019s organized into departments, which are each named after a research area or a discipline and within the departments there are groups of people organized by sub-discipline or area,\u00a0and so it\u2019s an organizing principle that\u2019s tried and true. When I went to DARPA, it was completely different. The departments aren\u2019t organized by research area,\u00a0they\u2019re organized by mission,\u00a0some easily\u00a0assessable\u00a0goal or\u00a0objective.\u00a0You can always answer the question, have we accomplished it yet\u00a0or not?<\/p>\n Host: Right.<\/b><\/p>\n Peter Lee: And so research at DARPA is organized around those missions and that was a big learning experience for me. It\u2019s not like saying we\u2019re going to do computer vision research. We\u2019ll be doing that for the next fifty years. It\u2019s,\u00a0can we eliminate the language barrier for all internet-connected people? That\u2019s a mission. You can answer the question, you know, how close are we?<\/p>\n Host: Right.<\/b><\/p>\n Peter Lee: And so the mix between those two modes of research, from academia to DARPA, is something that I took with me when I joined Microsoft Research and, you know, Microsoft Research has some mix, but I thought the balance could be slightly different. And then, when Satya Nadella became the CEO and Harry Shum took over our division, they challenged me to go bigger on that idea and that\u2019s how NExT started. NExT tried to organize itself by missions and it tried to take passionate people and brilliant ideas and grow them into new lines of business, new engineering capabilities for Microsoft, and along the way, create new CVPs and TFs for our company. There\u2019s a tension here because one of the things that\u2019s so important for great research is stability. And so when you organize things like you do in academia, and in large parts of Microsoft Research, you get that stability by having groups of people devoted to an area. We have, for example, say, computer networking research groups that are best in the world.<\/p>\n Host: Right.<\/b><\/p>\n Peter Lee: And they\u2019ve been stable for a long time and, you know, they just create more and more knowledge and depth, and that stability is just so important. You\u00a0feel like you can take big risks when you have that stability. When you are mission-oriented,\u00a0like in NExT, these missions are coming and going all the time. So that has to be managed carefully, but the other benefit of that, management-wise, is more people get a chance to step up and express their leadership. So it\u2019s not that either model is superior to the other, but it\u2019s good to have both.\u00a0And when you\u2019re in a company with all the resources that Microsoft has, we really should have both.<\/p>\n Host: Well, let\u2019s zoom out and talk<\/b>,<\/b>\u00a0somewhat generally<\/b>,<\/b>\u00a0about the promise of AI because that\u2019s where we\u2019re going to land on some of the more specific things we\u2019ll talk about in a bit, but Microsoft has several initiatives under a larger umbrella called AI\u00a0<\/b>for<\/b>\u00a0Good and the aim is to bring the power of AI to societal-scale problems in things like agriculture, broadband accessibility, education, environment and<\/b>,<\/b>\u00a0of course, medicine. So AI for Health is one of these initiatives, but it\u2019s not the same thing as Microsoft Healthcare, right?<\/b><\/p>\n Peter Lee:\u00a0Well, the whole AI for Good program is so exciting and I\u2019m just so proud to be in a company that makes this kind of commitment. You can think of it as a philanthropic grants program and it is,\u00a0in fact,\u00a0in all of these areas,\u00a0providing funding and technical support to really worthy teams, passionate people, really trying to bring AI to bear for the greater good.<\/p>\n Host: Mm-hmm.<\/b><\/p>\n Peter Lee: But it\u2019s also the case that we devote our own research resources to these things. So it\u2019s not just giving out grants, but it\u2019s actually getting into collaborations. What\u2019s interesting about AI for Health is that it\u2019s the first pillar in the AI for Good program that actually overlaps with a business at Microsoft and that\u2019s Microsoft Healthcare.\u00a0One way that I think about it is, it\u2019s an outlet for researchers to think about, what could AI do to advance medicine? When you talk to a lot of researchers\u00a0in\u00a0computer science departments,\u00a0or across Microsoft research labs, increasingly you\u2019ll see more and more of them getting interested in healthcare and medicine and the first things that they tend to think about, if they\u2019re new to the field, are diagnostic and therapeutic applications. Can we come up with something that will detect ovarian cancer earlier?\u00a0Can we come up with new imaging techniques that will help radiologists do a better job? Those sorts of diagnostic and therapeutic applications, I think, are incredibly important for the world, but they are not Microsoft businesses. So the AI for Health program can provide an outlet for those types of research passions. And then there are also, as a secondary element, four billion people on this planet today that have no reasonable access to healthcare. AI and technology have to be part of the solution to creating that more equitable access and so that\u2019s another element that,\u00a0again, doesn\u2019t directly touch Microsoft\u2019s business today in Microsoft Healthcare, but is so important we have a lot to offer so AI for Health is just, I think, an incredibly visionary and wonderful program for that.<\/p>\n Host: Well, let\u2019s zoom back out\u2026 um, no, let\u2019s zoom back in. I\u2019ve lost track of the camera. I don\u2019t know where it is! Let\u2019s talk about the idea of precision medicine, or precision healthcare, and the dream of improving those diagnostic and therapeutic interventions with AI. Tell us what precision medicine is and how that plays out and how are the two rather culturally diverse fields of computer science and medicine coming together to solve for X here?<\/b><\/p>\n Peter Lee: Yeah, I think one of the things that is sometimes underappreciated is, over the past ten to twenty years,\u00a0there\u2019s been a massive digitization of healthcare and medicine. After the 2008 economic collapse, in 2009,\u00a0there was the ARA\u2026\u00a0there was a piece of legislation attached to that called the\u00a0HITECH\u00a0Act, and\u00a0HITECH\u00a0actually required healthcare organizations to digitize health records. And so for the past ten years,\u00a0we\u2019ve gone from something like 15% of health records being in digital form,\u00a0to today, now over 98% of health records are in digital form. And along with that, medical devices that measure you have gone digital, our ability to sequence and analyze your genome, your proteome, have gone digital and now the question is, what can we do with all the digital information?\u00a0And on top of that, we have social information.<\/p>\n Host: Yeah.<\/b><\/p>\n Peter Lee:\u00a0People are carrying mobile devices, people talk to computers at home, people\u00a0go to their Alpha XR to get their flu shots.<\/p>\n Host: Yeah.<\/b><\/p>\n Peter Lee:\u00a0And all of this is in digital form and\u00a0so the question is, can we take all of that digital data and use it to provide highly\u00a0personalized and precisely targeted diagnostics and therapeutics to people.<\/p>\n Host: Mm-<\/b>hmm<\/b>.<\/b><\/p>\n Peter Lee: Can we get a holistic, kind of, 360-degree view of you, specifically, of what\u2019s going on with you right now,\u00a0and what might go on over the next\u00a0several years,\u00a0and target your wellness? Can we advance from sick\u00a0care, which is really what we have today\u2026<\/p>\n Host: Right.<\/b><\/p>\n Peter Lee: \u2026to\u00a0healthcare.<\/p>\n Host: When a big tech company like Microsoft throws its hat in the healthcare ring and publicly says that it has the goal of \u201ctransforming how healthcare is experienced and delivered,\u201d I immediately think of the word disruption, but you\u2019ve said healthcare isn\u2019t something you disrupt. What do you mean by that, and if disruption isn\u2019t the goal, what is?<\/b><\/p>\n Peter Lee: Right.\u00a0You know, healthcare is not a normal business. Worldwide,\u00a0it\u2019s actually a\u00a0$7.5 trillion\u00a0dollar\u00a0business. And for Microsoft, it\u2019s incredibly important because,\u00a0as we were discussing, it\u2019s gone digital,\u00a0and increasingly,\u00a0that digital data, and the services and AI and computation to make good use of the data,\u00a0is moving to the cloud. So it has to be something that we pay very close attention to and we have a business priority to support that.<\/p>\n Host: Right.<\/b><\/p>\n Peter Lee: But, you know, it\u2019s not a normal business in many, many different senses. As a patient, people don\u2019t shop, at least not on price, for their healthcare. They might go on a website to look at ratings of primary care physicians, but certainly, if you\u2019re in a car accident, you\u2019re unconscious. You\u2019re not shopping.<\/p>\n Host: No.<\/b><\/p>\n Peter Lee: You\u2019re just looking for the best possible care. And similarly,\u00a0there\u2019s a massive shift for healthcare providers away from what\u2019s called fee-for-service,\u00a0and toward something called value-based care where doctors and clinics are being reimbursed based on the quality of the outcomes.\u00a0What you\u2019re trying to do is create success for those people and organizations that, let\u2019s face it, they\u2019ve devoted their lives to helping people be healthier.\u00a0And so it really is almost the purest expression of Microsoft\u2019s mission of empowerment. It\u2019s not,\u00a0how do we create a disruption that allows us to make more money, but instead, you know, how do we empower people and organizations to deliver better\u00a0\u2013\u00a0and receive better\u00a0\u2013\u00a0healthcare?\u00a0Today in the US, a primary care doctor spends almost twice as much time entering clinical documentation as they do actually taking care of patients. Some of the doctors we work with here at Microsoft call this \u201cpajama time,\u201d because you spend your day working with patients and then,\u00a0at home,\u00a0when you crawl into bed,\u00a0you have to finish up your documentation. That\u2019s a big source of burn out.<\/p>\n Host: Oh, yeah.<\/b><\/p>\n Peter Lee: And so,\u00a0what can we do, using speech recognition technologies, natural language processing,\u00a0diarization, to enable that clinical note-taking to be dramatically reduced?\u00a0You know, how would that help doctors pay more attention to their patients? There is something called\u00a0revenue-cycle management,\u00a0and it\u2019s sort of sometimes viewed as a kind of evil way to maximize revenues in a clinic or hospital system, but it is also a place where you can really try to eliminate waste. Today, in the US market, most estimates say that about a trillion dollars every year is just gone to waste in the US healthcare system. And so these are sort of data analysis problems,\u00a0in this highly complex system,\u00a0that really require the kind of AI\u00a0and\u00a0machine learning that we develop.<\/p>\n Host: And those are the kinds of disruptions we\u2019d like to see, right?<\/b><\/p>\n Peter Lee: That\u2019s right. Yeah.<\/p>\n Host: We\u2019ll call them successes, as you did.<\/b><\/p>\n Peter Lee: Well, and they are disruptions though, they\u2019re disruptions that help today\u2019s working doctors and nurses. They help today\u2019s hospital administrators.<\/p>\n (music plays)<\/i><\/b><\/p>\n Host: Let\u2019s talk about several innovations that you\u2019ve actually made to help support the healthcare industry\u2019s transformation.\u00a0<\/b>Last year \u2013<\/b>\u00a0<\/b>a\u00a0<\/b>year ago\u00a0<\/b>\u2013\u00a0<\/b>at the HIMSS conference, you talked about tools that would improve communication, the healthcare experience and interoperability and data sharing in the cloud. Tell us about these innovations. What did you envision then<\/b>,<\/b>\u00a0and now, a year later, how are they working out?<\/b><\/p>\n Peter Lee:\u00a0Yeah. Maybe the one I like to start with is about interoperability. I sometimes have joked that it\u2019s the least sexy topic, but it\u2019s the one that is,\u00a0I think,\u00a0the most important to us.\u00a0In tech industry terms,\u00a0you know,\u00a0if the last decade was about digitizing healthcare, the next decade is about making all that digital data good for something and that good for something is going to depend on data flowing where it needs to flow\u2026<\/p>\n Host: Right.<\/b><\/p>\n Peter Lee:\u00a0\u2026at the right time.\u00a0And doing that in a way that protects people\u2019s privacy because health data is very, very personal. And so a fundamental issue there is interoperability. Today, while we have all this digital data, it\u2019s really locked into thousands of different incompatible data formats. It doesn\u2019t get exposed through modern APIs or microservices. It\u2019s oftentimes siloed for\u00a0business\u00a0reasons, and so unlocking that is important.\u00a0One way that we look at it here at Microsoft is,\u00a0we are seeing a rising tidal wave of healthcare organizations starting to move to the cloud. Probably ten years from now, almost all healthcare organizations will be in the cloud. And so,\u00a0with that historic shift that will happen only once,\u00a0ever,\u00a0in human history, what can we do today to ensure that we end up in a better place ten years from now than we are now? And\u00a0interoperability is one of the keys there.\u00a0And that\u2019s something that\u2019s been recognized by multiple governments. The US government, through the Centers for Medicare and Medicaid Services,\u00a0has\u00a0proposed new regulations that require the use of specific interoperable data standards and API frameworks. And I\u2019m very proud that Microsoft has participated in helping endorse and guide the specific technical choices in those new rules.<\/p>\n Host: So what is the API that Microsoft has?<\/b><\/p>\n Peter Lee: So the data standard that we\u2019ve put a lot of effort behind is something called FHIR. F-H-I-R, Fast Healthcare Interoperability Resources. And for anyone that\u2019s used to working in the web, you can look at FHIR and you\u2019ll see something very familiar. It\u2019s a modern data standard, it\u2019s extensible,\u00a0because medical science is advancing all the time, and it\u2019s highly susceptible to analysis through machine learning.<\/p>\n Host: Okay.<\/b><\/p>\n Peter Lee: And so it\u2019s utterly modern and standardized,\u00a0and I think FHIR can be a lingua franca for all healthcare data everywhere. And so,\u00a0for Microsoft, we\u2019ve integrated FHIR as a first-class data type in our cloud, in Azure.<\/p>\n Host: Oh, okay.<\/b><\/p>\n Peter Lee: We\u2019ve enabled FHIR in Office. So the Teams application, for example, it can connect to health data for doctors and nurses. And there\u2019s integration going\u00a0on\u00a0into\u00a0Dynamics. And so it\u2019s a way to convert everything that we do here at Microsoft\u00a0into great healthcare-capable tools. And once you have FHIR in the cloud, then you also,\u00a0suddenly,\u00a0unlock all of the AI tools that we have to just enable all that precision medicine down the line.<\/p>\n Host: That\u2019s such a Biblical reference right then! The cloud and the FHIR.<\/b><\/p>\n Peter Lee: You know,\u00a0there are \u2013\u00a0there\u2019s an endless supply of bad puns around FHIR. So thank you for contributing to that.<\/p>\n Host: Well, it makes me think about the\u00a0<\/b>Fyre<\/b>\u00a0Festival, which was spelt F-Y-R-E, which was just the biggest debacle in festival history<\/b>\u2026<\/b><\/p>\n Peter Lee: I should say, by the way, another thing that everyone connected to Microsoft should be proud of is, we have really been one of the chief architects for this new future. One of the most important people in the FHIR development community is Josh\u00a0Mandel, who works with us here at Microsoft Healthcare,\u00a0and he has the title Chief Architect, but it\u2019s not Chief Architect for Microsoft, it\u2019s Chief Architect for the cloud.<\/p>\n Host: Oh, my gosh.<\/b><\/p>\n Peter Lee: So he spends time talking to the folks at Google, at AWS, at\u00a0Salesforce\u00a0and so on.<\/p>\n Host: Right.<\/b><\/p>\n Peter Lee: Because we\u2019re trying to bring the entire cloud ecosystem along to this new future.<\/p>\n Host: Tell me a little bit about what role bots\u00a0<\/b>might<\/b>\u00a0play in this arena?<\/b><\/p>\n Peter Lee: Bots are really interesting because,\u00a0how many listeners have received a lab test result and have no idea what it means?\u00a0How many people have received some weird piece of paper or bill in the mail from their insurance company? It\u2019s not just medical advice,\u00a0you know,\u00a0where you have a scratch in your throat and you\u2019re worried about what you should do. That\u2019s important too,\u00a0but the idea of bots in healthcare really span all these other things. One of the most touching,\u00a0in\u00a0a project led by\u00a0Hadas\u00a0Bitran and her team, has been in the area of clinical trials. So there\u2019s a website called clinicaltrials.gov and it contains a registry describing every registered clinical trial going on. So now, if you are desperate for more experimental care, or you\u2019re a doctor treating someone and you\u2019re desperate for this, you know, how do you find,\u00a0out of thousands of documents, and they\u2019re complicated\u2026<\/p>\n Host: Right.<\/b><\/p>\n Peter Lee: \u2026technical, medical, science things.<\/p>\n Host: Jargon-y.<\/b><\/p>\n Peter Lee: Yeah, and it\u2019s difficult. If you go to clinicaltrials.gov and type into the search box \u2018breast cancer\u2019 you get hundreds of results. So the cool project that\u00a0Hadas\u00a0and her team led was to use machine reading from Microsoft Research out of\u00a0Hoifung\u00a0Poon\u2019s team, to read all of those clinical trials\u00a0documents and create a knowledge graph and use that knowledge graph then to drive a conversational chatbot so that you can engage in a conversation. So you can say, you know, \u201cI have breast cancer. I\u2019m looking for a clinical trial,\u201d and the chatbot will start to ask you questions in order to narrow down,\u00a0eventually,\u00a0to the one or two or three clinical trials that might be just right for you. And so this is something that we just think has a lot of potential.<\/p>\n Host: Yeah.<\/b><\/p>\n Peter Lee: And business-wise, there are more mundane, but also important things. Just call centers.\u00a0Boy,\u00a0those nurses are busy.\u00a0What would happen if we had a bot that would triage and tee up some of those things and really give superpowers to those call center nurses. And so it\u2019s that type of thing that I think is very exciting about conversational tech in general.\u00a0And of course, Microsoft Research and NExT should be really proud of really pioneering a lot of this bot technology.<\/p>\n Host: Right. So if I employed a bot to narrow down the clinical trials, could I get myself into one?<\/b>\u00a0Is that what you\u2019re explaining here?<\/b><\/p>\n Peter Lee: Yeah, in fact, the idea here is that this would help,\u00a0tremendously,\u00a0the connection between perspective patients\u00a0and\u00a0clinical trials. It\u2019s so important because pharmaceutical companies,\u00a0in clinics that are setting up clinical trials, more than 50% of them fail to recruit enough participants. They just never get off the ground because they don\u2019t get enough. The recruitment problem is so difficult.<\/p>\n Host: Wow.<\/b><\/p>\n Peter Lee: And so this is something that can really help on both ends.<\/p>\n Host: I didn\u2019t even think about it from the other angle. Like, getting people in. I always just assumed, well, a clinical trial, no biggie.<\/b><\/p>\n Peter Lee: It\u2019s such a sad thing that most clinical trials fail. And fail because of the recruitment problem.<\/p>\n Host: Huh. Well, let\u2019s talk a little bit more about some of the really interesting projects that are going on across the labs here at Microsoft Research. So what are some of the projects and who are some of the people that are working to improve healthcare in technology research?<\/b><\/p>\n Peter Lee:\u00a0Yeah.\u00a0I think pretty much every MSR lab is doing interesting things. There\u2019s some wonderful work going on in the Cambridge UK lab, in Chris Bishop\u2019s lab there, in a group being led by Aditya Nori. One of the things there has been a set of projects in collaboration with Novartis really looking at new ideas about AI-powered molecule design for cellular therapies, as well as very precise dosing of therapies for things like macular degeneration and so these are,\u00a0sort of,\u00a0bringing the very best machine learning and AI researchers shoulder-to-shoulder with the best researchers and scientists at Novartis to really kind of innovate and invent the future. In the MSR India lab, Sriram\u00a0Rajamani\u2019s\u00a0team, they\u2019ve been standing up a really impressive set of technologies and projects that have to do with global access to healthcare and this is something that I think is just incredibly, incredibly important. You know, we really could enable, through more intelligent medical devices for example, much less well-trained technicians and clinicians to be able to deliver healthcare at a distance. The other thing that is very exciting to me there is just looking at data. You know,\u00a0how do we normalize data from lots of different sources?<\/p>\n Host: Right.<\/b><\/p>\n Peter Lee: And then MSR Asia in Beijing, they\u2019ve increasingly been redirecting some of the amazing advances\u00a0that that lab is famous for in computer vision to the medical imaging space. And there are just amazing possibilities in taking images that might not be high resolution\u00a0enough for a precise diagnosis and using AI to,\u00a0kind of,\u00a0magically improve the resolution. And so just across board,\u00a0you go from,\u00a0kind of,\u00a0lab to lab you just see some really inspiring work going on.<\/p>\n Host: Yeah, some of the researchers have been on the podcast. Antonio\u00a0<\/b>Criminisi<\/b>\u00a0with\u00a0<\/b>InnerEye<\/b>, umm\u2026\u00a0<\/b>\u00a0haven\u2019t had Ethan Jackson from Premonition yet<\/b>\u2026<\/b><\/p>\n Peter Lee:\u00a0No, Premonition\u2026 Well,\u00a0Antonio\u00a0Criminisi\u00a0and the work that he led\u00a0on\u00a0InnerEye, you know, we actually went all the way to an FDA 510(k) approval on the tumor segmentations\u2026<\/p>\n Host: Wow.<\/b><\/p>\n Peter Lee: \u2026and the components of that now are going into our cloud. Really amazing stuff.<\/p>\n Host: Yeah.<\/b><\/p>\n Peter Lee: And then Premonition, this is one of these things that is, in the age of coronavirus\u2026<\/p>\n Host: Right?<\/b><\/p>\n Peter Lee: \u2026is very topical.<\/p>\n Host: I was just going to refer to that, but I thought maybe I shouldn\u2019t\u2026<\/b><\/p>\n Peter Lee: The thing that is so important is, we talked of precision medicine before\u2026<\/p>\n Host: Yeah.<\/b><\/p>\n Peter Lee:\u00a0\u2026but there is also\u00a0an\u00a0emerging science of precision population health.\u00a0And in fact, the National Academy of Medicine just recently codified that as an official part of medical research and it\u2019s bringing some of the same sort of precision medicine ideas, but to population health applications and studies. And so when you look at Premonition, and the ability to look at a whole community and get a genetically precise diagnosis of what is going on in that community, it is something that could really be a game-changer, especially in an era where we are seeing more challenging infectious disease outbreaks.<\/p>\n Host: I think a lot of people would say, can we speed that one up a little? I want you to talk for a minute about the broader tech and healthcare ecosystem and what it takes to be a leader, both thought and otherwise<\/b>,<\/b>\u00a0in the field. So you\u2019ve noted that we\u2019re in the middle of a big transformation that\u2019s only going to happen once in history and because of that, you have a question that you ask yourself and everyone who reports to you. So what\u2019s the question that you ask<\/b>,<\/b>\u00a0and how does the answer impact Microsoft\u2019s position as a\u00a0<\/b>leader<\/b>?<\/b><\/p>\n Peter Lee: Right. You know, healthcare,\u00a0in most parts of the world,\u00a0is really facing some big challenges. It\u2019s at a financial breaking point in almost all developed countries. The spread of the\u00a0latest access to good medical practice has been slowing in the developing world and as you,\u00a0kind of,\u00a0look at, you know,\u00a0how to break out of these cycles, increasingly, people turn to technology. And the kind of shining beacon of hope is this mountain of digital data that\u2019s being produced every single day and so how can we convert that into what\u2019s called the triple aim of better outcomes, lower costs and better experiences? So then,\u00a0when you come to Microsoft, you have to wonder, well, if we\u2019re going to try to make a contribution, how do you do it? When Satya Nadella asked us to take this on, we told ourselves a joke that he was throwing us into the middle of the Pacific Ocean and asking us to find land,\u00a0because it\u2019s such a big complex space, you know, where do you go? And,\u00a0we had more jokes about this because you start swimming for a while and you start meeting lots of other people who are just as lost and you actually feel a little ashamed to feel good about seeing other people drowning. But it fundamentally it doesn\u2019t help you to figure out what to work on, and\u00a0so we started to ask ourselves the question, if Microsoft were to disappear today, in what ways would healthcare be harmed or held back tomorrow and into the future? If our hyperscale cloud were to disappear today, in what ways would that matter to healthcare? If all of the AI capabilities that we can deploy so cheaply on that cloud were to disappear, how would that matter? And then,\u00a0since we\u2019re coming out of Microsoft Research, if Microsoft Research were to disappear today, in what ways would that matter? And asking ourselves that question has sort of helped us focus on the areas where we think we have a right to play. And\u00a0I think the wonderful thing about Microsoft today is,\u00a0we have a business model that makes it easy to align those things to our business priorities. And so it\u2019s really a special time right now.<\/p>\n (music plays)<\/i><\/b><\/p>\n Host<\/b>: Well,\u00a0<\/b>this is \u2013\u00a0<\/b>not to change tone really quickly<\/b>\u00a0\u2013<\/b>\u00a0but<\/b>\u00a0this is the part of the podcast where I ask what could possibly go wrong? And since we\u2019ve actually just used a drowning in the sea metaphor, it\u2019s probably apropos\u2026 but when you bring nascent AI technologies,\u00a0<\/b>and I say nascent because most people have said<\/b>,<\/b>\u00a0even though it\u2019s been going on for a long time, we\u2019re still in an infancy phase of these technologies. When you bring that\u00a0<\/b>t<\/b>o healthcare, and you\u2019re literally dealing with life<\/b>–<\/b>and<\/b>–<\/b>death consequences, there\u2019s not any margin for error. So\u2026 I realize that the answer\u00a0<\/b>to<\/b>\u00a0this question\u00a0<\/b>could<\/b>\u00a0be too long for the podcast, but I have to ask<\/b>,<\/b>\u00a0what keeps you up at night<\/b>,<\/b>\u00a0and how are you and your colleagues addressing potential negative consequences at the outset rather than waiting for the problems to appear downstream?<\/b><\/p>\n Peter Lee: That\u2019s such an important question and it actually has multiple answers. Maybe\u00a0the\u00a0one that I think would be most obvious to the listeners of this podcast has to do with patient safety. Medical practice and medical science has really advanced on the idea of\u00a0prospective\u00a0studies and clinical validation, but that\u2019s not how computer science, broadly speaking, works. In fact, when we\u2019re talking about machine learning\u00a0it\u2019s really based on retrospective\u00a0studies. You know, we\u00a0take data that was generated in the past and we try to extract a model through machine learning from it. And what the world has learned, in the last few years, is that those retrospective studies don\u2019t necessarily hold up very well,\u00a0prospectively. And so that gap is very dangerous. It can lead to new therapies and diagnoses that go wrong in unpredictable ways, and there\u2019s sort of an over-exuberance on both sides. As technologists, we\u2019re pretty confident about what we do and we see lots of problems that we can solve, and the healthcare community is sometimes dazzled by all of the magical machine learning we do and so there can be over-confidence on both sides.\u00a0That\u2019s one thing that I worry about a lot because, you know, all over our field, not just all over Microsoft, but across all the other major tech companies and universities, there are just great technologists that are doing some wonderful things and are very well-intentioned, but aren\u2019t necessarily validated in the right way. And so that\u2019s something that,\u00a0really,\u00a0is worrisome. Going\u00a0along\u00a0with safety is privacy of people\u2019s health data. And while I think most people would be glad to donate their health data for scientific progress, no one wants to be exploited. Exploited for money,\u00a0or worse, you know, denied, for example, insurance.<\/p>\n Host: Right.<\/b><\/p>\n Peter Lee: And you know, these two things can really lead to outcomes,\u00a0over the next decade,\u00a0that could really damage our ability to make good progress in the future.<\/p>\n Host: So that said, we\u2019re pretty good at identifying the problem. We may be able to start a good\u00a0<\/b>\u201c<\/b>conversation,<\/b>\u201d<\/b>\u00a0air quotes, on that, but this is, for me, like, what are you doing?<\/b><\/p>\n Peter Lee: Yeah.<\/p>\n Host:\u00a0<\/b>Because this is a huge\u00a0<\/b>thing<\/b>, and<\/b>\u2026<\/b><\/p>\n Peter Lee: I really think,\u00a0for real progress and real transformation, that the foundations have to be right and those foundations do start with this idea of interoperability. So the good thing is that major governments, including the US government, are seeing this and they are making very definitive moves to foster this interoperable future. And so now, our role in that is to provide the technical guidance and technologies so that that\u2019s done in the right way. And so everything that we at Microsoft are doing around interoperability, around security, around identity management, differential privacy, all of the work that came out of Microsoft Research in confidential computing\u2026<\/p>\n Host: Yeah.<\/b><\/p>\n Peter Lee:\u00a0\u2026all of those things are likely to be part of this future. As important as confidential computing has been as a product of Microsoft Research, it\u2019s going to be way, way more important in this healthcare future. And so it\u2019s really up to us to\u00a0make sure that regulators and lawmakers and clinicians are aware and smart about these things.\u00a0And we can provide that technical guidance.<\/p>\n Host: What about the other companies that you mentioned? I mean, you\u2019re not in this alone and it\u2019s not just companies, it\u2019s nations<\/b>,<\/b>\u00a0and<\/b>,<\/b>\u00a0I dare say<\/b>,<\/b>\u00a0rogue actors<\/b>,<\/b>\u00a0that are skilled in this arena<\/b>. H<\/b>ow do you get<\/b>,<\/b>\u00a0sort of<\/b>,<\/b>\u00a0agreement and compliance?<\/b><\/p>\n Peter Lee: I would say that Microsoft is in a good position because it has a clear business model. If someone is asking us, well what\u00a0are you going to\u00a0with our data? We have a very clear business model that says\u00a0that\u00a0we don\u2019t monetize on your data.<\/p>\n Host: Right.<\/b><\/p>\n Peter Lee: But everyone is going to have to figure that out. Also, when you\u00a0are getting into a new area like healthcare, every tech company is a big, complicated place with lots of stakeholders, lots of competing internal interests, lots of politics.<\/p>\n Host: Right.<\/b><\/p>\n Peter Lee: And so Microsoft, I think, is in a very good position that way too. We\u2019re all operating as one Microsoft. But it\u2019s so important that we all find ways to work together. One point of contact has been engineered by the White House in something called the Blue Button Developers Conference. So that\u2019s where I\u2019m literally holding hands with my counterparts at Google, at Salesforce, at Amazon, at IBM, making certain pledges\u00a0there. And so the convening power of governments is pretty powerful.<\/p>\n Host: It\u2019s story time. We\u2019ve talked a little about your academic and professional life. Give us a short personal history. Where did it all start for Peter Lee and how did he end up where he is today?<\/b><\/p>\n Peter Lee: Oh, my.<\/p>\n Host: Has to be short.<\/b><\/p>\n Peter Lee: Well, let\u2019s see, so uh, I\u2019m Korean by heritage. I was born in Ohio, but Korean by heritage and my parents\u00a0immigrated from Korea.\u00a0My dad was a physics professor. He\u2019s long retired now and my mother a chemistry professor.<\/p>\n Host: Wow.<\/b><\/p>\n Peter Lee: And she passed away some years ago.\u00a0But I guess as an Asian kid growing up in a physical science household, I was destined to become a scientist myself. And in fact, they never said it out loud, but I think it was a disappointment to them when I went to college to study math!\u00a0And then maybe an even\u00a0the\u00a0bigger disappointment when I went from math to computer science in grad school.\u00a0Of course they\u2019re very proud of me now.<\/p>\n Host:\u00a0<\/b>Of course!\u00a0<\/b>Where\u2019d you go to school?<\/b><\/p>\n Peter Lee: I went to the University of Michigan. I was there as an undergrad and then I was planning to go work after that. I actually interviewed at a little, tiny company in the Pacific\u00a0Northwest called Microsoft\u2026<\/p>\n Host: Back then!<\/b><\/p>\n Peter Lee:\u00a0\u2026 and\u00a0\u2026but I was wooed by my senior research advisor at Michigan to stay on for my PhD\u00a0and\u00a0so I stayed and\u00a0then\u00a0went from grad school right to Carnegie Mellon University as a professor.<\/p>\n Host:\u00a0<\/b>And then worked your way up to leading the department\u2026<\/b><\/p>\n Peter Lee: Yeah. So\u00a0I was there for\u00a0twenty four\u00a0years.\u00a0They were wonderful years. Carnegie Mellon University is just a wonderful, wonderful place. And um..<\/p>\n Host: It\u2019s almost like there\u2019s a pipeline from Microsoft Research to Carnegie Mellon. Everyone is CMU this, CMU that!<\/b><\/p>\n Peter Lee: Well, I remember,\u00a0as an assistant professor,\u00a0when Rick Rashid came to my office to tell me that he was leaving to start this thing called Microsoft Research and I was really sad and shocked by that. Now here I am!<\/p>\n Host:\u00a0<\/b>Right.\u00a0<\/b>Well, tell us,<\/b>\u00a0um,<\/b>\u00a0if you can, one interesting thing about you that people might not know<\/b>.<\/b><\/p>\n Peter Lee: I don\u2019t know if people know this or not, but I have always had an interest in cars, in fast cars. I spent some time,\u00a0when I was young,\u00a0racing in something called\u00a0shifter\u00a0karts and then later in\u00a0open\u00a0wheel\u00a0Formula Ford, and then,\u00a0when I got my first real job at Carnegie Mellon,\u00a0I had enough money that I spent quite a bit of it trying to get a sponsored ride with a semi-pro team. I never managed to make it. It\u2019s hard to kind of split being an assistant professor and trying to follow that passion.\u00a0You know,\u00a0I don\u2019t do that too much anymore. Once you are married and have a child,\u00a0the annoyance factor gets a little high, but it\u2019s something that I still really love and there\u2019s a community of people, of course,\u00a0at a place like Microsoft,\u00a0that\u2019s really passionate about cars as well.<\/p>\n Host: As we close, Peter, I\u2019d like you to leave our listeners with some parting advice. Many of them are computer science people who may want to apply their skills in the world of healthcare, but are not sure<\/b>\u00a0<\/b>how to get there from here. Where<\/b>,<\/b>\u00a0in the vast sea of technology\u00a0<\/b>and\u00a0<\/b>healthcare research possibilities<\/b>,<\/b>\u00a0should emerging researchers set their sights and where should they begin their swim?<\/b><\/p>\n Peter Lee: You know, I think it\u2019s all about data and how to make something good out of data. And today, especially, you know, we are in that big sea of data silos. Every one of them has different formats, different rules, most of them don\u2019t have modern APIs.\u00a0And so\u00a0things that can help evolve that system to a true ocean of data, I think anything to that extent will be great. And it is not just tinkering around with interfaces. It\u2019s actually AI.\u00a0To, say, normalize the schemas of two different data sets,\u00a0intelligently, is something that we will need to do using the,\u00a0kind of,\u00a0latest machine learning, latest program synthesis, the kind of,\u00a0latest data science techniques that we have on offer.<\/p>\n Host: Who do you want on your team in the coming years?<\/b><\/p>\n Peter Lee: The thing\u00a0that\u00a0I think I find so exciting about great researchers today is their intellectual flexibility to start looking at an idea and getting more and more depth of understanding, but then evolve as a person to understanding, you know, what is the value of this in the world, and understanding that that is a competitive world. And so, how willing are you to compete in that competitive marketplace to make the best stuff? And that evolution that we are seeing over and over again with people out of Microsoft Research is just incredibly exciting. When you see someone like a Galen Hunt or\u00a0a\u00a0Doug Burger or\u00a0a\u00a0Lili Cheng come out of Microsoft Research and then evolve into these world leaders in their respective fields, not just in research, but spanning research to really competing in a highly competitive marketplace, that is the future.<\/p>\n Host: Peter Lee, thank you for joining us on the podcast today. It\u2019s been an absolute delight.<\/b><\/p>\n Peter Lee: Thank you for having me. It\u2019s been fun.<\/p>\n (music plays)<\/i><\/b><\/p>\n To learn more about Dr. Peter Lee and how Microsoft is working to empower healthcare professionals around the world, visit Microsoft.com\/research<\/i><\/b><\/p>\n","protected":false},"excerpt":{"rendered":" Over the past decade, the healthcare industry has undergone a series of technological changes in an effort to modernize it and bring it into the digital world, but the call for innovation persists. One person answering that call is Dr. Peter Lee, Corporate Vice President of Microsoft Healthcare, a new organization dedicated to accelerating healthcare innovation through AI and cloud computing. Today, Dr. Lee talks about how MSR\u2019s advances in healthcare technology are impacting the business of Microsoft Healthcare. He also explains how promising innovations like precision medicine, conversational chatbots and Azure\u2019s API for data interoperability may make healthcare better and more efficient in the future.<\/p>\n","protected":false},"author":37583,"featured_media":640458,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"msr-url-field":"https:\/\/player.blubrry.com\/id\/56493546\/","msr-podcast-episode":"109","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"categories":[240054],"tags":[],"research-area":[13556,13553],"msr-region":[],"msr-event-type":[],"msr-locale":[268875],"msr-post-option":[],"msr-impact-theme":[],"msr-promo-type":[],"msr-podcast-series":[],"class_list":["post-640449","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-msr-podcast","msr-research-area-artificial-intelligence","msr-research-area-medical-health-genomics","msr-locale-en_us"],"msr_event_details":{"start":"","end":"","location":""},"podcast_url":"https:\/\/player.blubrry.com\/id\/56493546\/","podcast_episode":"109","msr_research_lab":[],"msr_impact_theme":[],"related-publications":[],"related-downloads":[],"related-videos":[],"related-academic-programs":[],"related-groups":[952050],"related-projects":[],"related-events":[],"related-researchers":[],"msr_type":"Post","featured_image_thumbnail":"Related:<\/h3>\n
\n
\nTranscript<\/h3>\n
![\"headshot](\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2020\/03\/Research_Podcast_Lee_Site_1400x788-960x540.png\")
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