 Good morning, everyone. Technology is reshaping so many industries and changing the very way we live, but perhaps none more so than health care, whether it's robotics, surgery, perhaps even changing hospitals as we know them. We have an incredible cross-section of technology and the health care industry here today to discuss how this is gonna happen. There's been a lot of talk here at Davos about AI and jobs. We're going to, of course, get to some of those questions today, but we're also gonna talk about the possibilities that AI and the technology revolution is unleashing on health care. So let me introduce our panelists. The first is Albert Borla, who's a chief operating officer of Pfizer from the U.S., Satya Nadella, the chief executive officer of Microsoft, which plays a very interesting role in terms of working with partners across the technology and health care spectrum, especially with AI. Michael Needorf, who is the CEO of Centine Corporation, one of the largest health care providers in the U.S. and the world, and Rajiv Suri, who's the president and CEO of Nokia. I'd love to get started. If you could, and Albert, when we were talking backstage, you were mentioning how really we're kind of at a breakthrough in terms of life sciences and technology coming together in ways that we've never seen before. Yes, first of all, let me start by saying how honoured I am to be part of a panel with such esteemed innovators here. And I would like to say that the impact of technology on health care, it is a topic that I live in brief. I cannot say it is what keeps me up at night, but I can certainly say that it is one of the things that gets me out of bed in the morning, because I'm very excited with the magnitude of the opportunity and I can see the profound impact that technology can have on health and impact, on health and wellness, which is, of course, the passion of my life. And coming back to what you just said, the pace of health innovation will accelerate and will accelerate exponentially. The past was defined by individual siloed progress within its scientific or technological field. Today, individual advances in life sciences or digital technology are colliding to create massive synergistic effects. And the possibilities are enormous and I'm not sure we understand right now the full extent of them, but I could certainly say that there are four themes that have clearly emerged in the health care sector. The first is that technology will help us bring more, better medicines to patients for, and much faster, artificial intelligence, medical devices, biological sensors, digitization of health care records are all super-charging discovery capabilities right now. And we will be able to develop solutions for unmet medical needs that today are very difficult to crack. The second theme, technology will improve physicians' ability to manage sickness. Armed with very powerful tools, they will be able to predict or diagnose diseases much earlier. They will be able to apply personalized treatments and they will be able to monitor, real-time, the progress of their patients so they can intervene when necessary. The third is that technology will empower patients to take an active role in managing their own health. We used to go to the doctor just waiting for instructions. Today patients, more informed than ever and armed with their own research and understanding they expect to be part of the decision-making when it comes to their medical options. And last but not least, technology could disrupt relations of the health care system stakeholders. For the first time in decades, the business model that defines these relations, it is at an inflection point and enabled by technologies ripe for disruption. So, as you can see, technology is touching every single aspect of the value chain of health care and can transform each one individually or the whole care system as a whole. And this is why I think the impact could be so profound. Sacha, what are you seeing? You work with companies around the world. AI is something that springs to mind immediately. Are we going to be seeing big changes with imaging and surgery, robotics? What are some of the biggest uses that you're seeing out there? Yeah, I mean, I'm obviously sitting in between two real experts in what's happening in health care. But one of the great privileges I have as a technology provider and a platform provider, in particular around AI in today's age, to see the advances in health care. I mean, you just take what's happening with AI and people with different abilities being able to fully participate in our society. One of the most exciting things for me is to see advances in computer vision really being applied to help someone with visual impairment to be able to actually interpret the real world. So we have an app that's in an app store called Seeing AI which completely changes the ability for someone with visual impairment. Similarly, take someone with dyslexia. Their ability to read has now been improved because of the advances in machine reading and comprehension. So in Word or in OneNote, you can actually use these tools if you have even dyslexia and improve your reading. We put recently, in fact, inspired by one of the patients of ALS, eye gaze technology into windows. So that means just with your eyes, you can type. And that just completely empowers someone who's suffering from ALS. So these are advances in AI, obviously being built in a much more generic way, but truly are helping people who need it the most. But then you go from there along some of the trends Albert was mentioning. For example, we worked with four hospitals to take their clinical data around eye care. One hospital in India, a couple in the United States, Australia and even in Brazil. Ground truth clinical data is the real scarce commodity here. But the magic happens. In this case, they brought all this eye care data and then applied AI and machine learning. But the most interesting thing is they plumbed it all the way to the medical record and the point of care applications that are deployed in the various hospitals. So the next time the doctor is measuring something for a patient, they're able to use the intelligence that comes from all of these records and completely change health outcomes. Talking about robotics, just even this week, I had a chance to meet a company who's partnered with us called Brain Lab in Munich who's doing some phenomenal work on neurosurgery. We obviously have done a lot of innovative things around VR and AR and HoloLens. And they're applying, so a surgeon can use the holographic output from all of what has been simulated digitally to truly practice the surgery before the surgery. So the surgical outcomes of a neurosurgery can be completely different. So there are many, many examples of industry, I mean, of hospitals to drug providers. In fact, if you think about the industry of drug discovery has always been, I think, bigger users of computational power. But our ability to service them with more computational power and more AI techniques is improving. And even the mundane, the one thing I'll end with is, we can get excited with a lot of technology. But the people I meet in, especially running hospitals and they tell me, look, the biggest cost still is administrative. And workflow automation. So we worked with UPMC in the United States just to start automating, especially real-time automation so that the doctor, the patient, and every provider are much more connected to the outcome. That itself, I think, can make a huge difference, at least in the United States, where we have a real challenge with our healthcare costs. I think that's probably one of the things that bends the curve. And all of these technologies you're talking about there, out there today? Every example I gave is all what's happening today. So we can now talk about what may happen in the future later on in the panel. But the fact is we're living in a time where truly new technologies, but with the real domain understanding of what needs to be done, magic can happen, I think. Now, Michael, Satya just mentioned data. And at 17, you have a lot of data every day about what happens with your patients. Could you describe how you're beginning to use that? Sure, but I might just comment. Of course. I think it's really important, is what you were talking about, Satya, about the holograms and things, the technology that's improving the productivity and the outcomes for the physician. So there's that side of it that I think is phenomenal. The thing that we're engaged with is looking at the data and we have masses of it, but being able to analyze it and put it to practical use day in and day out. And we have one system interpreter that can look at a million files we were talking about in the back room in five minutes. And it can determine that somebody's potassium is growing up so they're at risk for a heart attack. It says the white blood cells are moving at a different level and it's giving the doctor this information in real time. But what it's really doing more than anything else is it's allowing us to move in and be in addictive in a disease state so that you're able to go in before the person has a heart attack and discover what those issues are. If the genome is in there, they can tell us whether or not a new biotech drug will be effective on that person or not. So there's a lot that's coming from the technology that's very practical day in and day out. We're also talking, we have a true care product that every day, all the history on a patient's in there, all the things that have been ordered are in the file. So every doctor has an electronic record that's treating a highly acute case and can look at it and say, okay, they just changed this antibiotic that bothers me on something else. And it avoids those kinds of errors. But the whole focus has to be on the patient. The other thing that I think you mentioned earlier, someone mentioned, is the personalization of medicine. And it's clearly moving in that way and technology is enabling it. I mean, they're now mapping the genome of cancers. I always talk about St. Jude where I've spent some time looking at it, where a child's been told to take him home and let him make him comfortable with nothing more we can do. They take the child, they map the genome, they treat it very personally, and he goes home in full remission. So it's that type of technology, but it's understanding the patient and giving the doctor information in real time. The one other comment I will make is, it still doesn't replace the history and physical that a doctor takes on the patient. The patient, doctor interaction and the importance of an annual physical, interesting. Rajiv, Nokia, we know Nokia mostly for cell phones, but you're making a big bet on healthcare. But you were describing backstage, sounds really interesting in terms of both the present and the future where this could go. Yeah, so Nokia today is a networks company, but we have a healthcare division and as my colleague said, it's a mission to be involved in healthcare. So we believe in a world where you can move from reactive care to continuous monitoring and really move to preventive care because chronic diseases are the leading cause of mortality today. Some 60% of all deaths in the world today, heart disease, stroke, diabetes, they're all chronic illnesses. Most of them are preventable, right? And many are even reversible, with changes to diet and exercise and lifestyle. And some two thirds of the cost of healthcare is on treating chronic illnesses. And we know globally that the cost has skyrocketed, some 50 to 80% over the last 10 years. So at Nokia, we're trying to work on non-invasive, non-invasive wearable sensory devices so that you can continuously monitor the human body, so in vivo, so to speak. So let me give a couple of examples. Imagine the possibility of converting this massive scale medical device, optical coherence tomography. It's used for retina scans and it's used for cardiac catheterization and so on. But imagine that you could miniaturize that. So you convert it to a miniature device with a thousand times reduction, so you make it a bit size chip. And then you have it as a wearable device. So we're working on a sleeve, a thin, unobtrusive sleeve that you can wear and that can continuously monitor many of these stats. Or then take this technology and imagine a 3D OCD scanning system that you can identify biochemical specific information like cortisol levels, lactic acid levels, cholesterol as well, glucose using Raman spectroscopy. When you have all of that data, you are filling the void between consultations because you go to a doctor, you get a blood test, you get a scan done, it's a static scan and then you come back three months later and you don't have any continuous monitoring of that data. Or then think about another non-invasive technique. So if the glucose goes out of whack, it's immediately picked up? It's immediately picked up or you get your next doctor appointment, you've had that for the last three months. So you've had that information, it's immediately picked up as well. Or electrical sensing where you can non-invasively look at bio-potentials, the body composition, neuromuscular analysis, all of that. So the point is with these sorts of products that are continuously monitoring, there's a lot of data being thrown out that you can then analyze, but of course you can start to prevent stuff before it occurs. And we think that you can even figure out, through biomarkers, you can even figure out cancers several months before they occur. And imagine every month and every day counts in the life of a cancer patient. So those are some of the examples of working on these leaps. Today we have wearable devices, but they're fitness devices, they're for enthusiasts, but they're not really medical grade. So I think in the future, we'll see a lot of these devices move into, and I'm talking sort of a distant future here, but really medical grade FDA-approved devices. At Nokia, we have a few of these, we have blood pressure cuffs, we have a digital thermometer and so on, but we're not yet at that level. But we are working within Nokia Bell Labs on this spectroscopy and OCT type devices, and you can bring it on to a chip. Well, you can start to do a lot of things with that real time. I want to talk about cost, but before we do that, I want to talk about the future and try to get you all to think five or 10 years out. Where does this go? When you get up in the morning, what are you most excited about that you think that AI, life sciences, genomics, what sort of breakthroughs, Albert, do you see in the pharmaceutical industry that you're hoping this will all lead to? I hope that with the use of technology, we'll be able to find the cure of cancer. We will be able to unlock the mysteries of obesity. We will be able to reduce significantly cardiovascular deaths. The future is bright, provided that we do it with a patient centricity in mind. Sachin. A couple of years ago, I joined the board of Fred Hutch, which is involved in cancer research. And as part of that, I realized that one of the biggest limiters for our advances towards finding the cure for cancer is keeping up with the knowledge that's being generated. Interestingly enough, somebody instead describing this to me, the amount of new medical knowledge that is getting created, I believe, is such that a medical student is quickly out of date just the day they graduate, because in that period, there is a complete new knowledge that they need to pick up. So one of the things that I think we have to solve for in order to keep pace is come up with techniques, that is AI techniques, that actually, for example, help a scientist, whether it's about drug discovery or a scientist who's doing some fundamental research around cancer, to be able to form a hypothesis by actually getting on the shoulders of giants, so to speak. So I think that's one area. The other one, we recently did a partnership with a company that is trying to do what we have done for the human genome for the immunology. So just imagine if we can, in fact, digitize the human immune system, and we then take that knowledge and apply it for something like precision medicine, that can be a real game changer. So the underlying thing, I think, is going to be data and our ability to reason over data on a continuous basis, some of the things that Rajeev was describing, over time, what we have to watch for is that we don't create more silos here. What could block all progress would be if we have lots of data, but there's no way to connect them? But if we can figure out a way to connect the data and then reason over it in real time, then I think there can be some miraculous sort of advancements. I think if you think about five, 10 years out, you're going to find some disease states that are troublesome today or less so. We're gonna have curative, we're gonna be interdictive, we're gonna be pervenium before the evening. I think we'll also go into finding, there's a panel here I participated in several years ago, that the population's gonna age and they're predicting now where people will live to 120 in sound health up to that point in time because of these advances. When is that gonna happen? In our lifetime. Okay. There's hope, but I think as you start thinking about that, it says that the pace of technology, it's warp speed and I think panels like this help because it helps to bring together the various thought and factors that are out there and it's almost impossible to imagine how far out it can go, the data you're developing, the data and what you've talked about and our ability to analyze it and put it to practical use immediately. The one last thing I'll comment is the whole genome which they've raised. I mean they're gonna be able to analyze and I made the comment the other day that I think hospitals are not gonna exist 10 years from now as they do today because it's gonna be outpatient treating with genome, mixing up the concoction. You'll have hospitals for trauma, OB and joint replacements because that's still gonna be mechanical. And so you're gonna find costs coming down because technology always costs, I think about the visual computers, how expensive they are and now look what they are. And I think that same type of application we're gonna see in healthcare. Rajiv, you were saying that 5G is probably coming in a couple years, so. Yeah, so 5G should start to happen later this year but sort of more mainstream in 2019, 2020. And I think really this level of connectivity will make a huge difference because if you think about all these continuous monitoring devices, think about applications for elderly care at home, critical care, you mentioned it. So I think there'll be a world of medical homes, i.e. homes connected to the hospital over the cloud. And so when, because one of the problems is that if a patient's in the ICU, the monitoring is 90%, the patient moves to the general ward or the hospital room and then it drops to 20, 30% goes home and the monitoring's almost non-existent. So you just have to rely on, if something goes wrong, you'll come to the hospital or you'll call an ambulance. And so how about continuous monitoring and how about connecting the hospitals to homes? Now why is 5G important? Because when you have all of these devices, you're gonna throw out millions and billions of bytes of data. And so the capacity that you're gonna need from these continuous monitoring devices is something that current state networks cannot withstand or provide. So you need 5G for just sheer, massive capacity because we're talking a thousand times more capacity in 5G compared to what we have in current state. A thousand times. That's kinda. So then second is in the future, you'll be able to slice a telecom network. And so today you have a 4G network, you just have one network, it serves consumers, it might serve enterprises. But in the future you'll think about a network slice as a high-speed train where you have your own dedicated high-speed line and there's no interferences or the train that's gonna come in the way. Today's networks are a car going on a highway and there's traffic and there's congestion. And so you'll have your dedicated, so imagine a network slice for a group of hospitals or clinics and you have your own dedicated slice with very high user capacity and user level. So capacity, network slicing, and then latency. And latency means responsiveness of a network. I press the button on my phone, how long does it take to get an action? And of course we don't care, 40, 50 milliseconds is okay for us, but for these kinds of things you need one millisecond of latency. And then you can imagine a doctor in Chicago doing a surgery for someone in Taiwan who's in an emergency situation using robotic surgery. So virtual reality-based robotic surgery. And why do you need that latency? Because you want the doctor to use haptic feedback, to use that robot to actually do the surgery and so you need this very tiny latency. That is also needed for controls like factory automation or driverless vehicles and so on. But in the world of telemedicine and really VR remote robotic surgery, and you'll see it happen because why should all of these surgeries just have to be in the hospital in a fixed network? Because today the capacity isn't available. So capacity, latency, network slices will make a massive amount of difference to many industries, but particularly healthcare. When is that surgery, that kind of surgery gonna happen? A few years from now, I think it's possible. 5G networks go on stream. Of course we need to figure out not just the networks, but the hospitals propensity to want these networks, to have that high level of security and privacy that's needed. So we'll have legislation requirements for security and privacy. I think one of the things to ensure these sort of daily validation of data and devices, you could use a blockchain based approach to introduce security and privacy. So there's security privacy, there's the hospitals need to get it, that we need this, they need to pull for it. Of course my customers, network service providers need to be able to provide that service as a new opportunity. So I think two, three years from now. The other interesting thing is think about a 5G ambulance. And we're working with China Mobile Research Institute on this notion of 5G ambulance. So there's someone who's had a heart attack on the street. You've got this continuous monitoring. The person imagine this ambulance with high definition scanners and cameras, got a CT scan and everything on board. But what you want is persons in the ambulance, you're gonna start taking a CT scan and you want these records connected directly to the emergency room in the hospital. So all of that data is already transmitted to the hospital before this person is taken to the hospital. So by the time the hospital is there, the room's ready, you're in the ICU, and actually you've already got a bit of a diagnosis going. So this is plenty of opportunity once you got this massive capacity and so as I mean, it's interesting to see that connectivity could actually be the cure to some of these massive illnesses. So all of these technologies sound great, but we're in a situation at least in the US where healthcare is a tremendous problem and a lot of people don't have access to basic healthcare. How is the advent of AI and these new technologies not going to widen inequality? I mean, I think, it is the real pressing issue. Take even the veterans administration in their healthcare. One of the fundamental challenges we have is most of our veterans in the United States go back to the rural areas and in order to get even to a VA clinic, they need to drive. But yet there is telemedicine, but there's no connectivity because of market failure in the rural areas. So one of the initiatives that we have recently started is this rural broadband with partners to say what sort of techniques and technologies could be used to essentially solve a problem which is a market failure of getting high-speed connectivity to rural areas because that's where we will need to be able to take some of what is Rajeev was describing and we'll have to sort of say, how do we deliver the telemedicine? So I think whether it's the private sector, whether it's the government, whether it's the non-profits, we will have to sort of really look at these advances. How do we democratize them? And I do fundamentally believe, Michael mentioned that the costs are gonna come down. So our ability to democratize access to world-class healthcare is going to be there. But it's just not the raw physics of it. I think there needs to be political will. There needs to be private sector involvement and then there needs to be a lot of other initiatives that help us recognize the inequities that go beyond health access and deal with it as the pressing time in not just the United States, but all over the world. If I may add, I think what you touched on something very important, and we've talked about in the past, we have to move to policy from politics. And if we can develop a policy-oriented approach that it's a fundamental right for individuals have access to healthcare. Once you achieve that and you start there, then it's incumbent on the individuals on this stage to help develop the techniques and the capability to do it in a cost-effective manner. And I think there's no doubt that can happen. It can happen quickly. And also, I agree with Satya. I think technology not only is going to increase the inequality, I think it is the most powerful lever we have right now to decrease it for all the reasons that he mentioned, including the fact that technology can reduce significantly the cost of healthcare. And even, I mean, obviously drug prices are a big topic. You would see that happening around the world with drug prices as well. I mean, new medicines are very expensive, but over time, you think that the cost will come down? Yeah, look, sickness costs a lot right now to society, not only in terms of human pain, but also in terms of economic burden. And for example, as demographics are going to make the problem larger, because people are living longer. And with an ageing population, the prevalence of non-communicable diseases like cancer, diabetes, cardiovascular is increasing. WHO, for example, estimates that right now 68% of the deaths in the world are due to these communicable diseases. And the same organization is estimated that the cost, so you see now the life. This is 38 million lives, right? You see now the human pain. But also in terms of cost, cumulative WHO estimates that 47 trillion within 20 years will cost those deaths. This is 75% of the global GDP of a year. And a lot of these diseases can be prevented because they can be diagnosed much earlier with technology, so prevent it. And also can be managed much better with technology so they can reduce the burden. There is, let me start with one example of what you just said, Rajiv. You spoke about biological sensors. There was a study that tried to understand what will be the economic impact of good quality biological sensors that they can help diabetic patients monitor their glucose and manage better treatment. And they concluded that if the diabetic patient of a population of US had these wearables, we could avoid 700,000 emergency room visits and 340,000 hospitalizations. And that will cost the system, if the cost avoidance to the system would be four, seven billion dollars in the US only in a year. So you can see that the impact that technology can have as a cost could be profound. And a couple examples of the St. Vincent Health Hospital in Indiana actually did this telemedicine with focusing on congestive heart failure patients and congestive respiratory failure patients. And they found through this remote monitoring and telemedicine, they were able to reduce the re-hospitalization rates quite substantially to 5%. That's a 75% reduction. So there's a lot of anecdotal evidence exactly to your point that that happens. We had a situation, a couple of hospitals we worked with in a few countries where we have the blood pressure cuff and the data from that is given to the care team on a regular basis. So people that take control of hypertension through this found that the rate of that control increased to 86%. So less visits to the hospital and so on compared to the national average in America of 55%. So again, there is enough evidence to suggest that many of these techniques will actually reduce because you are moving to preventive care instead of reactive care. And like I said, two thirds of the cost globally is in reactive care of chronic illnesses. Michael, you mentioned the opioid crisis and how you're using that. I would say we, and I kept the data in front of me, but using machine learning, we have been able in our population to reduce it by 50%. And that's using predictive data to whom may be prone to move into the problems that can excessive use can cause. Evolveous. Evolveous. Evolveous. And so people talk, we can say it's 7.8 to 10 million dollars a year in our population. I say, forget the money for now. Think about the number of people, 50% of the people that are now gonna have more normal lives because we were in addictive using this data and this learning. So you can intervene before? Before, I mean they're looking through and we have the screening as a whole series of things. I don't know more about the detail, but we can identify those people that are prone to be abusers. And then you take the necessary steps, get them the help to avoid it. I wanna give you one other fact to it when you talk about costs. If you take smoking related, obesity related, diabetes related diseases, they reach about 300 billion dollars a year in the U.S. So you're talking about a trillion dollars of expense just by affecting those three states. Cut it by 45% the first couple years and just continue to hammer where? You're gonna pay for a lot of other advances. And to give you a magnitude or to put it in context what Michael just said, $300 billion that could be for example, the diseases related with smoking. It is the entire cost of the country for medications. The entire cost of the country for medication is the same amount. So we are talking small improvements in those areas are having profound economic impact. Before I open it up to questions, I would like to ask you all, we haven't talked much about the rest of the world. How will this play out globally? Do you see China with its growing AI prowess playing a leading role here? Could the U.S. with privacy concerns start lagging behind? How does this play out in India and Europe and other parts of the world? And who is in the advantage? I mean, I think you hit on the one challenge which is clearly if you look at all of the examples I think that all of us talked about data is going to be very important. Ground truth data, especially on the clinical side I think is going to be a big unlock for how one finds, how one goes from being reactive to preventive. And if you say that's true, then how do we get access to that data? There are certain systems that are challenged. The U.S. in particular I think we're challenged because we don't have that one medical record that is there that is universal. Large-scale hospitals and hospital care systems do have that advantage, but we don't have it universally. Canada, for example, does. And so I think China clearly just the demographics-wise will have an advantage in terms of population health being then translated into preventive care or precision medicine. And AI will play a role, but my own feeling is AI profits itself can become more commoditized over time. But the ability to have a policy framework, a connected record at the population level and at the individual level so that you can truly deliver precision medicine, those are going to be what's going to determine who's going to lead, who's going to follow. And there's a lot of work for all countries in the world. I agree with everything. I couldn't agree more with what you just said, but I want to add one other factor. Let's look at different continents and different countries and say what are the issues? There are many countries just providing pure water. For sure. Will greatly overcome their health issues. That type of thing. So I don't think it's one answer for everything. It's looking specifically at a country and in Africa elsewhere there's AIDS and things. Deal with water, AIDS and a couple of things. You can meaningfully improve the health stage of a large population. Then do the things you're talking about and that's for the more advanced. Rashid, how about? I think, Satya and Michael, you said it well. The thing I'll add is that of course it's underpinned by the connectivity that you can offer in the future because if you're going to move to all of this continuous monitoring, you know. You need connectivity. You need that high capacity simply to make something with that data. And so the one that race quickly to 5G networks and build it keeping in mind the industrial use cases, particularly healthcare, will be the winners eventually. Of course, there'll be telemedicine. It's not to say that developing countries will not get there because there's a lot of telemedicine and so on which doesn't need this high capacity necessarily in all instances. But if you're going to move to a world of preventive healthcare, 5G networks will be absolutely key and that's going to start to happen next year in the US, in China, in parts of Europe. But I think when you look at that being mainstream, I'd say it's 2021, 22. So we're still a few years away from 5G networks becoming more ubiquitous and mainstream so it can be everywhere. Right, just one last question before we open it up. We haven't talked that much about genomics and CRISPR and how AI will help really advance gene research and the implications of that. Do you all expect that to be a mega issue moving forward? It's unbelievable the impact that artificial intelligence will have on that just to give you two numbers to understand. The human genome has 30,000 genes and three billion pairs of DNA. And in DNA, so it is impossible without the computing power of artificial intelligence to have meaningful progress, particularly when you want to correlate these billions of information into everyday, every moment phenotyping information that's connected by wearable devices. So it is impossible to do it and this is the major breakthrough. What is an example of what will happen when we're able to do it? We will be able to correlate and find, for example, but this gene is responsible for this type of behavior in the heart and we'll be able to find this information which is connecting one pair with one characteristic in your heart among billions of information. I mean, ultimately precision medicine really personalized or really precise. But I mean, one of the fascinating things to me is how AI techniques developed for a lot of other purposes are turning out to be very, very useful in this quest for precision medicine. But as we get good with the genome, we now have more digitized data, so the immune system and then all of the real-time feedback. So I think the one other place where we will be challenged is to keep up with the compute capacity along with the connectivity that Rajiv made a fantastic case for. The other one is the compute power that is needed in order for us to be able to actually apply AI and all of this digitized data to deliver precision medicine is probably what's going to be the most exciting thing in the years to come. In the next 10 years, that's going to be the solution. It's going to be outpatient. It's going to be drawing your blood. There's plenty of cells available now. And it's going to be very curative, very specific. We can't have these data voids between consultations. Okay, we'd like to open it up to questions. I see one right here in the front. If you could please identify yourself. That would be great. Sure, good morning. My name is Alex Jia. I'm a global shaper from Tianjin Ham from China. And I run a housecare startup in variables called iHealth. So what I found basically as the panel mentioned actually from China getting good quality medical data because of less regulation is quite helpful. But I found one of the challenging things is actually developing the technology is okay, but it's actually challenging to actually be able to get the payer to actually pay for it, to have the business model and that either insurance company or government are willing or start paying for it is something what I may found challenging. I'm not sure about the view from the panel whether having the developing of AI or precision medicine, et cetera, variables, whether do you see that can be a difficulty of getting paid from the payer? That's the next one question. How are we going to pay for it? Someone has to pay for it. I mean, the reality is I think each country will decide in terms of what the system is. But I guess the real challenge is access. Because quite frankly, the real question today is not about who is going to pay for it but how much is what the outcome is going to cost. So one of the things that I do believe is there's going to be a secular shift is instead of paying for just activity, people will pay for outcomes. And so if somebody is designing a system today fresh, I think every payer will want to pay for outcomes. And so as long as we at least recognize that that's the shift, whether it's in China or in the United States, I think we will have a much more stable healthcare system where every constituent there truly does get, I guess, the benefits that are sustainable. Otherwise, I think we'll have an unsustainable system. I would agree with Saty and I would add that because of increased health care costs, sometimes the reactions are irrational because we are having an acute issue that we are dealing right now. But the truth is that sickness is what is costing and technology as well as medications are helping to reduce the cost. So once we will be able to come to an agreement that when there is a clear evidence of benefit to the patients and the healthcare system, there needs to be a value that is calculated and then this value we can happily pay for it, things will become much easier. And the fact that Satya spoke about we are moving in the healthcare system for a marketplace that it is much more volume-based, which means fee-for-service, for example, into a marketplace that it is much more value-based, which is outcomes-based reimbursement, for example. Technology and data will allow us to be able to document the value that we are producing with our interventions. So that will enable very different contracting relations between the parties. Including potentially, if it's outcome-based, personalized insurance. Including, this is a much bigger issue of personalized insurance. Contributial, but yeah. That comes to human rights. But I would say that eventually, the health and the patients will be the big winners. We're moving forward right now to a value-based contracting. But I think also- Even within the ACA and all the- Oh, we're the largest ACA provider. We do it very well and doing very well with that product. But it's value-based, but I think also we have to recognize a paradigm has to be one of, sometimes you have to invest to save a lot. But this is the government. I know that. We have to start to demonstrate how this investment will save a lot very quickly. So you would expect the government is going to- Well, I think it's gonna be a combination of government and a lot of private sector as well. Other questions? Is he one right there? Hi there. Hooman Hakimi, I run the diabetes group for Medtronic. I have a question about patient engagement. And you had touched on this before. All of these advances are amazing. But even if you make the greatest drug or the greatest wearable, there's no guarantee that the patient is gonna take the drug or wear the device. So how are you thinking about technology to engage the patient? Again, maybe I will use an example. I think it's fascinating what's happening in this field right now. I mean, FDA approved the first electronic pill, if I can call it like that. So it is basically biological chip that it is in the tablet. And once you take the tablet and dissolves into your stomach, it sends a signal that you took the tablet. So imagine the applications of that, compliance. The insurance companies to know that the medicines that patients should take, they do take them. It is fascinating what happens in this field. But of course, there will be an initial cost that someone needs to invest. Of course, education scales. But my sense is that we will move increasingly. Today we have hospital-centric or doctor-centric care. And the question is, will we move to a patient-centric care where the patient starts to pull if you're gonna move particularly to a preventive healthcare world? And I guess we don't see that level of patient engagement today because the awareness is massive. Because many of these devices, they're not continuous monitoring and they're not medical grade today. They're the wearable devices I'm talking about. So the in vivo devices are more fitness-based devices opposed to real medical grade making a difference. So if you have to stop pricking yourself and start to have a non-invasive technique to understand your glucose level or not to go to a blood test and understand your cholesterol levels, then obviously people will go more for that option because it's just non-invasive to begin with. And it is continuous. There's education, there's skills, but also you need the right kind of devices and infrastructure to be in place. Michael, with your physical comment earlier, you seem to emphasize that we're still gonna need the human. To his point about people just using it, you'll need the human interaction with the technology, not just the technology, right? Very true. And we've done a little research, not enough that I would consider it peer-reviewed level. But it says a lot of individuals who do not take their drugs, it's often because of a side effect. And that's where the physician, the nurse practitioner, the others have to interface with the patient and help them understand the value and the benefit of it versus the other issues. So we've seen that and we have to have a way to overcome it. And I think it's once again that personal intervention sometimes is needed that AI just won't do. Yeah, we believe also in a human augmented AI type of system, because yes, you have AI, but you will need that human intervention. It's a combination of computers and people work best. Exactly, right? I saw another question right here. My name is Yogesh Malik. I'm the technology officer of Veon. We are the seventh largest mobile operator in the world. And I agree, technology will advance a lot. But the topic we are also reaching the big challenge where data is going to be needed for everything. At the same time, we are talking about consent, privacy, GDPR. And the third angle is a cultural revolution where you cannot just augment by your own hunch, but you got to believe in the data and the AI. So how do you see these combining together to yield that super impact and empowerment to the grassroots? I think that's the question I see as a big challenge, but I'd be happy to listen to your views on that. I mean, I don't know. I don't know, at least I have an answer as to how it will be shaped. But this is where I think the multiple constituents who are involved in setting, let's say, the privacy guidelines, people who are thinking about how do we bring down the healthcare cost? All have to come together. So that's why I think in, at least, let's take the case of liberal democracies. It has to start with real legislative solutions to some of our society's hard challenges, unless and until we can confront that. How do us one actually say, oh, let me value privacy over better preventive care or precision medicine? Of course, both are valuable. But what's the framework that allows us to make sure that privacy, which is one of our enduring values, is not traded off, but at the same time, we're not left behind with higher costs of medicine. So I don't think I have a way to predict how this will shape up, but I do believe that in institutions like the legislatures have to really function in order to really do these, come up with new equilibria that allows us to make progress as a society. Of course, the thing with privacy and security is not just gonna touch health, it's gonna touch many other industries. And the thing is, countries are going with their legislations and policy requirements, but it is difficult to globally harmonize laws around privacy and security, right? That's not gonna happen. It's almost impossible to achieve. So the question we were debating this yesterday, also in the United Nations Broadband Commission, and we were talking about whether there should be some, at least some global standards and assessment principles that can be followed on privacy across the world. I don't know which entity has, sort of globally has that legitimacy to take the lead in that because ultimately, countries are countries. But my sense is, at least as a minimum acceptable requirement, we need some global norms, principles, standards so that we can drive this sort of privacy across the world. It's a hard nut to crack. Yeah, and at some level, by the way, just on privacy, GDPR hopefully de facto becomes that because the last thing the world needs now is more fragmentation. Yes. And if we can take all of the work that we've had to do to become GDPR compliant and build on it versus to your point, Rajiv, fragment, then I think at least we are on the path that will still help us resolve how do you keep privacy while at the same time being able to use data in different contexts that create common good? Yeah. It's a technology issue because technology is exposing what used to be very private in ways that we don't recognize until it actually occurs. Yeah. We have time for one more. Maybe you could both ask your question and then we'll tackle it before we wrap up. Arun Sharma, I'm a board member in the Adani Group and also a Deputy Vice Chancellor at Queensland University of Technology. It's been a fascinating discussion and I want to bring the topic back to the patients. The entire discussion is about compliance. Why aren't they doing it? Why don't we just treat the patient as what they are? They have their mix of what level of technology they are able to accept, where they want human intervention and where their behavioral profile of doing things is important. And I think doing an analysis of the patient's behavioral pattern is going to be extremely important in the effectiveness of these things. Like even the most human touch person is perfectly happy when you tell them that a robot will be able to take you to the toilet, they'd rather prefer that for their privacy than a human taking them. So we don't know these answers. And once we start doing it, the effectiveness is there with the patient and they become our advocates. Policy doesn't change because a bunch of academics come up with an idea or a bunch of corporate sector say this is the greatest technology solution. Policy change happens because politicians listen to the voters. And we have to make patient the center of attention here. Understand what they are prepared to take and how we adopt our technology and of course over time, using machine learning and behavioral economics, nudge them in the right direction and they become our advocates and they are the ones who are going to help the legislative change that is going to make this change. And then the one last question. Thank you, Josie, but I'm wrong for American company. My question is in view of the technological advancement that you just described, what do you see the role of the big pharma company in this equation going forward? The panelists quickly react to either of those. Albert, I think you're stuck. Yeah, I see the role is very important. The pharmaceutical companies are all about creating a patient value and actually the more value we create, this is the more value we can create also for our shareholders. So the two are very connected right now. So I see that technologies providing me an opportunity to do my job much better, more efficient to come to discoveries and achievements that I wouldn't dream to do before. And also at the same time, I see that technology would enable overall the healthcare system to become much better, more efficient, more effective and eventually create health for the world. So from my perspective, I think that the impact that we can have by embracing the technology, by mastering technologies that we are not familiar now with and by partnering with people that they are experts on that, it's an obligation that we have. It's not, it's an obligation to society because they expect from us to find the solution. And before we wrap up, I would love to ask each of you if there was one thing you could change or one challenge problem that you think really needs to be worked on before we can kind of get to this vision of a technology enabled future with significantly better outcomes in terms of healthcare. I just love to go around. From my perspective, and to talk about it, I could change one thing that would be regulations. I think technology is moving in a much faster pace than legislators. Regulations must catch up. We are talking about data interoperability. We are speaking about enhancing security and privacy rules. But at the same time, do not block progress with excessive and unrealistic restrictions. And we need the regulatory system to modernize itself so that they can review and approve those technologies because health is an extremely regulated environment. So if I could change one thing, I would bring regulations to the 21st century. Are they worse than the US or Europe or where are they most challenging for you? I think all over the world. And don't take me wrong. Regulators are trying to catch up, but right now they're behind, both in the US and in Europe. I don't know, I'll pick up on the gentleman's comment actually. I think perhaps maybe keeping patience and patient care as the central driver of what needs to happen that hopefully brings all the constituents together. Maybe that's what we need. Technology and technology advances are undeniable. Our ability to manage even the hard challenges that we face today in terms of cost of care is tangible. But then what's our ability to actually deliver the benefits of all of this? I think is going to be more about our policies and coming together in a way that all constituents have consensus to deliver ultimately to the patient or the citizen. Maybe that's what we should optimize around. What I came to realize in the last 45 minutes or hour is that there are four individuals on this stage that don't really compete day in and day out but have various roles to play within this. And somehow we have to find a mechanism to encourage more of this kind of discussion where the groups of individuals figure out how to work together against the common objective of ensuring that technology is applied in a constructive way that's patient-centric and helps reduce cost. Yeah, I mean, it's a multi-stakeholder world, as you said, Michael. And for me, I think the biggest thing I want to change is that we realize that reactive care is always ever going to be more expensive and more painful than preventive care. So I'd like all players in the ecosystem to drive towards preventive care. And I think the comment made by yourself is spot on that it needs to be patient-centric and different people in different parts of the demographic are gonna have different behaviors and acceptance rates, for example, elderly care versus other sections of the society. And we need to adapt to that. So this patient-centric care and the notion of preventive care and the fact that that through technology is gonna be the biggest cost reduction enabler. Well, I'd like you all to join me in thanking our panelists for a fascinating and very productive discussion. Thank you. Thank you.