The Future Of Medicine: Precision And Personalization with Dr. Daniel Kraft

Coming up on this episode of the Doctor's Pharmacy.

We're all touching our smartphones and other consumer devices frequently. They can become a bit of our health bubble that can give you smart nudges over time to help nudge you.

In the right direction in ways that match you.

Hey everyone, it's Dr. Mark.

Most people don't realize that our exposure.

To light has a huge impact on our health. That's because we're wired to respond to the changing position of the sun, which regulates our bodies circadian rhythm and either helps us to feel energized and awake or lets us know it's time for bed. But our modern always on culture means we're now surrounded by conventional LEDs and fluorescent bulbs and digital devices with bright lit screens that emit junk light around the clock. My friend Dave Asprey actually coined that phrase, junk light, to describe the excess of blue light as well as green and violet light that disrupt our circadian rhythms. Junk light reduces our ability to produce melatonin, which is a key hormone for regulating our internal clock, sleeping well and even aging well. It's important to realize we actually need to be exposed to certain amounts of blue light in the daytime, otherwise we may feel too sleepy or tired. It's the excess of all that blue light along with other types that leads to a long list of potential problems. So how can we get just the right amount of light throughout the day? Well, going outside is of course key.

But we almost all work on computers these days and have our phones with us 24/7.

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The full junk light spectrum, including blue.

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Episode of the Doctor's Pharmacy. Welcome to the Doctor's Pharmacy, and that's Pharmacy with an F. I'm Dr. Mark Hyman, and this is a place for conversations that matter. If you care about health care, the future of medicine, where we're going, what's coming around the corner, and how our health care is going to be over the next few decades or even a hundred years, you better listen up because we have a great conversation today with a good friend of mine, someone I've known for a long time, Dr. Daniel Kraft, who is a Stanford and Harvard trained physician scientist inventor and entrepreneur. He's currently chair of the XPRIZE Pandemic Alliance Task Force. He's been in practice over 30 years. He's in biomedical research, healthcare innovation. He's chaired the medicine department for Singularity University and is the founder and chair of Exponential Medicine, which is an amazing medical conference all about the future of medicine that I've been at and spoken at. And it basically explores the convergent rapidly developing technologies and the potential in biomedicine and healthcare. He's published in lots of journals. and is just a cool guy. He's a faculty at the UCSF Medical School and is involved in lots of innovation. He's a pilot, which is cool, like my dad, and he served in the Massachusetts California Air National Guard and officer and a flight surgeon with F-16 F-15 fighter squadron. That's pretty cool. Not many doctors get to do that. And he's just looking always at the future of where we're going and how we're getting there. So thanks for joining us on the Doctors Pharmacy. Daniel.

Thanks a lot, Mark, for having me. It's exciting to be here and to mix up our worlds again.

Yeah, it's great. So, you're a major pioneering voice in medicine. I remember hearing you speak TEDMED so long ago and you were painting a picture that was very refreshing to me because you were looking down the microscope at where we're going, or maybe the telescope, or you had some special glasses on that allowed you to see what is the most important trends in medicine and technology and health. and what the future of medicine might look like. So what does the future of medicine look like to you and how is healthcare changing with all our evolving technology? Because it's changing so fast and yet we're still seeing mass amounts of chronic illness, mass amounts of poor health that's only getting worse. So on one hand, we're doing all this great stuff, but on the other hand, our population is getting sicker and.

Sicker and dying more and more. So how do we reconcile that and how do we think about what the future could look like? Well, first we need to start to look at where we are and where we've been and where we're going. I think we don't actually practice healthcare. We practice sick cares. We both those clinicians, more often we wait for the patient to show up with a heart attack, the stroke, a late stage cancer. And so we live in this age of intermittent data where you only usually collect that in the four walls of the clinic or, God forbid, the emergency room or ICU. And that leads to our reactive mindset and where the future is heading and was starting to unlock and unleash, particularly with COVID as a catalyst, is to move to an era of much more continuous data. It could be from your smartwatch, from your smart bed, from the Internet of Things home, from your your mobile devices, and that's going to enable us much more personalized, proactive, true healthcare that can start to happen anytime, anywhere, arguably at lower cost with better health equity. So in a nutshell, the future of medicine is at this convergence of new mobile technologies, new forms of data, everything from your physiome, your digitome, to your microbiome, to your genome. Hopefully not just the data, but the insights that we can then use across the continuum to help the optimize wellness, to do earlier diagnostics, to do smarter therapies, and then of course, to apply to global and public health.

I remember being at one of your lectures years ago, and I've stolen this because it just was so brilliant. And I don't know if you're still using this framework, but you talked about five converging trends in science and medicine and technology that were going to transform our approach to health and disease. And they were, in no particular order, the omics revolution, which includes everything from our genome to our microbiome to our proteome and transcriptome and all the omics, which we're still plumbing the depths of. The quantified self movement, which is the digitization of our data, not the intermittent data you're talking about. In other words, your oral ring or your continuous glucose monitor or your Fitbit, and there'll be more and more sophisticated tools. They'll be able to track all sorts of things through our biology that are decentralized, democratized, and allow that data to be used to help analyze our state of health. Then there's the systems biology revolution. some people call P4 medicine from Leroy Hood or functional medicine, network medicine, there's a new textbook of network medicine out of Harvard. And so it's this framework of redefining the body based on biological networks and systems rather than the typical organs and specialties and diseases. And you take all that quantified self data, the systems biology layer on top of that to filter the data, the omics revolution, and you run that through our technology platforms of big data analytics and AI, and all of a sudden everything looks different. Because when you think about how traditional doctors practice, we do a physical exam, which is pretty rudimentary most of the time. Well, you can pick stuff up and then a bunch of lab tests. But the lab tests we do are pretty basic. They're often not really abnormal until you're really sick. And we're looking at a limited data set of maybe, you know, dozens to at the most hundreds when there are literally maybe hundreds of thousands of data points that we could be using. And when we are missing looking at all that, we're literally just sort of, you know, someone said, someone said, nutritional medicine is like, you know, trying to diagnose what's wrong with your car by listening to the noises it makes instead of lifting up the hood, you know? And I think this, this new framework that you laid out that I've borrowed and talked about, is so profound. So can you kind of take us down the rabbit hole of each of these things and how they're going to transform medicine, healthcare, and our approach to disease? Yeah, your spot on really is that.

Convergence of multiple fields that enables all those elements. And I love your point about, you know, what we normally do as clinicians, we get maybe a chem 20 or chem 40, you know, 40 limited pieces, we get the basic vital signs. And that leads to our sort of incremental medicine. But now in this, you know, exponential age with, you know, the power of my, even my, I'm holding right now my iPhone two that's 12 years old. It was amazing 12 years ago. Now it feels slow and clunky. Now our smartphone devices have become integrated medical tools. The camera can diagnose your urine, the microphone can diagnose your cough, the camera can now pick up your heart rate, your heart rate variability, even potentially your blood pressure, your blood sugar. And the point being from intermittent to continuous is that normally as clinicians we get that spot check. But what's really interesting, of course, in health is how do those data points change based on your baseline? So the Mark baseline versus the Daniel baseline might be quite a bit different. resting heart rate when I'm sleeping is detected by my mattress, you know, goes from 55 to 75, maybe something's going on. And the challenge is how do we take those digital breadcrumbs or your proteome or other elements that might be measurable and changing and understand when are you shifting from, you know, normal to some early sign of disease so we can cut it off at the pass or understand diseases much more through the continuity. Now there are ways to detect hormones from your saliva, voice as a biomarker can sound, you know, your sound of your cough is that COVID or just a cold? And so putting all this together, it's still the early days because right now as clinicians, we don't want more data from our patients. We want the actionable insights and information and knowledge and do something with it.

Right.

If I'm streaming my EKG from my watch, you don't want to see every EKG. You don't want to be liable for that. What we're starting to learn as we start to crowdsource millions of people wearing wearables, millions of folks getting their genome done, which has dropped from price, you know, a million dollars 15 years ago to, basically 200 US dollars or less, is to put that into the workflow of the clinician so you're not overwhelmed by trying to read omics and raw data from a sleep tracker and synthesize it using AI, machine learning, big data to make it really actionable for your exact patient, not for the average patient, because none of us are of course average. So we're still in the early ages of this digitization and connecting the dots. It's starting to unleash a bit, particularly with COVID and new forms of telemedicine and our ability to connect the dots to our mobile devices into our medical records and beyond, but tons of potential. But I would stress it was early days and we need the regulators, the FDA, to help unleash this, which are starting to do with software as a medical device. We need to help the payers pay for some of these new, whether it's your Omics or your digital exhaust, to integrate that into our care across the continuum, particularly on the prevention and wellness.

Side, not just waiting for when disease hits us. Yeah, it's such a different vision because, you know, I remember once sitting in my office talking to a guy who worked for Fidelity and his job was analyzing financial data. And I said, how many in your field use computers to analyze data to make decisions about what to do with money? He's like, what are you talking about? That's all we do. That's it. I'm like, well, guess what? We don't do that at all in medicine. We're relying on the person sitting in front of you, your doctor or healthcare provider, who went to medical school who knows how many centuries ago. who may or may not have caught up with the 900,000 scientific papers published every year, who is trying to see 30 patients a day and make sense of your story and hoping that they're going to figure it out. Whereas our possibility, given the painting, the picture you just painted, of interpreting enormous amounts of data, sifting that through a filter, making sense of it, and having decision support for providers is just a whole new world. It's something we really haven't really barely touched. And in functional medicine, we try to collect a lot more data and we try to understand much more data points and filter that through the lens of functional medicine and systems biology, but it's still only like a tip of the iceberg in terms of what we're headed towards, right?

So I think we're now entering this golden age of functional medicine, what you've been doing for years now, you can actually get a true microbiome and measure that every day if you'd like to. You can understand someone's metabolomics. I'm holding here, I just did my own CGM, these low-cost continuous glucose monitors. I'm not diabetic, but I get insights in how I respond to certain diets or foods or drinking orange juice or exercise or stress. And particularly with nutrition, which you're so honed in on, now I think we can enter this age of precision nutrition where you integrate microbiome, genome, metabolomics and really move from just one size fits all diet to ones that might really match someone's physiology or their disease state. So, I think it's a super exciting time, not just for the clinician who can hopefully not be overwhelmed by all this data but make sense of it, but empowering the individual, the consumer. We talked about quantified self. And yes, right now on my phone, I have my aura ring, my Fitbit.

I'm wearing my whoop and my Apple Watch.

And they, you know, they give me empowerment. And you're glowing in the dark. You glow in the dark. I do. And it's fun to compare how much they measure my sleep, you know, my sleep score, et cetera. But that could give me insights to hopefully self-coach my sleeping. I don't need to go see a sleep doctor. Similarly, if I have a medical condition like hypertension or diabetes, I can now collect that data, blood pressure, blood sugar, and share it hopefully to my clinicians. So from quantified self to quantified health where that data can flow, be interoperable, not overwhelming, and eventually sort of crowdsource, just like when we're driving now with Google Maps in ways we can't imagine driving without those now, we're crowdsourcing our driving and location. if we can build a bit of a WAYS for Healthcare, sharing what we have on our own health or wellness or disease journey with our fellow patients, patients like us or our clinicians to really make sense and not use again that sort of average clinical trial, double-blind randomized control for a set of patients that really don't match the individual. And one example that's starting to happen is a company out of Israel called StuffthatWorks.health is really building this WAYS for Healthcare. You can share if you have psoriasis, ulcers of colitis, my conditions plantar fasciitis. I share what's going on with my foot. I'm learning from hundreds of thousands of others who have plantar fasciitis.

What might work for me? It's not like patients like me and our friend Jamie doing that years ago.

It was, but now it's more accessible. Patients like me started for very sick patients like with ALS, Lou Gehrig's disease. Now it can be almost any condition. And, we're starting to see what really works for different drugs, different interventions, whether it's mindfulness training or a certain diet because, you know, not every patient is in the same subset. It might be older, different comorbidities. And that's the challenge with our medical data today. It's often an average patient. And I think we're now entering this age of precision personalized medicine using some of these new tools, some of these new diagnostics. And what's interesting as well is care is moving, of course, from hospital to home to our phone to on and inside our bodies. The fact that now sitting on my desk, I have a disposable PCR box that can diagnose COVID. And these sorts of home diagnostics have only accelerated in COVID and they'll not just be used for infectious diseases coming down the stream, they'll be used to pick up non-infectious elements and really give us a whole new lens for new forms of actionable information.

Yeah, I mean, well, the whole issue is what is the actionable information and how do we decide what to do? You know, my challenge and I'd love you to answer this question is if we get all this data, but we're still filtering through the same diagnostic lens of conventional medicine, which is based on these IDC ICD-10 codes essentially categorizing people according to symptoms and geography. What symptom do you have and where is in your body or what are your lab tests show as opposed to the causes and the mechanisms? For example, Watson is this computer that might beat the best chess player but also went to medical school. And, the Cleveland Clinic, they are partnered with Watson. and I said to the developer, what I say, you know, this is really great, but if you're sort of using, you know, this powerful tool, but using an old paradigm, it's almost like rearranging the deck chairs in the Titanic. How do we get to a place in medicine where we are taking advantage of the new framework of systems biology and using that as the filter for the data as opposed to our current diagnostic model?

Right?

And so right now we have the filter of diseases, but maybe we need to think about a filter that looks at these biological networks and the dynamic interactions. And the microbiome is the best example of discovery that's blown up our ideas of disease, right? How does the microbiome cause heart disease, cancer, diabetes, obesity, Alzheimer's, autism, autoimmune disease, allergies, you know, I could go on and on, depression. It doesn't make sense. You know, when you go to psychiatrists, they're not looking at your poop. or the rheumatologists are not looking at your Poo-pa, but maybe that's where the answer is. So that's just one example of how our framework of disease is so outdated. But I'm wondering how you see, given all the trends that are happening, we move from that paradigm to filter the data to a new paradigm.

Well, you spot on the paradigm. I was also shifting in how you define, quote unquote, disease. So something as common as type 2 diabetes, there are at least three different genetic subtypes who respond if you have type 1 versus type 3, you respond very differently to diet, medication, and other interventions. So almost every element from autism to Alzheimer's to, of course, cancer, lung cancer is just lung cancer. There's probably a thousand or 100,000 different molecular variations can now start to be understood at this molecular multi-omic level, which means we can then design both prevention and therapy to match them, including on particularly on the prevention side, Very few diseases have one gene like sickle cell or thalassemia. Now we're understanding this idea of polygenic risk scores, a base genome which doesn't change. Many genes play a role in your risk for diabetes, atrial fibrillation, cancer, et cetera. And I think part of our future and really truly functional medicine is to understand each patient based on their underlying genetic risk factors, also based on their socio, where they've lived. If you grew up in Beijing with lots of pollution, maybe you have to change your screening for lung cancer. and give that multi-omic, sociome, polygenic elements in a way that the clinician can adjust, that the patient and their families can understand, because it's just completely overwhelming. And platforms like IBM Watson can play a role, but again, they're only as good as the data they're trained on. And many of these systems-- Right, that's what I mean. Yeah. Yeah, they can only be, if they're only taking data from European Caucasians, it may give you the wrong answer if you're dealing with folks from Asia or from Africa. by heritage. And so there's a big attention now being paid to not just health equity, but data that's collected in forms that match the population. One great example is the NIH has this All of Us trial, all of us.nih.gov is the website, where you can sign up as a data donor and share your genome, your medical records, your Fitbit data beyond. And that's essentially like a Framingham trial on steroids. It's going to be a million or more Americans, and we're going to learn Instead of just from relatively healthy nurses in Framingham, Massachusetts, what really might be the best guidelines for you for high cholesterol, to managing hypertension, to cancer prevention, et cetera. So big challenges, big opportunities. The data alone isn't enough. How we analyze it and how we.

Make sure it's matching the folks you're targeting at are key as well. Well, that's right. So you kind of have to have the overlay of the paradigm you're filtering the data from, or this junk in, junk out. And I think that's, that's what I worry about is that it's so difficult for that paradigm shift to happen for traditional medicine. You know, like the structure of scientific revolutions by Thomas Kuhn talked about this idea of paradigm shift in normal science and how difficult it is people to shift out of the normal science, a normal way of seeing the way they see things. It's like they have blinders on. And it's just striking to me how challenging it is to get people to.

Kind of come along to get the ideas of a new paradigm. Well, part of the paradigm shift, of course, in healthcare, there's many misaligned incentives. And the practice of care is, again, sick care. You get paid to often do more biopsies, more procedures, more transplants to keep the hospital beds full, not to keep patients out. And so part of that paradigm shift has to occur in the context of how the clinical care is performed. How do you reward the clinician? If they want to prescribe a connected blood pressure cuff or one that's embedded in your smartwatch, are they going to get rewarded for looking at that data and manipulating it? Or will the AI system be paid for that can help tweak your medications or 3D print them in your home. So part of the paradigm shift has to be aligned with the practice of care, who's doing it, how we get paid for it. Because in many cases, the incentives are.

To treat the disease, not the symptom. I mean, we see that, for example, in clinical care right now with diabetes, it's one in three Medicare dollars, which are spent usually on intensive treatments, medications, hospitalizations, surgeries, all the things that are needed to keep diabetics from getting more complications. And yet we know that food is the biggest driver of diabetes and that for most people it is the biggest treatment. And yet we don't provide payment for people to actually get treated with food, which is striking to me. You know, the Geisinger study looked at food insecure diabetics and David Feinberg, who's now at Google, gave them $2,400 of food a year plus some support. and food up for their family, which doesn't even like a lot of money or food. And they're able to save about, you know, almost $200,000 per patient and improve their blood sugar simply by providing the food. And that's really what's frustrating to me is that we have a lot of the beneficial treatments that optimize health, but we don't pay for them. We pay for, well, you know, what we do in medicine now, which is usually drugs and surgery.

Yeah, and Hippocrates said a long time ago, let food be thy medicine, medicine be thy food. And now what's interesting in this, you know, digital age, I've got on my desk here randomly my little lumen device. I can track my my my tabletome if I'm ketogenic or not. I've got that CGM that I mentioned. There's other handheld spectrophotometers that can wander food and detect, you know, how many calories, if it has peanuts in it, it has gluten. And again, that might lead to enabling all of us to use food as medicine or as health in easier ways and, and to connect those dots. And again, learn. I think that's, you know, back to the, you know, this idea that we can crowdsource. I used the Waze analogy early, but to the car analogy, there's all these new sensors coming into your car, 400, 500 sensors. You don't pay attention to any of them. You don't even know most of them. You do pay attention to is when that check engine light goes on, and then hopefully makes you take your car to the mechanic before you blow a gasket. I think part of this future medicine will be that simplified user interface that can match the individual's age, education, culture, it communicates in the right way to help none just towards a better diet, to getting checked up, to addressing a problem before it gets challenging. And the car model, now we have Teslas, which are essentially, you know, computers on wheels. And when they are driving in their self-driving or quasi self-driving mode, if they learn that they need to slow down in a curve, they upload the map to the other Teslas when they do the update in the cloud. So there's that hive mind element. So whether it's with nutrition or treating cancer or diabetes, the more we can start to cross-fertilize, share, connect those dots, and update the maps for all of us. we'll do better across the nutrition side and every other element of health care, including public health. Our data out of Stanford and scripts can show that your smartwatch can find changes in heart rate variability and other elements that predict that you're catching COVID before you're even symptomatic. And imagine part of our future public health measures where we're all part of that map going forward.

Definitely looking at the quantified self stuff is interesting. I put on the the levels of glucose monitor and track my blood sugar over a number of weeks and was fascinating to see, you know, what I ate, when I ate, how it affected my blood sugar, when it was up, when it was down. It was really quite interesting. And I, I'm not diabetic or don't have any metabolic issues, but it was, was still very instructive about, oh, if I do this, this is going to create a bigger Spike or a bigger drop. And this is how I keep my blood sugar even. And we know that, for example, keeping your blood sugar even is one of the key to longevity and health, that it's these spikes in insulin and blood sugar that really cause a lot of our problems or looking even at my aura ring and my heart rate variability. You know, when I moved to Maui for the winter, I really noticed over time, I started to see my heart rate variability improve. In other words, my metabolic health, my heart rate all improved as a result of lower amounts of stress by living in Maui. And I was like, wow, this is really interesting. I'm getting more stress proof by simply doing the behaviors like sleeping well and eating well and exercising and meditating and just having a more balanced life than running around like a crazy man like we used to do before COVID You and I both were like that. And it's like, wow, this really is something you can pay attention to and then impact.

Hey, everyone, it's Dr. Mark.

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The Doctor's Pharmacy Daniel what what about the the term exponential medicine this is something you coined what does it mean how do we leverage it to impact our health and how does going to transform healthcare?

The framing of exponential medicine is understand the pace of change. So we mentioned earlier Moore's Law, the power of computing in your smartphone is doubling in performance in half the price every year or so. The fact that our sequencing a genome or microbiome has dropped from millions of dollars to $100, the fact that our internet of things and connected devices are going up at an exponential rate. And just a reminder for those who are not mathematicians, our brains are fine thinking linearly 30 linear steps will be across my house. But if I took 30 exponential steps, 2, 4, 8, 16, 32, 64, by the 15th step I'd be at about 32,000 meters, but by the 30th step I'd be 26 times around the planet, a billion meters. Wow. And that's sometimes the surprising power of exponentials. And so what we need to keep in mind as we look to build our future of health and medicine is what's going to be possible with the next generation of wearables or Internet of Things or 5G moving to 6G. The fact that we're now seeing satellites now from SpaceX, trying to bring high-speed bandwidth pretty much anywhere in the world. How do we think about drones, which 10 years ago were toys, now are delivering drugs and medications? How do we think about gene therapy, which now is accelerated with CRISPR and next-generation mRNA therapeutics? So a bit of the framework of exponential medicine, the conference I chair and founded, is to get people looking at all those technologies, how they come together, and how you converge those to address challenges and pain points and to learn from others that are doing it. For example, we had our friend Leroy Hood there sharing his perspective around precision wellness that ties into a lot of your work and where that might go and how not only to have the technology but how to integrate it in with the payment models and the healthcare systems and the incentives and the policy makers. So that's a bit about the exponential going. And I would argue that many of the things that we had, you know, it was actually 10 years ago this month, I did a TED Talk called Future of Medicine. There's an app for that. And at the time, I think there were 60,000 healthcare apps. Now there are, I don't know, 600,000 or more. But what's interesting is those have shifted from the consumer app for mindfulness or maybe tracking your steps to being medicalized. They're getting paid for. They are becoming FDA approved. Like there's now video game app video games for treating ADHD that are approved or for managing PTSD. And so we've gone from sort of the shiny objects and these are kind of cool widgets to where they're being integrated into care models, they're being regulated, they're being paid for. And that's a bit on this exponential. Of course, as clinicians in healthcare, we're often a little slower to adopt than if it's just a pure video game. Another fun example of an exponential many of us have experienced is virtual reality. You know, six years, seven years ago, the Google Glass was kind of a fun example. But now there's Oculus Quest for $200 and VR can be great for playing video games and putting grandma on a roller coaster, but now VR can be used for therapy to treat pain or for medical education. You go into a virtual operating room and you practice your procedure just like a pilot would be on a flight simulator. So, these are examples of things coming together in surprising ways that we all need to appreciate and leverage into health and medicine.

I think all these things are going to change healthcare and change our approach to our own health. but, you know, being a little bit of a devil's Advocate, you know, we have all these great Technologies, but technology in the end doesn't save us because at the end of the day, it comes down to the simple things that create Health, which are what we eat, how much we sleep and exercise and our stress level and, and a few other simple things like our nutritional status and toxin load and overall health and, and how, how do we get people to focus on those changes? Because right now, as we sort of start out talking about, you know, we have 88 of Americans that are metabolically unhealthy, 75 overweight, six in 10 have a chronic disease. It's driving, you know, one out of five healthcare dollars is one out of five dollars in our economy is healthcare dollars for health care. And about 80 of that is for chronic illness. It's mostly related to lifestyle. So that's the big question, is Behavior change, right? We know what to do, right? I can cure someone's diabetes. It's not hard. Change their diet. The data is there. It's not controversial. And yet It's really hard to get people to do. How do we deal with that? How do we get exponential in terms of behavior change? Right.

Well, comment number one is of course technology only plays a role about 15% of our health and a lot of it are the core elements, you know, food, sleep, social connection, diet, and putting on my pediatric hat for a second since I trained in medicine and pediatrics, we know now that if you give a child at six months of age, not that sort of cheaper white rice, yummy sweet cereal, but they give them whole grain cereal, it changes their microbiome, their epigenetics, and the risk for obesity and diabetes goes down dramatically. So number one, start young. I've got young kids and sometimes they like their sweets, but you try and moderate. But of course now we know, we don't need to be quantified self to know you're supposed to exercise more and eat less, but behavior change is super hard. But what's getting interesting now is we can start to use some of these new tools to become that digital coach that really matches you. The avatar you might want is Einstein. I might want my mother as my coach or and these avatars can feel real even if they're just something living on your phone or through voice. And I think what's going to be part of this element in the future, we're all touching our smartphones and other consumer devices frequently, they can become a bit of our health bubble, kind of like your almost personal health avatar that can give you smart nudges over time to help nudge you in the right direction in ways that match you, right? I'm an INTP, you might be an ENTJ, we might relate to health information differently. If you're a baby boomer versus a millennial, how you communicate, how you have the user interface on the wearable app might be quite different. So I think it's a bit of a blending of all these things to meet people where they are and give them the power of why, right? If you can show them in the mirror, not just you of today, but you of the future, if you keep smoking, drinking, not getting enough sleep, stressed out, that can be a powerful lever and that can be done with augmented virtual reality as well. So I think it's a blending of those tools and now it's a bit dystopian or big brother. There's even insurance companies, health and life insurance companies that will track your steps. And if you're walking 10,000 steps a day, you might get a lower premium. So there'll be other financial and other incentives that come into play.

I think we haven't been asking that question enough when it comes to technology, which is what is the science of behavior change? I think you know, you know, BJ Fogg and others, Charles Duhigg from the New York Times, written about habit change, behavior change. And I think we really are often ignoring that piece of medicine because at the end of the day, if people don't change their behavior, none of these things really matter, right? Because, yes, you can find a Precision way to match this drug to this disease, and that's great. And we need to do that. And wonderful. But when you talk about the majority of what we're suffering from in terms of chronic disease, that's not going to cut it. And, and we, we need to get into the homes of people and, and get out of the hospitals and the clinics and have decentralized Health. Like you said at the beginning, we have a sick care system, a healthcare system. So Health really happens at home. Nigel Crisp who wrote a book called, Health Happens at Home, Hospitals for Pairs. And I think that's a good way to think about it.

Yeah, I actually recently chaired a conference on the future of the hospital with a bunch of CEOs from hospitals. And our takeaway was that the future of the hospital is no longer the hospital. It's increasingly virtualized. It's moving to your corner pharmacy. It's moving to your smartphone. I've been the host of the CVS Healthy Conversations podcast. A lot of it is bringing in other voices that you might not always hear from them. the pharmacist or the pharmacy executive struggling with how do you manage everything from COVID testing to the social determinants elements and equalizing care? Because now we have the ability to connect the dots through this sort of digital connected mobile age. It can happen in our home. More and more patients are being admitted to the home, not the hospital, for maybe a simple pneumonia. And with sort of the technology piece where you know, we when we were medical residents, you remember we keep some in the hospital for an extra day or two just to check their temperature or lab. Now you can send them home with the lab or, you know, a wearable device like this one that is basically an intensive care unit level patch that can stream their, you know, ICU level data and enable you to do a better job of that home based care.

From hospital to home or hospital to home spittal is going to be home spittal.

I like that home spittal. I was going to say, think about what do you have in a hospital? It's usually, you know, an IV pump, which you now can be converted to a smart smart pump at home. Some drugs, which we used to give only by IV or subcutaneous infusion, can go into a robotic pill that you might swallow and inject the biologic into your wall, into your gut wall. Our Wi-Fi now can pick up our vital signs. MIT project by Dina Katabi showed that modifying Wi-Fi can pick up the vitals and behaviors of 10 or more people in the same home. So again, a bit big brother, but we're exuding our digital exhaust 24/7. That enables us not just to do the wellness side, but when folks have an acute or chronic medical condition, you can manage them remotely. Something as simple or common as someone just had a total hip replacement or came home from the hospital with COVID is their wearable device showing that they're walking more, doing better, or walking less? And if you can intervene early on the folks who are walking less before they have a fall or other complication, that could be a big game changer as well. So a lot of the new digital breadcrumbs will come from the home and.

Enable us to do smarter, more holistic, and integrated care. And one of the most interesting things was I was on a flight back from a conference with Mike Rozen and Dr. Oz and they were sharing this phone technology which is a sensor in the phone that detects your voice. And you touched on it earlier, which can tell you what your mood is, whether you're at risk for different problems. And it's just fasting based on the tone of your voice, the quality of your voice. And so we're able to pick up data that's going to inform us about, well, maybe this person is about to commit suicide or maybe this person really needs some help with this or that. And you can begin to really create a system that responds to the real needs of people in real time, which is very different than sort of our one size fits all approach. Well, that whole field of voice is a biomarker.

I mean, the ones that have come up this year are the sound of your cough, is that COVID or a croup or a cold, but mental health can be picked up. I talked to a startup in the San Francisco Bay Area yesterday. They have a way of picking up depression and scoring it based on your voice. And then another advent that's accelerated is digital mental health so they can then connect you to a platform that might help you manage your stress or your anxiety or PTSD or your depression and then have ways of actually quantifying that because mental health in the brain has been so hard to quantify. You can't put people in MRIs every day. Another piece of voice that can pick up signs of early neurologic conditions and given the scourge of Alzheimer's and other neurologic challenges, what if you could detect 20 years before someone's symptomatic that they are likely to get dementia? maybe just like we give a statin for high cholesterol, we're going to start to give some of these drugs that reduce neuroinflammation or can reverse and stop plaques early on in the progression and use these biomarkers from voice to your eye tracking to your omics to actually move the needle on preventing these horrible diseases as well.

Yeah, so true. I think what I want to dive into a little bit is this whole field of precision nutrition. And, I just published a book called the Pegan Diet, which is focused on two big concepts, which is food is medicine. it's a biological response modifier. In other words, it changes every aspect of your biology in real time. And two, personalization. How does the future look to you in personalized nutrition? What will we be doing? How will it inform us? Because there isn't a one size fits-all diet for everybody. So how do we begin to get.

To a closer approximation of what was going to work for us? Well, I think as we start to understand nutrition at the, the true biologic level, which is relatively new, the fact that we can all now where CGM and glucose is one part, of course, how we can start to measure even some people do it every week, their microbiome. And we're seeing new ways to collect your microbiome from other parts of your gut as well. We're seeing the ability now to see the impact on other levels of biomarkers. So I think hopefully it doesn't have to get super complicated where you're quantifying your meals every day, but you get a bit of a best picture look at what's really gonna keep you healthy, optimize your health, whether you're trained to run a marathon or you're trying to reverse your diabetes or reduce your risk of cancer or treat a cancer. So I think the way it looks, it might be along the lines that number one, our smart kitchens might be tracking some of this for us. They maybe can even order the right meals or give you better points for shopping in healthy ways that already exist. But ideally it becomes something that's fun and integrated and much more appreciated. Yes, you can still go and have your fast food occasionally and have that big chocolate cake, but we are understanding its real impact in measurable ways. And we can integrate that into medical education because we don't get much nutrition in medical school. I think I had one hour at Stanford. And make sure it's part of our healthcare prescription. Prescribing a diet, for example, will become much easier and that will be something that will be tuned. And in some cases, we're going to want to modify things in real time. One element since I trained in medicine and pediatrics is like dosing. You might dose a meal, but also dosing your medications. Ideally, we want to have folks off medications, but one technology I developed is a way of sort of 3D printing your own personalized polypills. So, someone who has an asthma, statin, beta blockers, synthroid, vitamin D, you might imagine you could print that pill every morning based on their data or even print the right dose of statin or lasix into their breakfast bar or into their coffee. Amazing. ideally becomes a little less hard to do and you don't need to be a quantified self for tracking every calorie or every cupcake.

Yeah, it seems to me that when I look about and I see what's happening in the future of Madison Nutrition, I think we're going to be able to use a lot of different tools to assess a person's individual needs, their genome, which looks at enzymes. I mean, one-third of our entire genome codes for enzymes and all those enzymes require nutrients or vitamins and minerals. and they require different kinds and different amounts, depending on your genetics. That's just one aspect. You can look at nutritional testing that may be done through saliva or urine or blood or transdermally or through your eye. Who knows? We're gonna be able to figure out and detect what's going on with your nutritional status. Are you alone? This or that nutrient? We'll be able to look at your metabolic features, you know, whether they're, you're pre-diabetic or not, or whether your blood sugar is off or not, and even more subtle things that we'll be able to measure. we have to look at your stool and look at your microbiome, which plays a huge role in how you respond to different foods. So when we collect all this data, plus our, our own family history and our own personal history, and I think it's going to look like a very different landscape where we're gonna be able to see, okay, you, you're somebody who may need to be on a higher fat, lower carb diet. In other words, you might be on a lower carb, higher fat diet, or you do well with saturated fats, and you might not do well with saturated fats, or you might do well with, you know, eating, I don't know, blueberries, and you might not be okay with eating blueberries. And I think that is going to be a, a really breakthrough moment where people can start to get off of the, the Dogma that they're on around what they should or shouldn't be eating and really understand that this is a personalized future that, that both in terms of pharmacology, but also in terms of nutrition and in terms of our own ability to personalize our wellness. You know, Libra Hood calls it scientific wellness. I just call it functional medicine. Dave Asprey calls it biohacking. You know, we call it exponential medicine. Whatever we want to call it, it is what's going on. And, to me, it's one of the most exciting things. And, I've been doing it for 30 years. And, I can see over that time we've gotten better and better at understanding what to look at, what tools there are, how to personalize these approaches. And, when we see the outcomes of those interventions, it's just striking to me when I work with my patients that way. I mean, I had one woman who was, for example, very overweight, struggling to lose that, you know, 20 pounds that she needed to lose. She was struggling because she was, you know, really having terrible lipids with super high cholesterol, super high triglycerides, low HDL, was really having trouble. And she's like, I'm like, I've tried everything. Well, why don't we try a ketogenic diet? So I basically put her on coconut oil and butter, 70 of her diet, and she literally transformed. Her weight dropped off 20 pounds, just like that. She had a dramatic reduction of 100 points in her cholesterol, 200 points in her triglyceride, or HDL went up, you know, 30 points, which is unheard of. It was a miracle. Another guy who was a 50 year old biker who was relatively healthy but wanted to optimize his health, wanted to try ketogenic diet. I'm like, okay, try and see how you do. We checked his numbers and it was the opposite. He got terrible cholesterol particle number, really high, large, small particles, the opposite of what you would see with this woman. So same diet, totally different biological responses. So I think we have to be humbled by the fact that we're just at the beginning of this discovery process. And through these new tools and Technologies, we'll be able to really drive in a much more personalized approach to scientific wellness or health. And, one key part of that is.

The evidence base, right? There's always, I like to drink my coffee. Most of the recent studies saying coffee is good for you, but occasionally you'll hear one where it's not, or vitamin A or vitamin D. And, what's interesting now in a bit of our ConnectedA is that we can all now become members of virtual clinical trials, whether it might be a form of nutrition or a particular medication that's dropped off by drone, and then your apps sense that. I think building the evidence base to match the potential is really critical. And now we can accelerate clinical trials and evidence as well.

Well, let me challenge you on that because in the field of exponential medicine and thinking differently about the future and understanding network biology, our current two tools that we use aside from sort of animal studies are randomized clinical trials, which are looking usually at specific interventions for specific disease in a specific population that may or may not be generalizable using, you know, a statin and 70 kilogram men from Kansas who all, you know, wear overalls, you know, basically it's a perfect study versus the real world where we see all sorts of size shapes, colors, and ages of people. And the second tool we use is public health studies, which are epidemiology. We look at large populations, we see trends over time. And again, those are generalizable to a population, but not to individual and the randomized trials are specific individuals, but not super generalizable in my view. And there was even a great paper in JAMA that kind of talked about this challenge with research in the field of the future of medicine, whatever we call it. How do we reimagine research to be able to look at the complexity of biology and get out of this reductionist paradigm of just looking at the single intervention for a single disease or the single drug?

The one example of that is verily Google spin out in health is doing the baseline trial where they're taking, I think, 10,000 plus volunteers looking at their digital exhaust from their wearables, their genome, their diets, their health history and starting to connect the dots and sort of do a continuous clinical trial to understand health and also see disease in a normal distributed population, at least the normal ones who signed up for the study. I imagine we could all be part of a continuous clinical trial going on. potentially if your food intake is tracked by the future spectrophotometer on your smart device. And so we will start to opt in, I think, into sort of more generalizable holistic clinical trials that using big data and multiple streams of information can give us better, less narrow insights that can apply to precise prevention diagnostics or therapy. So huge challenges. How do you pay for it? what data you do look at. And then even in the form of nutrition, you know, one form of milk is it might be different from another depending on the cow. So I wonder how we can sort of start to standardize some of the nutritional components as well. Yeah, right. Milk isn't meat.

Meat isn't meat. Meat isn't meat, right? So we talked about this in my book and on other podcasts, but you know, kangaroo meat or wild animal meat is very different in its biological effects than feedlot meat where, you know, the feedlot meat raises inflammation, the wild meat reduces it. if you're eating, you know, like you say, milk from sheep, which has A2 casein, it had different biological effects than a cow milk that's A1 casein. And so we, it even gets more complicated about how do we begin to focus on that. But I'm sort of excited about it. And I, and I can tell you the more I dial in what, what I see in my patients data and lab tests, the better their outcomes are clinically. And, and I wish, you know, we had a way to really study that. At Cleveland Clinic, we're doing outcome data on everybody. you know, I wish we had, you know, tons of money to study this. I know there's so much money, like billions and billions and trillions being spent on things like COVID. And it seems like just a fraction.

Of that spent on studying some of these issues in more detail would be so powerful. Well, a question for you related to that. I mean, functional medicine really is this integration of all these different fields. But healthcare still practice amongst specialists that often don't talk to each other. And they just, you know, one specialist for the right arm, one for the left in some centers. How do we better integrate these elements so it's not just your primary care doctor who's trying to struggle to connect all those dots. And how do we make functional medicine truly functionalize for every individual and almost every clinician? Are there are ways you've seen that work? Because not everyone can spend the amount of time and the resources and the.

Experience of Dr. Hyman. How do we create the AI version of you to help all clinicians? That's what I was going to ask you because I agree. I mean, I've had this unique perspective because I've had the privilege of working at Canyon Ranch, which is a health resort. where people were very affluent and also in my own private practice where I saw people from all over the world and they could afford significant testing. And so we would do sort of an experiment. I would say, look, let's just get this data. And the more data we have, the more we'll know about your biology and the more we'll be able to personalize in this approach and help you get healthy. And so I've seen literally millions of data points on tens of thousands of people, and it's all in here. And I can see those patterns in the data, which is what sort of AI does. But, you know, I'm not that smart. And so I'm probably missing a bunch of stuff. And I have also seen stuff that I know nobody else has seen or noticed because I just had so much data. And my dream is to actually get this convergence to happen where we somehow get the right people in the room who can use AI and the right AI programming to understand all this information that's being fed into this big data fields, right, of omics, quantified self, systems biology, paradigm shifts, and can it create a decision support system for providers to say, okay, here's the thing you should think about. Here's a patient with Alzheimer's and based on their history, based on these lab diagnostics, that the likelihood is that they probably have an insulin resistant driven Alzheimer's. Or this patient might actually have Alzheimer's is caused by some latent infection, like Rudy Tanzi is talking about some low grade infection in the brain. Or maybe it's from Lyme disease, or maybe it's from heavy metals, or maybe it's a microbiome issue that's causing brain inflammation. and we'll be able to then begin personalized nutrition and medicine and then come up with the right therapeutics based on those algorithms. That I see coming. I don't know anybody who really is working on it. I've talked to Peter Diamandis and his group working on the sort of personalized longevity programs that they're developing. You know, we've talked to Human Nucleus and folks down there, Craig Venter and his team and now a new team down there, they're trying to get to this. but it's tough. Leroy Hood tried to do this with his study at Arivale. Unfortunately, the business model didn't work, but he really has done this quantified data on 100 people, wants to do on 100,000 people looking at all these variables and what happens when you start to impact these over time. Those are the kinds of things that have to happen for us to really move forward. But I think all the people you know and all the things that are really going on in the world, if somebody who had money could catalyze the research field in this way to kind of put these pieces together that you talked about, it would be transformational. Well, one part of that transformation is.

It has to be part of the, we talked a bit about workflow. We know clinician wants to be looking at all the raw omics. And I even went through the RVL program. It was fantastic, but it was very, you know, very intensive. You had one coach. They still looked at very fragmented sets of your data, your, your genome, your microbiome, your scan, your other element. And hopefully the trick is, and you've told these stories of your experience with heavy metals and mercury poisoning, what if the AI computer decision support suggested for the primary care doctor in rural Idaho that, wow, this patient really keeps not doing well. Have you considered checking the mercury levels or other elements? Sometimes we have so much misdiagnosis, so many folks get to late stage and it's often fragmented amongst different specialists who never see the complete picture. That I think if we can smartly start to integrate that into the workflow and ask those questions, even before you see the clinician, we'll start to move the needle. That's part of that paradigm shift.

It's pretty exciting. I want to get there fast because I see so much needless suffering and there's a huge gap between our current knowledge and current practice. And we hear, you know, average of 17 years for things to get into practice from when they're discovered in the scientific literature or 50 years, you know, doesn't even take a while. And often people are vilified or discounted because of that. But I think we'll get there. And I think your work is just so important because it connects the dots for people and helps them look at the future in a really different way. I want to sort of turn the tide a little bit and talk about COVID with you for a minute because it's really created these unprecedented social economic challenges and given us also an opportunity to think about how to make a difference in our whole approach. So how do you see COVID has been a catalyst for change when it comes to the future of medicine? I have some ideas about that. I'd love to hear what you're thinking.

Well, one lens is that it's forced us to collaborate faster. I've been sharing the XPRIZE Pandemic Alliance Task Force, which has made up some amazing folks like, you know, like from Dean Kamen to the chairman of IDEO to the folks who head up Life Sciences for Intel, but also 100 organizations from small companies to academics to Fortune 50 companies to help address what are the challenges of this pandemic and how do we prevent future ones. Part of COVID as a catalyst has been to accelerate new forms of communication, new forms of data. It's from studying the genomics of COVID patients and figuring out what blood type might be causing more morbidity or susceptibility, all the way to catalyzing new forms of diagnostics. We launched with Jeff Huber, the founder of GRAIL, a cancer testing company. We started and launched and finished an XPRIZE for rapid COVID testing. And that generated 700 different teams from 70 countries. And the winning Teams, some of them were using the basic PCR, but they could make it faster, cheaper, better. Some were picking up ways to use smell as a screening test in various precise ways. Others were using breath and new forms of physics. And so COVID has forced us to be smarter, to collaborate faster. And I think the silver lining of the pandemic is some of these testing solutions we talked about will lead to better diagnostics for many diseases. Certainly we've learned around the vaccine element that it was amazing. January of 2020, we sequenced the virus. A month later, we built the first basic vaccines, mRNA based. We're into trials a month later, and we have vaccines in the market less than a year later. So it's, I think the lessons that we've learned, narrowing the gap from data to insights to action will serve us in the sort of reinvention of healthcare going forward. And it means we all need to use this as an opportunity to break open our old silos and do things smarter and faster.

Totally. And I found also, you know, our practice, we, like many people, when COVID hit, we're like, what are we gonna do? Cause people aren't coming to the office anymore. Everybody's staying at home. So we had to pivot to virtual healthcare. And we were doing some of it before, but we switched basically to running our practice on Zoom, which is pretty amazing. And, and initially almost entirely now people are coming in a little bit, but we, we're seeing that, the silos, for example, between states, now we can treat people from other states with all these artificial barriers that are regulatory. that it kind of limited medicine. Like you have to have a license in every state to treat someone in another state or they have to see you in person. I mean, these are things that have been established and honestly have no really good reason for them. And now we're like seeing, oh wow, you know, we can do really good medicine online. Yes, it would be good to see the patient. Yes, it'd be good to do a physical exam, but I often do good exams online or, you know, I had a orthopedic consult with a patient and I saw the doctor was like, okay, do this, do this, bend here, do this. And it was he was telling her how to sort of do all the moves that would trigger whatever you wanted to trigger. And it was like, wow, you know, we really have to rethink our whole approach to treatment. I also think the decentralization of care, the democratization of care, you know, getting care out of, you know, the clinic and the hospitals just makes sense. And I asked the chief of staff at Cleveland Clinic years ago, I said, where do you see Cleveland Clinic in 10 or 15 years? And I see a Cleveland Clinic without walls, which is exactly what you were talking about before, which is transforming where care is delivered, how it's delivered, what kind of information we're doing. It's really the most exciting time, I think, in medicine. I'm just thrilled. It's just frustrating it's not happening faster.

Well, we do have to still make sure things are safe and effective, but on the telemedicine side, which is exciting, of course, HIPAA relaxes some of its regulations so you could do a Zoom visit, reimbursement models changed. And I think part of our future telemedicine business, now that many of us experienced both as clinicians, as patients, why do I need to go in for that little checkup when I can just do a Zoom chat? But what I think is going to get exciting is before you even see the clinician in the future, you'll have talked to the AI chat bot. Maybe you have abdominal pain and it will ask you 20 questions and figure out whether you really have appendicitis or not. And it'll already know if you had your appendix out or if you're pregnant. Also, when you see the clinician, they will potentially hopefully have, you know, months or years of your digital exhaust, have your heart rate changed through your wearable, your Oura ring. What is your genome? so it will not just be the face-to-face visit, but you'll be integrating that with a whole other set of tools and insights, and particularly in functional medicine, like you say, how's your diet been? How's your bowel movements been? No one can quite remember that, but your smart connected toilet might remember that.

And, I think, part of your virtual visit integrated into what you see on the screen, you know? Okay, so take us forward 25, 50 years. I'm having a problem. Let's say I'm having digestive issues or I'm having memory issues and I walk into the doctor's office or I walk into, what does it look like? I want to go get help. What does it look like? Take us through an experience of a patient in the future and how we're going to come up with a way to treat them. Let's take something a little more complex.

To put together, like an autoimmune disease, something like Lyme disease or rheumatoid arthritis. Often there's many manifestations of that disease that are often hard to put together and hard to measure. so maybe part of the future of diagnostics will be before you even know, number one, before you even know that the problem, it might be like minority report. Wow, you're showing signs of early dementia or rheumatoid arthritis or any other number of diseases. And just like a minority report, they won't throw you in jail, but they'll send you the proactive intervention. It might be dietary, it might be a form of exercise or a video game for your brain. But holistically, before you walk into the real doctor's office or virtual one, I think that sort of digital bubble of data that you've been generating, your digital exhaust, your digitome, will have been synthesized, it will have been analyzed, maybe continuously or maybe in real time just around that question, it might have parsed your microbiome data. And then when it's going to start to suggest a therapy again, it won't be doing it on that average patient from Idaho where wears the blue jeans and drives a truck. It will do it from folks with your same age, your other, your other genomic co-factors, your socio, your environment, and really suggest the precise prevention to help it from progressing or the precise therapy. And in many cases, that will no longer be the sort of more generic, let's say, generically acting drugs, which often have multiple side effects like steroids. They'll be targeted to, let's say, your base omics issue. So the mRNA technologies, which are moving very quickly on vaccines, are going to be applied to treating certain molecular diseases and we'll have much targeted therapies that might even be again kind of printed at home to match what you need. So that's a bit of that touch. I think we'll still need the human in the mix. It's not, you know, your doctor's not going to be replaced by a robot, but the doctor using an AI or a robotic assistant will replace those who don't. And so it's a bit of that combination that's going to really hopefully synthesize these things. So we need to keep the human piece but leverage all these new tools. for proactive, preventative, personalized anytime, anywhere care.

I love that. And, I hope it won't be just rearranging the deck chairs on Titanic and doing the same thing better, which is actually the wrong thing. We have an AI bot, but there's one called AskMD that I've seen and it's very good. If you have a headache, it takes you through a series of questions and at the end you say, okay, you probably have a migraine. You should see your doctor and get these tests or do these potential treatments. But that bot is actually operating off of the ICD-10 diagnostic code system, which is based on the old scientific paradigm of diseases based on symptoms and organs, not mechanisms and causes and systems. So we need an AI bot that does the latter in order to really.

Create an exponential change in medicine, don't you think? Yeah. Number one, yes, exactly. Every disease needs to be sort of recategorized out of its CPT code or narrow bucket. But the biggest potential, I think, is, is you talked about rearranging the decks here on the Titanic. That Titanic was for the super wealthy, unless you were on the steerage. which what's exciting about these new tools is they really can start to democratize healthcare around the planet from rural California to rural Rwanda to the point where, you know, almost everybody has a smartphone that gives you not just access to information but now digital diagnostics, you know, where the camera on your smartphone can take a picture of your urinalysis dipstick and diagnose a UTI or early signs of kidney disease if you're diabetic. It can provide you that telemedicine consult that can drop off by drone that device or vaccine or therapeutic you might need. So that's part of the exciting piece as well moving forward. That's not now we're not all writing the Titanic. We can, you know, as is happening in China, there's a platform called Good Doctor by Ping An that has, I think, 250 million users now getting sort of AI assisted virtual care that then.

Can connect them to human care when they need it as well. Yeah. That's so fantastic. I can't tell you how exciting it is to be alive and a doctor in this time. And because of this rapid transformation, our worlds are going to look very different. in 10, 15, 20 years. I mean, think about it. We didn't even have an iPhone 13 years ago. There was no iPhone. Now it's like, what do you mean? Everybody's got a smartphone on every corner of the planet, pretty much. Right? And it's that level of exponential change.

We'Re going to see in healthcare. Well, I just did the keynote for my Stanford Medical School alumni event last week, and I was realizing when I was a medical student, gosh, almost 30 years ago or so, like, yeah, we didn't have smartphones, we didn't have Wi-Fi, we were still having, you know, slides for presentations. how do we, we couldn't Snapchat or I don't know how we communicated, but now 30 years later, we're still using fax machines. Unfortunately, we still have, I had a cardiac study done about a year ago and I got my result on a CD ROM. I don't even own a CD ROM anymore. So, I know some of the elements of healthcare and practice are so ingrained that we need to break up with the mindsets of medical education, of healthcare systems, of payers or regulators to really bring us to this age of exponential medicine and outside of the realm of the fax machine, which we're still stuck with in many centers. So it takes not just changing and seeing new possibilities, but getting out of our old mindsets as well.

So moving from fax machines to AI bots, that's great. Well, Daniel, thank you so much for your work in reimagining medicine and reimagining healthcare and being a voice for a real change. You've been in the mix of it for a long time and I think you're a voice that really sees the potential for a whole new system and it highlights some of the things that are happening on the fringes that are now kind of moving into the mainstream and anybody who's listening should check out Daniel's work, should understand the importance of really looking at healthcare differently. And check out his new podcast with CVS Health called Healthy Conversations. He's the host and it has all sorts of conversations about the future of healthcare in really deep conversations with great people across the spectrum of healthcare, from providers to policymakers, to health care insurers, to behavioral therapists, to pharmacists, pretty much anybody who is interested in healthcare, you're gonna learn about a different way of thinking about things. And Daniel, thank you so much for everything you do. Thank you, it's been an honor and.

A pleasure, and I'll just close with the thought that we can all be catalysts in the future of healthcare. You certainly have been. There's that famous quote, the future is already here. It's just not evenly distributed. And so it's up to all of us to get out of our linear, it's up to all of us to get out of our linear mindset, get into the exponential one, find the tools and solutions that might match you or your family member with a particular medical health issue and help move those into this future so it comes faster than we might think is possible. Well, thanks, Daniel.

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