The Next Revolution In Medicine: Scientific Wellness, AI And Disease Reversal

Mark Hyman, MD

Dr. Mark Hyman is leading a health revolution—one focused on using food as medicine to support longevity, energy, mental clarity, happiness, and so much more. Mark Hyman, MD is a practicing family physician and an internationally recognized leader, speaker, educator, and advocate in the field of Functional Medicine. He is the founder and director of The UltraWellness Center, Founder and Senior Advisor for the Cleveland Clinic Center for Functional Medicine, a fifteen-time New York Times best-selling author, and Board President for Clinical Affairs for The Institute for Functional Medicine. He is the founder and chairman of the Food Fix Campaign, dedicated to transforming our food and agriculture system through policy.

He is a co-founder and the Chief Medical Officer of Function Health. He is the host of one of the leading health podcasts, The Doctor’s Farmacy with 150+ million downloads. Dr. Hyman is a regular medical contributor to several television shows and networks, including CBS This Morning, Today, Good Morning America, The View, Fox, and CNN.

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Full Transcript

Automatically generated. Please forgive any typos or errors in the following transcript. It was generated by a third party and has not been subsequently reviewed by our team.

Introduction: Coming up on this episode of the Doctor's pharmacy

Dr. Nathan Price: And you can actually forecast the likely amount of time that you have with a healthy brain given your current state.

Dr. Mark Hyman: Welcome to the Doctor's Pharmacy. I'm Dr. Mark Hyman, that's pharmacy with an enough place for conversations that matter and today's conversations about the future of healthcare, about an age of scientific wellness, a revolutionary new way of thinking about how we look at our own biology through the lens of what's really emerging as the principle model that we should be using for medicine, which is systems medicine and biology. And we have with us two of the leading proponents, advocates, pioneers in this field. It is a real honor to have them. Dr. Leroy Hood is the c e o and co-founder of pH Health, which is a nonprofit developing a project called the Human Pheno Initiative based on the science of wellness, which will sequence genes and generate longitudinal phs of 1 million people over 10 years of pheno basically is the expression of your genes. So what your medical history is, what diseases you have, what biomarkers you have.

Dr. Mark Hyman: So it's the expression of your genes. So it's really important not just to look at your genes, but actually what all those genes are doing and how it affects your health. And it's going to help us deliver a totally new paradigm in healthcare based on prediction, prevention, personalization, and participation. It's what Leroy Hood calls the P four model of healthcare, and it's really very aligned with functional medicine and it addresses some major healthcare challenges and it'll improve healthcare outcomes, facilitate brain health, make healthcare more cost effective, reduce the huge burden of chronic disease, promote healthy aging, which we're all interested in, and really lead the way for the US to be transforming health and health innovation. He's founded or co-founded 17 biotech companies, including Amgen, which you might've heard about. It's a big pharma company, applied Biosystem, Rosetta Ave. He's won so many prizes that are given kind of the equivalent of the Nobel Prize, like the Alaska Prize, the Kyoto Prize, the National Medal of Science, and he's the chief strategy officer and professor at the Institute for Systems Biology, which he founded in Seattle, Washington.

Dr. Mark Hyman: And Nathan Price been a long time friend. He's the chief scientific officer of Thorn Health Tech and the author of the Age of Scientific Wellness, which actually both Leroy and or Lee Hood actually and Nathan both co-wrote. He was previously the c e O of and AI Health Intelligence Company that merged with Thorn prior to the I P O. He's named one of the 10 emerging leaders in Health and Medicine by the National Academy of Medicine. Again, no small feat. In 2021, he was appointed to the Board of Life Sciences and the National Academy of Sciences Engineering and Medicine, and he spent a lot of his earlier career as a professor and associate director of the Institute for Assistant Biology co-director with the biotech Pioneer Lee Hood, who we just introduced. He's also as affiliate faculty at the University of Washington in bioengineering and computer science. And he's co-authored more than 200 scientific peer review papers, given over 200 toxic keynotes and including at the Institute for Functional Medicine. And he serve as a chair of the N I H study section on modeling and analysis of biological systems, which is really important because how do we think about the complexity of human biology? And he's also a fellow, the American Institute for Biological and Medical Engineering. So welcome Lee and Nathan,

Dr. Leroy Hood: Pleasure to be here. Thank you, mark. Great to be

Dr. Mark Hyman: With. Those intros basically took about half of the podcast, but it's worth it to let them know who you are. Yeah, I'm thinking about

Dr. Leroy Hood: Down,

Dr. Mark Hyman: Slow down. I mean, what everybody listening should know is that these two men are among the leading thinkers in a revolution in healthcare right now that we've been working on for decades in functional medicine. But they bring the weight of tremendous scientific credibility to a new way of thinking about health and disease that isn't based on just diagnosing and treating symptoms and diseases. But on a very important question, what is the science of wellness and how do you create scientific wellness? In other words, what are the biomarkers, what are the metrics? How do we measure health? How do we not just look for disease? And it's a really revolutionary view, and I always say functional medicine isn't the science of treating disease, it's a science of creating health. So we've seen a real radical shift in our thinking, and I think most people think of wellness as fluffy, as light, as spas, massages, whatever, but not hardcore science.

Dr. Mark Hyman: And I think what's really important for people listening to understand is that systems biology is big. A change in our medical thinking about health and disease as quantum physics was to Newtonian physics. It's a huge paradigm shift. It's a paradigm shift that's equivalent to thinking the earth is flat, to the earth is round, and it really hasn't caught up with clinical practice yet. All of medical organizations, the medical education, our reimbursement system, the way we code, the way we get Bill is all based on this outdated model. And so Lee and Nathan have been re-imagining what healthcare could look like as we start to apply this new paradigm. So tell us, maybe you can start, Lee, how you guys came up with this idea of scientific wellness, how you began to think about biology differently from this reductionist view where we're all just focusing on the bits and pieces and not the whole and how it all integrates as a network and how our body is a biological network or a network of networks. And to be healthy, we need to create balance in those networks. So can you talk about the origins of this concept of systems biology and scientific wellness? Let to hear from both of you on this.

Dr. Leroy Hood: I think the essential feature to understand is that humans are incredibly complex. They have complex systems that interact with one another. They interact with one another at many different levels from an informational point of view and from a organizational point of view. And in thinking about this many, many years ago, it became obvious that there were a number of things that we had to do to deal with complexity. And the most important of it was really what's come to be known now as big data. What is essential in a human being to deciphering their complexity, whether it be a complexity associated with wellness or with disease is having information about many different systems, being able to understand what the organism is, what the human is on the outside as well as the inside. And one major principle that we've really formulated this idea, blood is a window into health and disease.

Dr. Leroy Hood: Your blood base, every organs, they secrete molecules into it. If you can analyze those molecules, you can in a sense begin to understand how all those different organs are with regard to their health state and so forth. I think another thing that's become very important is when you make the measurement on many different blood analytes proteins and metabolites and clinical chemistries and everything, you get an enormous amount of complex data. And the question is how do we deal with that data? And that's where systems biology comes in. And the idea is exactly as you expressed it, mark. The idea is that our body is a multitude of different biological networks that carry out the physiology of a normal individual. And in fact, when you become disease, those networks also become diseased. So what we have to do with systems biology is take the big data information that we can now gather from your blood and so forth, and to place it into those networks and to do it so in a dynamical way so that over time we know how the networks are changing and those networks and their change gives us an idea of the slope of your health.

Dr. Leroy Hood: Are you transitioning into a disease? Are you heading toward wellness? So the integration, then big data of scientific, of systems biology, and I'd say the final initiative is the understanding of how AI is going to be able to deal with this complexity and translate it into meaningful information for physicians. For example, we have the hope in the future that with large language models and digital twins and knowledge graphs, these are all fundamental tools of ai. We'll be able to take the very complex information that comes from your genome and from your genome and feed it into this system and have it identify your deficiencies and for each individual, give us an ordered list of the actionable possibilities that can move us to greater wellness or back from disease to a wellness state and so forth. So those are the fundamental principles and you enunciated them very clearly when you articulated the introduction.

Dr. Mark Hyman: Thank you. Nathan, what are your thoughts on this sort of revolution in scientific wellness and how did you come up with this concept? Because kind of a beautiful way of expressing the hard science behind health, which is something we've not really looked at in medicine.

Dr. Nathan Price: And that's kind of how we thought about it because Lee and I both come in from a hardcore science background into this, but you mentioned earlier the way that people think about wellness. You tend to think about yoga and you think about

Dr. Mark Hyman: Acupuncture, right?

Dr. Nathan Price: Acupuncture, exactly. All these kind of things. And so there's this really interesting nexus between the way we think about medicine or healthcare in the west and how it's thought about in the east. And there's this very interesting intersection about a philosophy of wellness, but taking some of the scientific rigor of the principles of what we have that has defined a lot of western medicine. We get into this in the beginning of the book. And so that's where we came up with this. The term for better or worse, that we chose scientific wellness was kind of to indicate wellness, which is the orientation towards not disease but health. But the scientific moniker was supposed to differentiate or give a sense, that's what we're talking about. And so scientific wellness in that sense then is really just the same principles that we might think of in precision medicine that's trying to take a very deep view into how you leverage all these molecular data and tools.

Dr. Nathan Price: But our feeling is that that is too narrow because the way that that's getting set up, it's still set up around this paradigm of wait till you have some horrible symptom, get diagnosed with a disease and you get this drug. And we're trying to give those drugs more precisely, but scientific wellness says, no, that's not enough. We want to shift the whole orientation so that we're still being precise and deep, but do it early and focus on let's extend your health span as long as possible, reverse disease in its earliest transitions if it arises, and try to never get into those later states to the degree that that's possible. And then the effort around scientific wellness is really to just drive how do we have as deep of a scientific enterprise underneath the wellness paradigm that we've developed under the disease paradigm.

Dr. Mark Hyman: It's amazing. It reminds me of a patient I had years ago that came in and this blood sugar, I think it was one 20 or something, and I said, Hey, has your doctor seen this and have you gotten any advice from your doctor about what to do? And he says, well, yeah, my doctor said my blood sugar is going off, but wait until I get in the diabetic range and then he'll give me a medication. It's sort of the opposite of what we're talking about. It's like, well, if your blood sugar is one 20, you're already screwed When you look at the data, anything over 85, which a hundred is considered now normal, it used to be 110, but if you're 85 to a hundred, you're still having an increasing risk in a linear wave for cardiovascular disease and other bad events. And when you think about what you're talking about as a doctor, what I learned to do was take a medical history, what I could remember to ask, do a physical exam, look for things that I could see crudely that were wrong, maybe get some imaging, a few blood tests, not that money, maybe 20, 30, 40 analytes in your basic chem screen, C, B, C, and then assume that I could kind of figure things out.

Dr. Mark Hyman: And when things go really bad, those things are off, right? When you're kind of in the hospital at the end stage of these processes, you get to see abnormalities, but most of the time you don't see much. And it's kind of a joke because there's billions and billions of chemical reactions every second. And what you are both talking about is really a revolution where we're not just taking a few physical signs and symptoms, a few lab tests. We're talking about literally billions of billions of data points that are going on in your body from your genes to your microbiome, to your metabolome, to your transcriptome, to your proteome. All these things that we're looking at in the Omic revolution and biometrics that we're now going to be able to put in through wearables. And we're going to be doing analytes of things that we haven't been able to measure before.

Dr. Mark Hyman: And so we're all of a sudden able to have enormous amounts of data, but there's no way a doctor can make sense of that because they would have one brain and it's kind of not ai, but it's pretty good eye, but it's not able to sort of measure and track and interpret and analyze a list. You've talked before about these dense dynamic data clouds. You've gave a talk at Cleveland Clinic for grand rounds data. It was really great and you talked about the future of this and shared what you've been learning through some of the work you've done. And so rather than just taking a simple view, you're taking this complex view and mapping out where are people in the continuum of health and wellness. So you've done a number of projects, the Pioneer 100 Group, you're now trying to do a much bigger one with a million people, and you've created Error Valve, which was an attempt to create a clinical model for this. Can you talk about your learnings from the Pioneer 100, which is where you try to collect all this data and make sense of it for people and then give them a plan that's, as you call it, P four P or P four P four, which is personalized, it's preventive, it's predictive, and it's participatory, meaning the patient has to do some of the work.

Dr. Leroy Hood: Well, I think the Pioneer 100, which occurred around 2014, was a study in which we put together essentially 108 of our friends and we carried out a whole genome analysis and we did the blood analytes and we used a Fitbit and we analyzed the gut microbiome and all of these data were integrated together, and it was done in the context of people who understood medicine. So from these data, we identified 3,500 statistical associations and took the most interesting of those associations to the medical literature. And they led us to actionable possibilities to something concrete. The individual that had that particular verte patient could do either to improve their wellness and or let them avoid disease. And during the course of this program, we came up with hundreds of actionable possibilities, and it was obvious with a larger study, we'd end up coming up with thousands of these kinds of things.

Dr. Leroy Hood: What we did learn that was very important was that the fourth P participatory, the need for the patient to take their own health was absolutely critical. And in this pilot study, we had coaches who actually could take these actionable possibilities, prioritize them and discuss them with each patient, encouraging them to move on and carry these things out. And we found that the coaching was enormously beneficial in one, the retainment of these people for the full year that we did it, or nine months that we did it, and two, in causing people to actually carry out these actions and so forth. And that was foundation for us. Moving to airville program that lasted for four years, did exactly the same thing with the same general approach, but generated an enormous amount of data that gave us deep insights into scientific wellness, into aging, into our ability to detect transitions years before the actual disease showed up clinically with the hope that we'll be able to use prevention and or therapy to reverse it at that early and very simple stage.

Dr. Leroy Hood: And that's where we stand today. We have from these two demonstrations, one of 108 and one of about 5,000, an enormously compelling picture of what we can do for an individual if we analyze the genome and the pH. And I just add that the pheno really turns out to be three interesting things. It's one, your personal behavior and the choices you make, and two, it's your environment and how they impinge upon yourself. And I think a really APTT analogy for doing this is a composer writes a tune, right? And it's the player that takes the tune and gives it life and puts passion in it and changes it. And different players change it in different ways. It's exactly the same with the genome and the the genome is your basic construction kit for how human develops, but the pH is the artist and that's your behavior and your environment that play on this genome.

Dr. Leroy Hood: And the three of those things together give you your phenotype at any given point in time. And essentially these measurements are attempting to determine the influence your environment and your behavior of had in making what you are and more important in being able to take you to where we want to go to superb wellness. And I'll just say one more thing. Most people who are well don't realize they've probably exerted only 20 or 30% of their potential for wellness. They can do much, much more in many different ways. And it comes back to how do we persuade patients to actively participate in this process and commit themselves to a future where your health span will equal your lifespan And we think we can move it out into the nineties or hundreds where we can give you an extra 20 or 30 years of healthy life. And of course, the fascinating question is what are you going to do with it?

Dr. Mark Hyman: Exactly. Well, and we know what you're doing with it. Ali, you're 85 and going strong and just building new companies and businesses and writing new books. It's very inspiring. I think Nathan, I think when you looked at the Pioneer 100 study, it was very early on in this sort of space and it was using lots of data information. It was mostly filtered through the human mind to come up with a set of recommendations and guidelines. But now we're talking about something that's even beyond that. So how do you see this progressing where we use these big data analytics and AI machine learning behind the scenes to actually make sense of this enormous amount of data and what's the next iteration of the pH study or the Pioneer 100? Because as a physician who's been doing this for those long, I see all the patterns in the data that I recognize and I can be very good at it because I've had tens of thousands of hours of experience seeing millions and millions of data points and I'm sort of 30 years in, but it's kind of locked in my head.

Dr. Mark Hyman: I can't really share with anybody easily. And I know I'm missing probably 90% or 99% of what actually really is true also, even though I probably see more than most. So I know that there's so much in there and I've seen patterns when I do these really extensive phenotyping of people through all the diagnostic testing and I can see these patterns that are emerging that I've never seen described. For example, I see someone with heavy metal toxicity and I can guess that they have it because I see mitochondrial dysfunction on organic acids. I see for example, methylation problems, low glutathione, low zinc, low amino acids, oxidative stress, and it gives me a clue that there's something damaging these various pathways and it's likely heavy metal. So I can kind of infer that, but I've never seen that written up in a paper, and I'm sure that's just like the of the iceberg. So how do we take the sort of insights that now we're gleaning from this phenotyping, these dense dynamic data clouds of all these biomarkers and actually make sense of it and create a predictive model for people to create a personalized program that optimizes their health and not just as treating disease?

Dr. Nathan Price: It's a great question. So at the very beginning, you're exactly right. There was just pinpricks of information relative to now that you could really deal with.

Dr. Nathan Price: But over the last several years, and maybe we'll come back to this in a little bit, we learned a tremendous amount about the data, published a ton of papers, insights, things we can talk about, and we can come back to that in a minute. But I want to address your forward question of what do we do with all these different kinds of data? And this is where as we talk about in the age of scientific wellness, the reason we think this is so ripe for pushing now is because of these two big features that are happening. There's this massive growth in the amount that you can measure, but at the same time, there's massive increase in how you can interpret those data and deliver it back to people. So for example, one of the things that we've done done recently is to get into digital twins.

Dr. Nathan Price: And so a digital twin is a representation of your body's physiology. And we've done this first for brain health. And so what we can actually do in this case is, and we're going to release a test on this, a product based on this next year. But basically what you can do is you can monitor for a number of these blood measures, your genetics, cognitive assessments and so forth, and you can then run a simulation based on your particular biology. And it's based around the understanding from a physiologic and molecular level what's driving brain health. And you can actually forecast the likely amount of time that you have with a healthy brain given your current state. More importantly, you can go to personalized recommendations for different kinds of things that people can do, some of which are exercise to keep your oxygenation in your brain high.

Dr. Nathan Price: You can get into things like phosphatidylcholine. Turns out that that becomes rate limiting under low oxygen conditions. Latest people are developing dementia, hugely important Vitamin D, very simple one. We could talk a lot more about that one turns out to be very important. There's many, many of these. But the point is that what you can actually do with the digital twins is you can get a representation of a person's individual risk profile and then tailor the precise recommendations. These recommendations are very different person to person. Once you get to four recommendations, only 1% of people actually benefit from what's the best thing the best for in the population. We just did those simulations. So it's very interesting when you do that. And so you get this intense personalization and you can get into the physiology and you can start to make sense of this because you have to take the complexity of all these measures.

Dr. Nathan Price: You can't place that on a person. You have to put that into the algorithms and deliver back simple, actionable information. And then the other side of the coin, which I'll just mention here briefly, is the chat, G P T and all these things that have shocked the world over the last year. The ability now to deliver personalized insights that give you a lot of context and that you can have a back and forth with and you can get access to a dialogue even with what your digital twin is saying or what you're learning about your body. The capability for us to develop personalization on that front is just radically better than any of us thought it was going to be a couple years ago. And so those things together are really pushing us into this new world of where we're going to be able to harness so much more of this complexity than we could have even thought about before.

Dr. Mark Hyman: I mean this tragedy BT there now, for example, I put in all my symptoms, I enter in all my lab data and I hit tell me what's wrong and what to do about it. Would it given me anything useful at this point or is it still far

Dr. Nathan Price: Off? So I've played with this a lot, so maybe I'll jump in on that, but it's pretty much what I do in my free time. I don't do anything else.

Dr. Mark Hyman: You're up by contract. You put it on here on your symptoms. Why you stomach ignorance? I got a head pain. Yeah, so

Dr. Nathan Price: It's partially there. If you use earlier versions like the G P T 3.5 for example, you'll get lots of hallucinations. It's sometimes useful, sometimes not. G P T four is pretty good, except anyway, there's this weird trend. It's not as good as it used to be, and there's a lot of chatter around that on it. It doesn't let you go as deep as it used to. I don't know if it's legal, they're not really ing

Dr. Mark Hyman: Put guardrails on it. Yeah,

Dr. Nathan Price: They put guardrails and various kinds on it and so forth. But as long as if your question is reasonably well dealt with in available text that it's generating from, it can be quite good. And I've used it not just on medical issues, but explained statistical analysis of this kind of data or something like that. And it actually gives back really reasonable kinds of information. Now it's not fully to where it wants to. Oh, and I did see a survey, maybe you saw this as well, they pulled doctors and apparently 60% of doctors are using G P T today right now in the background on things that they do. So I That's interesting. If you saw that survey,

Dr. Mark Hyman: Actually, it was

Dr. Nathan Price: Not totally ready for primetime, but just to say that. Yeah, go ahead.

Dr. Mark Hyman: Well, no, I was at this big medical conference in Lake Nona and they had this guy from Microsoft with I think Prometheus, which was kind a new version of chat G B T. That was four doctors. And they had a case report that they were sharing and they were entering in this case study and it got it totally wrong, and I guessed it immediately. I went and guessed it. I just knew what it was. I listened to the story, but it was basically a patient who had frequent urination, fever, chills, I think maybe had had a history of rheumatoid of strep long ago or something like that, or had a murmur, maybe had a murmur as a sort of part of the exam. It was just a murmur. And I'm like, oh, this guy has endocarditis. This guy has bacterial endocarditis. And the chat, the Prometheus thing said, oh, he is got a kidney infection.

Dr. Mark Hyman: And I'm like, no, he's not a kidney infection. And it was wrong and it was in front of like 500 people. So I kind of wonder, but I do think that the things are changing. So as you've gotten into looking at these enormous amounts of data through the typing of people, when that goes into these machine learning AI models, where is the next step in this in medicine? Are we all moving towards this? Are doctors going to become in some ways obsolete or think it's going to be helping to implement some of the decision support that these tools give? Because personally, I would love to be able to put all the data for my patients in and instead of spending hours and hours muddling over it and thinking about it, trying to remember every study I ever read and what to do and my medical school training, this is going to give me a roadmap to start with and then implement it. How far are we away from that?

Dr. Leroy Hood: Well, I'll make a couple of comments. I think a really important thing about these large language models, which is what G P T and the other things we've talked about is that they have to be educated properly. So if you take a large language model and you expose it to the internet and you expose it to the conspiracy theories and the lying and all of those other things, you have an enormous susceptibility in that device. And my argument is for health, we ought to have a G P T that has only been educated with biomedical data. And we're actually collaborating with a group that has one of those. And what our hope is, is wealth. And part of the education has been to put PubMed into the device, which gives you an enormous amount of data. Now, some is right and some is wrong, and you'll still have to make judgements. But what we plan to do is we have access, for example, to Google's, Google's knowledge graph, and this is a graph that connected roughly 50 different features from the literature. So it's assembled from the PubMed literature, all of the relationships between genes and proteins and diseases and drugs and on and on and on.

Dr. Mark Hyman: PubMed for those listening is just the entire body of peer-reviewed, published medical resources,

Dr. Leroy Hood: Biological information.

Dr. Mark Hyman: Yeah, it's millions of millions of studies.

Dr. Leroy Hood: Well, this knowledge graph has 50 million nodes and 850 million edges, which means an enormous number of relationships. So we're going to put this knowledge graph in this medically educated G T P, and we're going to put in, we're building now a knowledge graph for the kidney. We'd certainly like to put in the knowledge graph for brain health. All of the knowledge graphs and digital twins that we have should go into educating this thing. And then my hope is the following, we'll be able to take the data genome and pH from each individual enormously more complicated than what we did in a avail, maybe 10 times as much data as we had initially, and put it in there and ask it to generate from tens of thousands of actionable possibilities, the ordered priority of actionable possibilities that you as an individual can use to optimize your health or avoid disease or whatever.

Dr. Leroy Hood: And what the AI will actually do is send this information to a doctor, and there'll be two things. The information will have to do, one, clearly explain the actionable possibility and what the doctor and the patient will be expected to do. But two, it's to give the physician the medical evidence for this actionable possibility to assure him or her it's bonafide. And the dramatic result of this is you'll be able to take a family practitioner and make him a domain expert in virtually every field of medicine. It gives you this global reach that you were talking about and the capacity to handle virtually anything. And that democratizes medicine in an incredible way. And I'll argue, we'll never ever get rid of the physician because they're in the end still and integrative factor that we're a long ways from being able to replicate and so forth. But he will have the tools to become a world expert in every field of medicine, really quite a remarkable promise for the future and what it promises for patients. That is the optimization of this wellness and prevention. Nathan and I have talked about, I think is really dramatic.

Dr. Mark Hyman: So how far away from this are we?

Dr. Leroy Hood: So I think we'll begin to see the effects of this within the next year or so as these things get, I mean, we won't have 'em in the full glory for who knows, maybe 10 years is way too long to say, because look what I mean, that 60% of the doctors would use a tool like this. I would've said, there's no way in the world that conservative group of people would ever go into AI like this. And yet, so

Dr. Mark Hyman: They're putting their patient's history in there and saying, Hey, what's wrong? Is that what they're doing? It's amazing.

Dr. Nathan Price: Well, we should probably not over us. It means they use it to some degree. Because the thing about replacing doctors, the line that I really like, I think it's Eric Pels, which is AI won't replace doctors, but doctors who use AI will replace doctors who don't. And I think that is a really good way to put it because it is a tool. And I think it's like today, it's already a super useful tool if you're trying to remember something or if you want to delve into the literature, you can, especially with these particular GPTs that are based around PubMed and things like that, they're already an assist, right? So it's just already a function of how strongly that assist can be made. And I think the doctor's still going to be the quarterback, but your ability to block and tackle and just solve lots of issues with Theis is incredible.

Dr. Nathan Price: And it's not just the LLMs. I mean, one of the really biggest uses that's straightforward right off the bat is getting rid of as many medical errors as possible, right? Because a doctor who's tired, it's easy to, you've got a long complicated name and there's two of 'em that look almost exactly the same. It's pretty easy to accidentally check the wrong box. But if the AI actually knows, well, you said your patient has diabetes and that's a drug, did you actually mean this drug for multiple sclerosis? And that's already happening today, right? Hospital systems have saved millions of lives already by just implementing some of those really simple things. The kind of mistake that's easy to make as a human and a computer won't make. Now vice versa, computers will make the, and ais will make errors that a human never would because they don't understand causality, they don't understand the context. There's all kinds of stuff like the case study that you got, right, that the AI didn't, there's things that it doesn't know. So a hybrid or what we call centar AI in the book, a hybrid approach really makes a lot of sense so you can cover your bases because those two kinds of intelligence, human intelligence and AI actually operate quite differently. And the kind of errors you make are very different. So combining them is powerful.

Dr. Mark Hyman: What you're talking about is definitely going to help transform the expertise of physicians and allow them to practice medicine that's more up to date that reflects the scientific literature that is based on understanding a wide network of biological factors that they haven't been able to consider before. And that's going to be fantastic. But the truth is that wellness health does not happen in a doctor's office. And so 80 to 90% of the things that determine your health actually don't require a doctor. And are things that you can learn about yourself and fix without a doctor's help. And so in a way, this is also going to help, I think disintermediate people from the healthcare system and from doctors because we don't really have a healthcare system. We have a sick care system. What you're talking about is actually a new kind of healthcare system where people are going to be empowered with their own health data guided by these big dense data clouds of their own biological information from all their omics to their blood panels, to things we don't even measure now that we're going to measure to their wearables and biometrics.

Dr. Mark Hyman: I mean, I have a Garmin watch. I know everything about myself, my pulse ox, my heart river ability, how much I slept, how much deep sleep, how much light sleep about my training, P, this is how much time I need to recover. I mean, it's pretty impressive and all that. It's just sitting out there ready to be kind of harvested and used. And so individuals I think are in this moment where they can become more empowered to be actors in determining their own degree of wellness and health and then know when to go to the doctor like, oh, well gee, your creatinine's like five, you better get your ass over to the nephrologist tomorrow. So that's going to for sure be still there. But a lot of this stuff that actually requires a physician isn't really needed. It's really diet, lifestyle, behavioral changes, supplements in other practices that they have access to. So how do you see this kind of being a tool that the individuals and patients and consumers can use in a way that is really going to disrupt healthcare?

Dr. Leroy Hood: Mark, I think you made a really excellent point, and that is the importance of education for the consumer, if you will. And we're doing a number of things in that regard. For example, this past year, an educational team at the Institute for Systems Biology that I initiated 20 years ago to deal with K through 12 science education problems has put together a four module one year course based on two chapters. Several of us wrote in a systems biology and systems medicine book, one on systems medicine, one on P four healthcare. And the essence of this module is to give them the picture that is portrayed in our book of what healthcare is going to be in the future, and to clearly explain the responsibilities they'll have for their own education. And it makes very strongly the point the core of your health is going to be diet, exercise, size, sleep, stress, et cetera.

Dr. Leroy Hood: And these are things you can do about it. And these are tools and devices you can use to measure it. And oh, by the way, there is this more sophisticated medicine of assay your blood and your gut microbiome that can tell us. And by the time students will get done with that year course, I'll guarantee they'll know more about what I think what we think the future of medicine is than 95% of the physicians out there. I mean, this revolution in transforming healthcare from a disease orientation to an orientation of wellness and prevention, I can't stress how important that's going to be in doing two things. One, improving the quality of health for every single individual that practices even partially. And two, it's going to lead to enormous cost savings in the healthcare system by avoiding what costs 86% of our healthcare dollars today, mainly chronic diseases.

Dr. Nathan Price: And Mark, I'd love to weigh on that question as well that you asked because I think it's such an important thing because you're exactly right, because the more and more of what we can call put under healthcare, especially if we start talking about wellness care, we like to say scientific wellness should be the front door of the healthcare system. Most of that effort should be really beyond this maintenance, maintenance of health. And then you get referred back into the disease care system when hopefully early enough that really make a difference, but with some advanced warning. But the ability for us to deliver this really efficiently and low cost, I totally agree with you, is pushing this more and more to the home remotely making it easier. So some of the things that we've done, for example, we've spent the last few years developing essentially painless at-home blood collection device, used to be called the one draw now called the NanoDrop, but that's like one feature of it.

Dr. Mark Hyman: You're not going to go to jail like Elizabeth Holmes with this, are you?

Dr. Nathan Price: Not at all. Yes, exactly. That was my objection to the name change honestly

Dr. Mark Hyman: Sounds like very familiar. It'll be real science. I have gotten into her story, the nanotainer little, yeah,

Dr. Nathan Price: I read the book, I watched the documentary like 12 times. I watched the dramatization one they did of it. It's a fascinating story in many ways, but you can move to home microbiome testing, you can do that in your home, you can get access to this with ais. We developed something called the microbiome wipe to make that as easy as possible for people and so forth. But the whole idea is that we should be able to deliver health information to people in ways that are much more efficient, much more user-friendly, not nearly as expensive, and that people can have a real control over that kind of over their health and be informed by really deep data. I think that's really the key. Coming back to some of these small measurements, and you brought up Elizabeth Holmes and so forth, one of the things that's important is that a lot of people have failed in trying to take traditional measures and miniaturizing them, at least doing a lot of them at the same time.

Dr. Nathan Price: But the kind of things that we're talking about in terms of omics, like a metabolome where you can make thousands of measures, which we're going to do on this device, a proteome that you can do, right? Again, thousands of measurements, those are only ever done on small amounts of blood. So if Lee and I are running something on that in our lab or any of the top labs in the world, you only ever run those things on if you gave them a huge bat of blood, all they would do is take a tiny amount out of it and run it on the mass spec. There's no such thing as running this through it. So you're talking about technologies that are miniaturized already. That's the way that they work. And so there isn't actually a technological breakthrough of any kind that's needed to use this small amount of blood to get those many measurements.

Dr. Nathan Price: The breakthrough is you have to understand how to read the information. But in the modern world, I'd much rather have an information challenge than a technology challenge because the information challenge can actually be overcome by getting access to samples. The AI is the long, and I'll give one interesting example. So think about what happened in genomics. So in the genome initially, one of the traits that we couldn't predict from the genome was height. Now we all know height is heritable, right? If you have tall parents, you have tall kids, if you have short, if you're short 11,

Dr. Mark Hyman: It depends on what you're eating.

Dr. Nathan Price: It depends part on what you're, there's some other factors, but by and large, it's fairly heritable. So in the early days, there's no gene for height and there's no small set of genes for height. But you fast forward to now and height is now the number one trait that we can predict with the highest accuracy. You can capture over 60% of the variants in height by a genome prediction, but that genome prediction requires over 180,000 genetic variants. So it's distributed across this long tail. So one of the things that we don't know yet is how much mean?

Dr. Mark Hyman: You mean SNPs? You mean? Are you talking about SNPs?

Dr. Nathan Price: SNPs,

Dr. Mark Hyman: Yeah, which it's single and nucleotide polymorphism, which in English means you subset out one nucleotide in that gene sequence that changes the function of the genes. So you need 108,000 of these slight little S spelling variations in order to actually predict what's going on. That's impressive.

Dr. Nathan Price: Predict high. But you could see that there was a really interesting paper, and one of the people they included was Sean Bradley, if you remember him. He was a basketball player. He was seven, six, huge outlier. And you look at this and you get a distribution, and he's a massive outlier. If you looked at his genome at birth, you could have predicted that he was going to be crazy tall. So you can do this in the N B A, you can do it in all these different groups. And so coming back to the blood, the thing that we don't know yet is it might be possible once we're able to make say tens of thousands of measurements out of the blood instead of the handful that we do in medicine, we might find that there's a lot of information in that long tail. It's a little harder, not as digital as the genome, but it might be there. And so it's an open question, but these are some of the things that are really fascinating as we go forward, because there might be a ton of signal that will let us optimize health in many ways and look for early warning signs or clear them and so forth. And there is just an incredible amount of data you can pull out of blood that we haven't harnessed yet.

Dr. Mark Hyman: And I think it's really important. I think people, what were we going to say, Lee?

Dr. Leroy Hood: I was going to say one really nice example of polygenic scores and how they can be, they can apply to improving people's health is we were able to look at the polygenic score that is a multiplicity of SNPs that explain a fraction of why you have high L D L, which is a proxy for heart disease and so forth. And we were able to show that people in the upper fraction of those things could only bring down their L D L cholesterol with statins and other chemistry, whereas people in the lower 40% or so beautifully brought down high L D L with just exercise or diet or So I would argue for all of the 150 or so polygenic traits, we have many toward disease. We're going to want to treat low risk people differently from high risk people. And it's going to be important for everybody to know those risks.

Dr. Mark Hyman: Well, that's the personalization

Dr. Leroy Hood: Aspect and everyone's doctors to know those risks,

Dr. Mark Hyman: Not like one size fits all. Right, now you've got a high L D L, you got a statin, boom. It's not very nuanced. It's very rudimentary. One of the things that actually concerns me is how these AI machine learning models will be trained. Because when I was at Cleveland Clinic, I met this guy who developed Watson, which was the I B M AI supercomputer. And the big thing was Watson went to medical school. I read all the medical textbooks, I read all the medical literature, and in my mind, I went up and said to this to the guy, I said, listen, this is great, but you're going to be just doing the same things better. It's like you're going to be basically having a better mousetrap for the same kind of medicine, which is disease-based, organ-based ICD 10 disease classification system diseases, which isn't actually a true reflection of how biology is organized.

Dr. Mark Hyman: We're an ecosystem. We're a network of biological networks. It's not the typical diseases that we think of that we should be looking at underneath the mechanisms and the root causes and the things that go wrong. The hallmarks of aging are much more approximate than understanding of what's really going on in the body. And so I'm like, well, this is great, but it's going to help diagnose conventional problems better and have a better application of conventional approaches, which to me is just doing a better approach to, I don't know, the earth is flat kind of thing. It's not actually changing things. So I wonder, second, my question is how do we avoid that and how do we train these models and AI in the assistance biology, assistance medicine, functional medicine approach to actually know what to do with the data? I see the same data as traditional doctors, but I see very different things when I look at them. I

Dr. Leroy Hood: Think the really important point is with phenomics, we're going to give billions of features of the individual to the ai, and it's going to sort through a dimensionality of information that's staggering. And reading textbooks is one thing that's metadata, that's descriptions at very high levels. Your data is the core of what you are, and AI is going to be able to extract that essence and translate it into the actionable possibilities that'll actually benefit you enormously. And the other point is you'll have to train the AI properly. And it isn't just reading medical textbooks or not, it's using knowledge graphs, it's using digital twins, it's using all of these kinds of things.

Dr. Mark Hyman: Yeah, I mean, let me give you an example. Maybe we can play off this because for example, let's say a patient comes in with psoriatic arthritis and from a traditional point of view in a diagnosis, they have these kinds of lesions. You can diagnose it with ai, interpretation of skin pictures based on their medical history, joint exams, et cetera, et cetera, certain blood tests, and it'll say, okay, this is what you've got psoriatic arthritis and autoimmune disease, and here's the catalog of drugs you get to choose from and the therapies, steroids, creams, biologics, whatever. And you're going to get that recommendation. Now, when I see that patient, I think of different things. What is the cause of their inflammation? And in psoriatic arthritis, after decades of doing this, I've learned that it's a few things that aren't typically considered. One, it could be environmental toxins like heavy metals.

Dr. Mark Hyman: And I've seen completely clear up with just getting rid of heavy metals in the body. I've seen it be from, for example, gluten sensitivity, which is maybe diagnosed or undiagnosed celiac or gluten, non-celiac gluten sensitivity. And removing that helps. I've seen it be the result of an overgrowth of bad bacteria or fungus in the gut, SIBO or SIFO and severe leaky gut and a disruption in that barrier that drives these symptoms. And my approach would be very, very different depending on which of those problems a person had. And so what I always say is, just because the name of the disease doesn't mean what's wrong with you. And so how is this new framework going to be drawing on that kind of knowledge? And I guess some of this knowledge toxins or leaky gut or gluten are there in the literature, but they're things that are completely ignored by traditional doctors in healthcare because they don't fit in the paradigm. It's an outlier. So it's like we don't know what to do with that. And so it's like, let's just stick with our lane. And so what I'm wondering is how do we kind of use this new phenotyping to give us the right information, the right plan for the person, instead say, oh, you have psoriatic arthritis. Take this drug.

Dr. Leroy Hood: The really key point is all of those things will be reflected in the pheno and you'll be able to read those things. And even in a simple way with a avail, we had people that had extremely high mercury level and we were wondering where that came from. And the most common cause turned out to be people who ate a lot of tuna sushi. And those are simple kinds of correlations that the observation in the blood says you've got high mercury and there'll be a whole series of conclusions you can draw. And so too, having parasites, having all sorts of different environmental exposures or your own self choices, those will all be reflected in your pH, and those will be read by an instrument that will in time become increasingly sophisticated. I'm not saying they'll start out that way, but they'll take in more and more data as these things are learned.

Dr. Mark Hyman: So you're saying basically the AI and machine learning itself will sort out what's true and will help to distinguish earth's flat world from an earth is round world, even though give major

Dr. Leroy Hood: Symptoms, diagnoses, and it'll make hypotheses, but someone like you, that's why we need the physician as a part of the system and the physician himself will be training ai as you say. No, wait a minute. Here are three other explanations I've come across,

Dr. Mark Hyman: But those two other explanations are not things that traditional medicine now even considers. They're things that on the functional medicine systems medicine folks are doing, but it's just like they don't,

Dr. Leroy Hood: No. But functional medicine can feed into AI just as certain as traditional medicine.

Dr. Mark Hyman: Interesting. I think

Dr. Nathan Price: One of the,

Dr. Mark Hyman: What do you think, Nathan? I know this is hard questions, but you guys are smart. So I'm asking the hard questions. I

Dr. Nathan Price: Think it's a really good question. So a lot of it has to do with how you set these things up. So the ais, there's many, many ways you can set up ais, but as long as it's really focused on, like you were saying, diagnosis, here's the steps and these are the buckets, and we're just trying to optimize this information we have down to these buckets. You're exactly right. It's not going to know more than that. It's just going to do that. So partly what I think is really important is that we go down a layer to where we're really trying to understand the biology behind it. And I think this is where you're getting the biology and also lifestyle. And so some of the things that we really want to say, and this is partly what we get into in the age of scientific wellness, because our understanding of genetics, genetics is all based around disease.

Dr. Nathan Price: So we understand all kinds of things about the genetics of disease, but we need to understand the genetics of health and we need to understand the molecules of health and things of that nature. So one of the elements, and Lee was getting at this with the kind of large scale genomic data that you can get from metabolites and proteins and going to these much larger numbers of measures out of the blood and so forth, is we should have modules that are looking at things related to your health, systemic inflation, how much information is packaging between or molecules are getting from your gut into your blood. And you can look at that. How much of an integrity do you have in your blood brainin barrier and so forth. So you're basically going down and now you're trying to develop these modules that are related to different aspects of the function of the health of all these different biological systems.

Dr. Nathan Price: And so you're not just trying to learn, okay, what's my diagnosis? You're actually looking at the function towards homeostasis of multiple different elements At the same time, and this can be quite surprising and insightful when we did this, I mentioned we built these models for brain health, for example, and it was really about that trying to understand how does the brain maintain homeostasis? And so you're using a certain form of AI to do that. And most of those papers and the things that we put in there and the data that we called was not data about Alzheimer's disease. It was data about health, was data about how does the brain stay alive? What are the things that it has to satisfy? How much energy does it have to make? How does it take out the trash? How does it do? And get very much more technical if we wanted to.

Dr. Nathan Price: But there's all kinds of things that are in there and it can lead to surprising outcomes. One thing that crystallized that was pretty interesting is that as your neurons tend die, and a big trigger for that is low oxygen, and then a p o e four, it turns out that when you put these things together, you want to keep cholesterol levels and these supporting cells astrocytes really low. And a p o e four, which gives you high risk for Alzheimer's, will transport that cholesterol out of asteroids, but it's slow so that concentration stays high. A o e two will do it quickly so it stays low. Those two facts together will predict for you the age of onset of all the different genotypes and when they get Alzheimer's. So then a surprising thing happens is as those neurons die, you have to secrete a molecule to recruit additional synapses in order to keep your brain functioning.

Dr. Nathan Price: And what's the molecule that the body uses? Amyloid beta. And so beta amyloid then, rather than being thought of as the cause of Alzheimer's, where we've spent, I got a quote from a guy the other day, I have to go verify it, that we've spent over a trillion dollars on, he was pretty good pharma source, but I haven't verified it, but I've been using 300 billion as my super conservative estimate, but somewhere in that range. So with that amount of money, 450 failed clinical trials. We have a couple that have kind of help a little bit right now. But the point is that by mistaking cause and consequence, by not understanding homeostasis, not understanding, I think the essence of that disease and putting it into a structure that's set up to operate on this one drug paradigm like it does, and it does that well, but it's aimed at a certain thing that causes a massive problem.

Dr. Nathan Price: So that was an area where we went into an AI and you start piecing all these different things together. It explains why statins look like they're good for the prevention of Alzheimer's in observational studies, but bad for Alzheimer's. When you look at A R C T with M C I, we could get into details on that, but you can sort these kinds of things out. So anyway, all that to say that we could go through examples, but as you start moving from, okay, I'm just doing a diagnosis to, I'm going to break down all the different biological modules and try to understand them in depth and then arm, depending on which situation you're in, either the person in their home, if we're talking about wellness or the physician in the hospital system if we're talking about disease. But you can inform that by this basic biology informed by this really deep phenotyping. So it can be incredibly, incredibly powerful. And we could go anyway on and on about how you set up these different kinds of ais because it gets really rich, actually.

Dr. Leroy Hood: But I think your early point mark was really an important one. You have to take these data and put 'em into a systems biology context that gives you causality. Okay. That's the really important point. And that's, as Nathan said really nicely, what's going to differentiate out what these large language models can do from what I B M did where it had the wrong set of data. And I think the other major mistake that I B M made is it was all done by engineers who thought they knew what doctors needed and they didn't. Frankly,

Dr. Mark Hyman: I think the difference between cause and consequence is really critical. And I always say functional medicine is the medicine of why not what? And it's based on mechanisms and causes, not symptoms and location, which is what traditional medicine is. And this is the revolution you're talking about. And I think I importance to understand what are the root causes of disease, but also what are the causes of health and what are the features of health? And I think the hallmarks of aging, which is a sort of a new heuristic to understand what goes wrong as we age that are underlying all diseases, the things that actually are the root cause of the dysfunctions that lead to symptomatic disease. Things like nutritional sensing problems, mitochondrial issues, damaged proteins, stem cell exhaustion, zombie cell formation, the senescent cells, the shortened telomere, the increase in inflammation, the microbiome changes, the altered cellular communication, inflammaging, all these things are things that are described in functional medicine as root causes that if we treat those, the diseases get better.

Dr. Mark Hyman: And the argument is we treat diseases. We may extend life by five to seven years. If we treat causes, we might get 30 or 40 years. But there's also an interesting paper that I am not sure if you both saw in cell in 2021 that talked about the hallmarks of health. And they sort of break it down into very similar framework, which is first we have to do is be able to maintain homeostasis. We have to be able to respond to stress, and we have to actually make sure things stay in their right location and don't have a leaky gut or a leaky brain. And their hallmarks of health are the homeostatic resilience, hormetic regulation, repair, and regeneration, which are response to stress, the maintenance of homeostasis, which is how do we recycle and turnover parts that we need? How do we integrate different circuitries of communication?

Dr. Mark Hyman: How do we have a balance in a rhythmic oscillation and circadian rhythms? And how do we compartmentalize things spatially with making sure our intestinal barriers and our brain barriers and communication systems are right? And how do we contain things that are bad things like allergens or toxins or microbes from affecting us. So this hallmarks of health framework is really interesting and I think it's a very different way of looking at and modeling what's going on to actually define what is scientific wellness? What is the measure of wellness? Oh, I know how to diagnose diabetes, I get your blood sugar and if it's over 126, you're diabetic. But gee, what do I measure to determine if you have a high level of scientific wellness, what are the things that you're looking at that are the most important things to determine that?

Dr. Nathan Price: Yeah, I love that We've referred to these typically as metrics.

Dr. Mark Hyman: Are you familiar with this paper? Are you familiar with this paper? Yeah.

Dr. Nathan Price: Yeah. It's the

Dr. Mark Hyman: Hallmarks of Health paper,

Dr. Nathan Price: The Hallmarks of

Dr. Mark Hyman: Health. It's interesting, right?

Dr. Nathan Price: And it's exactly along the lines of what we're talking about because, and this is why we've talked about needing this enterprise of scientific wellness to establish markers and models and the deep science behind health so that you don't go in and you just get a test for disease or not, because this is exactly what I think the health checkup of the future, whether it's at home or in office should look like, which is how good is your body at dealing with oxidative stress? What's your glucose control actually look like? That one's easy now because we have CGMs and so forth, how robust is, yeah, exactly. The integrity of your intestinal lining is your gut microbiome, healthy, et cetera, et cetera. And so defining what those are is I think in many ways the central effort of scientific wellness because those are the kind of things that I agree with your other point, which is if you can optimize those as you go along and you don't go down into their disease pathways, you're just much, much more likely to gain a lot.

Dr. Nathan Price: Because once you're down the disease pathway in a long way, coming back to Alzheimer's, just as an example, once you've lost a bunch of your neurons have died and billions of synapses are gone, there's no notion that you can have a small molecule drug that's going to regrow those back. There's no chance of that. But prevention, right? Thinking about, okay, what do I have to do so that my brain cells don't die in the first place is a much more doable. And we wrote this piece on Alzheimer's prevention for the LA Times a few weeks ago that goes into some of that. But basically those two problems like the regrowth of your brain after it dies and the prevention of it from dying are not in the same universe in terms of complexity and in terms of your likelihood of being successful. And so you've got to think about how do we stay healthy, stay away from those boundaries where you're going to cross some irreversible threshold and stay as healthy as possible. And things like those metrics for health, that's a bridge to get there.

Dr. Leroy Hood: I'll make a quick point on metrics for health. And that is in the Airville program where we had people ranging in age from 91 up from 21 to 97, we were able to determine parameters from looking at blood analytes that gave us an algorithm for biological age. That's the age your body says you are, as opposed to your chronologic age. The further your biologic age is below your chronologic age, the more he your aging. And what we showed in the airville program was that for women, for every year they stayed in the AFA Scientific Wellness Program, they lost a year and a half of biological age, and for men it was 0.8 years. And the important point is here is a metric that allows you to assess aging. Here is a metric that in a sense allows you to assess wellness, and it's the integration of a whole series of measurements in the blood that culminate in essentially one. And we're going to be looking in the million person project for tens if not twenties, of these summation products that can look at integrated sets of networks and their behaviors. And of course for aging, it's an enormously integrated set of networks you're assessing, but you can get single measurements that give you very, very deep insights. And these are the things that are going to be the gauges for assessing wellness in its many different dimensionalities.

Dr. Mark Hyman: And the quantitative sophistication is going to get more and more. Right now, for example, Ariel, I'm sure you weren't using D n a methylation, you're using other intermediate biomarkers that you sort of aggregate and come up with a biological age estimate, right? And now we'll be able to use other biomarkers like D n a methylation or other measurements like telomere length or the age of our immune system, and actually have a very much more robust picture than even what's available then. So this is accelerating so fast, it's exponential,

Dr. Leroy Hood: But methylation will never give you suggestions about how to improve your education, your aging, whereas the metabolic analysis from the blood do give you insights into things you can do to improve your aging. So these different things give you different capacities.

Dr. Mark Hyman: That's really why I created and co-founded Function Health, which is a testing platform to get your biomarkers interpreted through ai, through the lens of functional medicine to help you personalize and see what's going on and at this sort of rate of dysfunction in your body where things that we weren't looking at very often. So it's very powerful. Now, I know both of you are younger than your biological age. Nathan, you're in your forties, you're about 10 years younger. Lee, you're 85 and are 70 years old biologically. I actually recently saw an article about you and read it in a Popular Mechanics, which is an interesting place to read an article about you Lee, but talking about your own health routine. So you've been deep in the weeds on this. What have you come to as a synthesis for your own program for how to actually live in a way that is about scientific wellness and that is about reversing your own biological age?

Dr. Leroy Hood: Well, I would say that

Dr. Mark Hyman: Because Nathan still looks like he's 12, so I think I want to your perspective, I'm waiting for

Dr. Nathan Price: People to say that after I'm 50, which isn't so far away,

Dr. Leroy Hood: Well, I would say that I fundamentally agree that the core set of things for health, namely diet, exercise, sleep, and stress, I really believe ways to mediate them for exercise. I was an athlete, played football in high school and college. I've exercised my entire life, vigorous exercises, and it's a way of my life. I do it virtually every single morning. I spend 40 minutes and I do intense aerobic exercises, like 150 pushups and a hundred sit-ups, a hundred deep knee bends to exercise all the deep muscles. And that's really important as you age, because

Dr. Mark Hyman: Well, you do 150 pushups all at once.

Dr. Leroy Hood: No, I do 'em 80 at the beginning of my routine and 70 at the end of my routine.

Dr. Mark Hyman: Wait, you can do 80 pushups straight?

Dr. Leroy Hood: Absolutely.

Dr. Mark Hyman: At 85 years old, that's unbelievable. That's unbelievable. I mean, I can get to about 70, but I'm younger than you.

Dr. Leroy Hood: Well, but you haven't done those kind of things. So exercise is a big part of my life. I'll tell you on the diet, it's all the classic things, vegetables and fruit and low on the gluten kind of thing. But I think what has been a real, I ballooned up to 195 pounds at one point in my earlier career, and I've used intermittent fasting to painlessly bring me down to, I weigh just about what I weighed when I played high school football now. Oh, wow. I'm in terrific shape. So I think intermittent fasting where you eat it in the evening and not again until noon the next day, and then dinner, so you do your eating in an eight hour window rather than a 16 hour window. But the other things I do balance out my bloods, all these chemistries that you've talked about in the blood, I try and I have two genes of block the uptake of vitamin D. So I have to take mega doses, 5,000 international units just to keep it at a normal level and everything. And there are other chemistries that are being explored that block aging and so forth that I think are going to be very intriguing to look at in the future and all the things we've learned, the actionable possibilities where they're relevant. I've tried to adopt those and use those, keeping your blood cholesterol down. I have a terrible family history of heart attacks in the fifties for my three previous generations, and so I've made it well past the fifties.

Dr. Mark Hyman: Yeah, clearly with a

Dr. Leroy Hood: Subset of the genes my ancestors had. Anyway.

Dr. Mark Hyman: That's amazing, Lee. I mean, I think you're a testament to what's possible. I mean, you're clearly sharpest ever. You're doing 150 pushups a day, that's a lot. And you're continue to produce your life's greatest work, and I think the best is yet to come. I think for you guys. That's

Dr. Leroy Hood: How I look at it with Nathan. I think we both look at it exactly the same way. And Nathan is in his infancy. He's got a long ways still.

Dr. Mark Hyman: He's a baby. So how did you get 10 years younger, Nathan?

Dr. Nathan Price: Yeah, so the routine that I've been following that's been working for me pretty well. I mean, there's all the usual things that you have to do, right? There's a mix of aerobic and weight training and so forth. The things that I've really found that have been working well for me, especially lately, and this is the kind of advice you hear all the time, but just focus on things that you think you can do forever. Had a number of times when I've gone on, I tend to go really intense, and then I heard something slack off. And so the things that I've been doing that have worked really well for me. So one on diet. So I also do the intermittent fasting. So I rarely eat before noon workdays. I tend to fast till about two o'clock. If I'm at home, I tend to fast till 1130 or so.

Dr. Nathan Price: I usually eat a little earlier if I'm at home, but so I'll eat a little bit later. I tend to have a relatively small meal, and I'm very consistent about lunch or breakfast. If I'm at home, I pretty much every day will eat plain Greek yogurt with blueberries and a little bit of oats in there, and I put a little collagen in coffee. And so basically what that does for me is it gives me 80 grams of protein to start the day and with a little bit of other things, and I'll take my various supplements, maybe I'll talk about it in a moment. And so that works well for me and for me, it works well. And then I save my larger meal for dinner Data is probably that. It's probably better to do it the opposite, but I much prefer just from preference to do it that way.

Dr. Nathan Price: And so I'm generally in a calorie deficit because I'm trying to lose a little bit of weight. So I'll eat 500 ish calories for lunch and about a thousand ish for dinner typically. And then the thing that's been really helpful to me that I got from a nutritionist, it's been very helpful, is to try to use this rule of thumb on protein. And it's probably a little higher than you need on protein, but especially if you're in a calorie deficit, I think that's good is that if you take the number of calories and you drop a zero, then that's your target for the amount of protein you'd like to see. So in my Greek yogurt, so anyway, so if you have 300 calories, you'd like to get 30 grams of protein as part of that 300 calories. It's a little on the high side, but for me, that works really well.

Dr. Nathan Price: It's partly in a calorie deficit and partly because I probably don't track every single thing that I eat. So you probably have a little bit of, so it gives you a little bit of leeway there. But like Greek yogurt for 300 calories of Greek yogurt's, about 60 grams of protein. So I actually start much above that level, and it gives me some room to come down as I eat a little bit of fruit or something like that during the day. That has helped a lot. And so far this year I'm down about 20 pounds, and I've also gained 5% of muscle at the same time. So it's been working pretty well for me by

Dr. Mark Hyman: Exercising my

Dr. Nathan Price: Exercise, by exercising my also exercising, yeah, so I do resistance training. So I work out, I do my weight training on days that I stay at home. So I work in the office three days a week. I have exercise bands in my office. So when I get a little tired in the afternoon, I do just kind of some extra resistance training in the office when I'm there. And then in the morning I'll do yoga on days that I go in. So I do something kind of easier. And I don't do super long yoga. I like to do yoga with Adrian on YouTube, so I just do her routine. So I do that in the morning before going in. And then when I'm home, I alternate between weightlifting and running. I find that to be really easy because, and then if I'm, I'm commuting in, I walk for an hour, so I at least get that, and then I'll do running on days I'm home. So my routine is set up in such a way that it's very enjoyable for me, and it's pretty easy for me to do. It's easy to

Dr. Mark Hyman: Stick to it. Well, it's happens. It's just kind of

Dr. Nathan Price: Reinforcement. I can do it forever. And between my bedroom and my bathroom, I have a pull-up bar. And so I do pull-ups there, and I can do pull-ups in between. So if I need to go to the bathroom there, I do a few pull-ups. And so that's worked in, so where I watch if I'm going to watch a show or something in the evening, the other thing I keep by, there's two places in my house, I'll do this, and I keep forearm exercises there. So there's this device that you push your fingers out, and then there's a hand device, and those are just sitting there. So if I'm sitting there doing that, so I do those every day. And then in the two rooms where, yeah,

Dr. Mark Hyman: Grip strength is a huge thing, correlate with longevity, believe it or not. Yeah,

Dr. Nathan Price: I know that. That's why I started it. So I do grip strength exercises almost every day because they're just sitting there. And the other thing I do is if I'm in one of those rooms, we also have a small trampoline in each of those rooms rather than sit, I can just do whatever on a small trampoline and so forth. So what I've tried to do is just peel as many little things into my daily routine such that a little is better than nothing. And then on days I stay home, I reserve those for my bigger workout days because I have the extra time because I'm not commuting for two hours.

Dr. Mark Hyman: Well, I think that's key. It's making the healthy choice and the default choice, the default choice and the easy choice, right? If it's hard, you're not going to do it. I'll

Dr. Leroy Hood: Add one more thing about what I do. I do walk to work a mile each way back and forth, and it's actually a reasonable uphill slog going home. But what I take in a vest are two grippers and the entire two miles I'm walking, I'm doing the gripper thing. That's great. So I'm a firm believer in, if your hand strength is great, you're aging well.

Dr. Mark Hyman: There you go. Well, you guys are both inspirations. I mean both in terms of your own personal routine and what you're doing, but more importantly, paving the way for radically new different way of thinking about health and medicine and disease and pioneering something that I think is going to be the future of healthcare. And I think everybody should definitely get a copy of the Age of Scientific Wellness. It's an amazing book. It's a subtitled why the Future of Medicine is personalized, predictive Data, rich and in your hands. It's available everywhere you get books. It's really an important book. I think it's one of the most, I think, important books in medicine in the last half century because it maps out a future that we're all going towards, whether we realize it or not. And I think every doctor should read this, every healthcare administrator should read this, and certainly every person who has a body, which as most of us should read this.

Dr. Mark Hyman: So I think it's really an incredibly important book, and I really look forward to working with you both on this. I think it's such an important project to map out the pheno and create ways to actually create predictive models based on the emerging science and systems thinking. So God, thank you so much for being born, for doing this work, for Paving The Way for so many of us. I feel like we've left a thousand topics on the table, but they're all in the age of scientific wellness. I encourage everybody to grab a copy. If you've loved this podcast and learned a lot, please share with your friends and family on the social media. How have you optimized your wellness? How have you measured your own scientific wellness? We'd love to learn from you and subscribe right to your podcast, and we'll see you next week on the Doctor's Pharmacy. You

Dr. Leroy Hood: Too,

Dr. Nathan Price: Mark. Thanks so much. Mark.

Closing: Hi everyone. I hope you enjoyed this week's episode. Just a reminder that this podcast is for educational purposes only. This podcast is not a substitute for professional care by a doctor or other qualified medical professional. This podcast is provided on the understanding that it does not constitute medical or other professional advice or services. If you're looking for help in your journey, seek out a qualified medical practitioner. If you're looking for a functional medicine practitioner, you can visit ifm.org and search their find a practitioner database. It's important that you have someone in your corner who's trained, who's a licensed healthcare practitioner, and can help you make changes, especially when it comes to your health.