Inside the New Era of Precision Medicine: Where AI and Human Insight Unite

23:35Dr. Mark Hyman:Yeah, they put guardrails on it, yeah. They put guardrails and various kinds on it and so forth. But as long as your if your question is reasonably well dealt with in available text that it's generating from, it can be quite good. And I've had and I've used it, you know, not just on medical issues, but, you know, explain statistical analysis of this kind of data or something like that. And it's 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 polled doctors and apparently 60 percent of doctors are using GPT.

24:10today right now in the background on things that they do. So I said, if you saw that survey. No, but it was actually not totally ready for prime time, but just to say that. Yeah, go ahead.

24:22Dr. 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 of a new version of like chat GBT that was like, you know, for 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. Like I wouldn't guess it. I just knew what it was because I listened to the story. But, you know, it was basically a patient who had, you know, frequent urination, fever, chills, you know, had had, I think maybe had had a history of rheumatoid or of strep long ago or something like that, or had a murmur, maybe had a murmur as a sort of part of the exam.

25:06Dr. Mark Hyman:And 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's got a kidney infection. And I'm like, no, he's got a kidney infection. And it was wrong. And it was like in front of like 500 people. So, you know, I kind of wonder. But I do think that, you know, the things are changing. So as you've gotten into sort of looking at these sort of enormous amounts of data through the phenotyping of people. You know, when that goes into these machine learning AI models, like, you know, where is the next step in this in medicine?

25:45Dr. Mark Hyman:Are we all kind of moving towards this? Are doctors going to become in some ways obsolete? Or are they just going to be helping to kind of, you know, 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 and thinking about it, trying to remember every study I ever read and what to do in my medical school training, like this is going to give me kind of a roadmap to start with and then implement it. How far are we away from that? Well, I'll make a couple of comments.

26:14I think a really important thing about these large language models, which is what GPT and the other things we've talked about are, is that they have to be educated properly. So if you take a large language model and you expose it to the internet, 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 GPT 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 we'll, and part of the education has been to put PubMed into the device, which gives you an enormous amount of data.

27:11Now some is right and some is wrong. You'll still have to make judgments. But what we plan to do is we have access, for example, to 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.

27:45Dr. Mark Hyman:PubMed, for those listening, is just the entire body of peer-reviewed published medical research. Biological information. Yeah, it's millions and millions of studies. 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 GTP. 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.

28:37And then my hope is the following. We'll be able to take the data, genome and phenome from each individual enormously more complicated than what we did in Aravail. 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. 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.

29:32But two, it's to give the physician the medical evidence for this actionable possibility to assure him or her it's bona fide. And the dramatic result of this is you will 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 an integrative factor that we're a long ways from being able to replicate and so forth.

30:26But 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. So how far away from this are we? 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 them in the full glory for, you know, 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.

31:18I would have said, there's no way in the world that that conservative group of people would ever go into AI like this. And yet -

31:27Dr. Mark Hyman:So they're putting their patient's history in there and saying, hey, what's wrong? Is that what they're doing? Yeah. That's amazing. I know we should probably not over, over us. It means they use it to some degree because the thing about like replacing doctors, the line that I really like, I think it's Eric Topol's, which is, you know, 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, it is a tool. And I think it's like today, it's already a super useful tool. Like if you're trying to remember something or if that, you know, if you want to delve into the literature.

32:04It's so, you know, you can, and 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 is still going to be the quarterback, but your ability to block and tackle and just solve lots of issues with the AIs is incredible. And it's not just the LLMs. I mean, one of the really biggest uses that's, you know, 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 got a long, complicated name, and there's two of them that look almost exactly the same.

32:43It'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, right? 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 kind of, you know, and AIs will make errors that a human never would because they don't understand causality. They don't understand the context.

33:18They don't, you know, there's all kinds of stuff, like the case study that you got right that the AI didn't, like there's things that it doesn't know. So a hybrid or what we call Centaur 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.

33:43Dr. 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, right? 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.

34:15Dr. Mark Hyman: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. And so 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, you know, these big, dense data clouds of their own biological information from all their omics to their blood panels, the things we don't even measure now that we're going to measure to their wearables and biometrics. I mean, I have a Garmin watch.

34:46Dr. Mark Hyman:I mean, I know everything about myself, my pulse ox, my heart variability, how much I slept, how much deep sleep, how much light sleep, how my training prettiness is, you know, like how much time I need to recover. I mean, it's pretty impressive. And all that is 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 the 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 is like five. You better get your ass over to the nephrologist tomorrow.

35:17Dr. Mark Hyman:So that's going to for sure be still there. But a lot of the stuff that actually requires a physician isn't really needed. It's really diet, lifestyle, behavioral changes, supplements, and 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 health care? You know, 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-12 science education problems has put together a four-module, one-year course based on two chapters.

36:17several of us wrote in a systems biology and systems medicine book, one on systems medicine, one on P4 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,

36:56exercise, sleep, stress, et cetera. 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 assaying 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.

37:50One, 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, namely chronic diseases. And Mark, I'd love to kind of weigh in on that question as well that you asked, because I think it's such an important thing because you're exactly right, because more and more of what we can 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.

38:32Most of that effort should really be on this maintenance of health, and then you get referred back into the disease care system when, you know, hopefully early enough to 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 an essentially painless at-home blood collection device. It used to be called the OneDraw and now called the NanoDrop.

39:08But that's like one feature of it.

39:11Dr. Mark Hyman:You're not going to go to jail like Elizabeth Holmes with this, are you? Not at all. Yes, exactly. That was my objection to the name change, obviously. Sounds like very familiar. It would be real science. I have gotten to her story. The nanotainer. Yeah, 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, right? Microbiome testing, right? 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.

39:51But 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. You know, I think that's that's really the key. Oh, and on the, you know, coming back to, you know, some of these, you know, like small measurements, you know, 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, you know, at, you know, at least doing a lot of them at the same time.

40:35But 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, you know, if we 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 time. If you gave them a huge vat 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.

41:11That's the only way. 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. 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 AIs, the long term. 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.

41:50And we all know height is heritable. If you have tall parents, you have tall kids. if you have short, you know, if you're short. It depends part of what you're, there's some other factors, but by and large, it's fairly heritable, right? 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 variance in height by a genome prediction, but that genome prediction requires over 180 ,000 genetic variants. So it's distributed across this long tail.

42:32So one of the things that we don't know yet is how much - You mean SNPs?

42:36Dr. Mark Hyman:You mean, you're talking about SNPs? SNPs, yeah. Which is like one, it's single nucleotide polymorphism, which in English means you substitute out one nucleotide in that gene sequence that changes the function of the gene. So you need 180 ,000 of these slight little spelling variations in order to actually predict what's going on. That's impressive. 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 7 '6", huge outlier. And you look at this and you get a distribution.

43:08And he's a massive outlier. Like if you looked at his genome at birth, you could have predicted that he was going to be crazy tall. And so you can do this in the NBA. 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 because it's not as digital as the genome, but it might be there. And so it's an open question.

43:41But 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. One of the things that is, I think, a major force right now, and we saw it with COVID in many ways is that people are taking charge of their own healthcare and that they're actually very hungry to do so. And the means that they're looking for today isn't working. And this is coming at the same time where there's actually now all these tools that do miraculous things.

44:19You see what you can do with GLP-1s. You can see what you can do with CGMs, these glucose monitors. Metabolic health is such an exciting area. There's numerous areas in health that are being driven by patients and patients as consumers, not as products of the healthcare system, but as real active drivers of it. And that's one of the key areas that we've been interested in. And Daisy and I have been working on that space together. And we're seeing that basically, I think what's growing is a movement of like-minded companies, like-minded founders, that there's an opportunity to really transform healthcare in this way.

44:58There's many aspects to healthcare. So this is one part of it. But this part actually, I think, is really ripe for disruption. And by enabling people to understand their health, whether we're talking about diet, fitness, primary care and beyond, I think these are areas that are actually something that people are building in today. Yeah, I couldn't agree more. I think we talk a lot about in healthcare, you know, problems of cost and access. But what we don't talk about is how broken the consumer experience is. And it's broken because consumers are not seen as the end customer in healthcare, you know, providers and hospital systems see the insurance company who pays them as their end customer and therefore don't optimize around consumer experience.

45:43and what results from that is like even if you are a highly motivated patient who wants to take control of your health you it's really hard to make appointments and get tests and understand those tests and understand what you can be doing um and then we have problems of behavior change and everyone's like oh that's a cultural issue but i think what we ignore is that the best companies fundamentally change consumer behavior and we see that all the time in other industries um you know And so I think we're really ripe for consumer disruption in healthcare. And Function is at the forefront of that.

46:21Dr. Mark Hyman:Yeah, it's exciting. You think about what healthcare looks like today. And we were just talking about this earlier, but my healthcare records are across a bunch of different doctor's offices in different states. And it's really hard to understand what's happening in my body and how it's changing. And with function, you get, you know, your data is tracked. Every three or six months, you have all these comprehensive tests. You can see how your biomarkers are moving. It plugs, you know, it's going to plug into EHRs and have all the data that happens at a doctor's visit, all the data from your wearable devices.

46:59And it's going to be, you know, everything that's happening in every person's body, you know, in one database for them.

47:05Dr. Mark Hyman:You know, I think that's an incredible vision. And one of the things that I am curious about your perspective on is the types of innovations that are happening. Because when I was at Cleveland Clinic, Toby Cosgrove, one of my heroes, brought the kind of discoverer, inventor, whatever you call it, of Watson. It was IBM's sort of supercomputer. And the big kind of tagline was Watson goes to medical school and was able to sort of ingest all of the medical textbooks and knowledge and pass exams and do all that great. And what really struck me was that it was sort of like rearranging the deck chairs in the Titanic.

47:43Dr. Mark Hyman:It was using incredible technology to do the same thing better, not to do something fundamentally different that what I would call scientific wellness or functional medicine or systems medicine or whatever you want to call it doesn't matter. It's just going to be medicine. But this paradigm shift is not, from my perspective, not really emerging from a lot of the new startups, new businesses, new innovations that are happening. And I see just incrementalism in innovation, not a fundamental shift in how we think about health and healthcare and disease and diagnosis and treatment. What are you seeing come across your desk that is different?

48:24Dr. Mark Hyman:Or are you just seeing the same kind of thing that I think I'm seeing? Am I wrong? Or this is actually how things are shaping up? I don't think you're wrong in the sense that for two factors. One is that, look, I mean, changing a system as complex as healthcare, you know, 20 % of US GDP, that's not something that's easy to do. And in fact, too, you can change, you can improve one part, but it's a complex system. That doesn't mean the whole thing improves. So the task is really hard. And then also, there are probably only going to be a few companies that really make this kind of revolutionary change.

48:59You think about the companies that have revolutionized other industries, like Spotify revolutionized music. That's something that it was basically one company that did that, or a few companies. It's not like hundreds of companies. You can go through Lyft and Uber for transportation or Airbnb for hotels. These are only going to be a few companies. There are going to be many that will try in a couple of different ways. But I think what will happen in this space is that a few will really stand out. And these are the ones that will be transformative. We review like thousands of companies before we invest in a year.

49:38And so there's many brilliant, hardworking entrepreneurs in this area. But making this type of change is something that only a few people can do and only a few companies will do. And those are the ones that we're looking for.

49:50Dr. Mark Hyman:And what do you think, both of you, around your vision for healthcare and what are the big disruptive innovations that are really game changers for us coming up? I'd love to hear your perspective because, like I said, you have this sort of crystal ball looking at the future and seeing what's bubbling up and also understanding the complexity of healthcare and understanding the challenges and looking for ways to really shift. So I'd love to kind of hear your vision for the future. Maybe I'll take one area and Daisy can take another. And we can list more. But if I were to pick one that is the one that's been on my mind is AI.

50:26And when you think about healthcare, what are the big issues in healthcare right now? I think if I were to name the top three, I would call them cost, quality, and access. And AI has a hope to address each one of those. What about outcomes? That's the one I care about as a doctor. I put that in terms of quality, like the quality of outcomes.

50:46Dr. Mark Hyman:Yeah. You know, in terms of cost, I think one thing that we're already seeing is that AI is a pilot for doc co-pilot for doctors today and may take on more and more tasks. That's something that can actually what's exciting about it when it can be trained from the very best doctors, it can give access effectively of the very best doctors to everyone. And that's something that we just don't have today. And that democratization of medicine, I think, would be very exciting. So that would be cost and access. And in terms of quality, you know, when we saw a similar arc in other areas, like in, let's say, on Wall Street 20 years ago, people were talking about using computers to do trading.

51:26And the reaction was like, that's ridiculous. Being an expert trader takes like decades and decades, right? And there's no way a computer is going to beat a human being. You know, like there's no way. And then 20 years later, it's like, well, that's ridiculous. There's no way a human being is going to beat a computer. And we saw this in chess. We saw this in so many different areas. And I think it's the flip that we're in the middle of now is that it feels hard for some to imagine that a computer or an AI couldn't do what a human being can do. But sometimes you think about what we're asking doctors to do.

52:00We're asking them to be machines to grind through all of this information, all this medical data about me and about the world and instantaneously come up with the answer. That's a lot to put on somebody's shoulders. But I think the hope is that AI working with doctors will be the best of both worlds. And the future of in terms of cost, quality and access would be dramatically improved.

52:24Dr. Mark Hyman:Yeah, I think that's a beautiful vision because I think those those are three elements. on the quality bucket, I would put the paradigm shift that's happening too in medicine, because we can do the same things better, which needs to happen. And often when I hear about quality based care, value based care, it really to me is often about improving things around the margin, like improving medical efficiencies, reducing errors, care coordination, better EMRs, better tracking of data, maybe better preventive screening, but it's still diagnosing the same disease as prescribing the same drugs. How do you think AI can play a role in really disrupting the medical paradigm itself, the scientific paradigm, not just the practice of medicine and getting people access and democratizing and decentralizing and bringing down costs and improving all of that, but how does it really change the scientific paradigm?

53:12Yeah, I think we talked about the data analysis part. I think that's part of it, but then I think, and you would know better than I, but I think the part of making medicine successful is giving the right care at the right time at the right place. And AI helping doctors and helping medical systems make sure that happens. And this is a win for providers. Doctors want to make health care better, but it's also a win for payers in that if we can do that, we can keep people healthier and healthier patients are obviously less expensive, which is the win-win. We think about what health care will look like in 20, 30, 40 years, And then we work backwards from that.

53:52And we have invested in a lot of companies who are taking on pieces of that puzzle to build us, you know, toward a better tomorrow. But I think, you know, 30 years from now, we probably 90 % of health care is delivered via your phone. So we're going to have amazing wearable devices, both in terms of watches, rings, et cetera, but also subcutaneous that are monitoring all sorts of molecules and things happening in our bloodstream in real time. We're going to all be doing function. We're going to have at home blood collection by then. We probably won't meet a phlebotomist. We'll have a device to do it.

54:31And so we'll have a real monitoring of our health. And you were describing this earlier, but we're going to have all of our health data in this one place. And you're going to be able to chat with, you know, your phone and say, I have a stomachache. What's going on? Does anything seem weird in my body right now? And it'll ask you questions, right? Yes. And we're all going to have access to like the world's best AI and human doctors through our smartphone. And then probably 10 % of health care will be, you know, going to the hospital for procedures. years, but more and more every year is going to be something that you can do at home with, and then we'll have drug delivery into the home.

55:11So I think it's going to look very different 10, 20, 30 years from now. And I hope it happens faster rather than.

55:19Dr. Mark Hyman:It seems like the cost will then come way down. I mean, it seems like the cost in healthcare are just kind of crazy. And I wonder if you're seeing any technology companies that are creating transparency, you because I can send a patient of mine. I did this not too long ago before function who wanted to get some lab work done. I wanted to sort of check a bunch of things. And I did kind of an abbreviated panel of what's in function. And her insurance didn't cover it. And she sent me, said, Mark, I don't know what to do. Like the bill is like$10 ,000. And I'm like, oh, I'm sorry. Let me call the company.

55:50Dr. Mark Hyman:And so I called the lab. Like, hey, this is not our pricing. Like you give us a different pricing. And so there's such variability in elasticity in the marketplace. You can go to one hospital and get a scan for my knee for$400. Another scan, another hospital, it's$2 ,500 for the same scan and the same machine. And the consumer doesn't know any of this. And they're completely confused. I went to go get a knee exam and I needed a knee brace for something. I messed up my knee. And I get a call from the hospital today. They said, oh, just to let you know, your insurance didn't cover that knee brace.

56:19Dr. Mark Hyman:And it's$1 ,000. I'm like,$1 ,000 for a knee brace? I got a new knee. And so the elasticity in pricing and the lack of transparency in pricing, you know, leaves the healthcare so padded with costs. You know, we spend twice as much as any other developed nation and get much worse healthcare outcomes. You know, we're like the bottom of the pile of developed nations. So how do you see kind of this evolving and us actually using technology and AI to help create transparency and kind of more democratize healthcare? Because it's so messed up right now. Yeah, it's funny, Mark. We all work in healthcare, and I think none of us understand how the pricing works or what we're going to get.

57:01On purpose. You know, what kind of bill we'll get in the mail. I was actually trying to figure out if I'd hit a deductible today. And it is purposely very confusing. But I think there's a lot of promising changes on the horizon. We're getting some regulatory changes around price transparency. where investors at a company called Turquoise that's helping consumers and other entities in healthcare understand what everyone's pricing is. And so I do think we're starting to see, and you have a lot of people moving on to high deductible health plans, which is probably not a great trend in healthcare where you have to, you know, you have to pay out of pocket for the first$5 ,000,$10 ,000,$20 ,000 before your health insurance kicks in.

57:39But the silver lining of that is I do think it enables some more free market dynamics where people are going to start shopping for work care and comparing prices. And we are, we're definitely seeing some of that in consumer behavior today. And we actually thought in relation to function, I think we thought, you know,$500 a year. Is that something that, you know, most Americans are going to want to pay? And what really struck us when we were going through all of the customer surveys is how many people were like, this is amazing value. I, something's wrong with my health. I'm bouncing around the healthcare system, trying to figure out what's going on.

58:13And I know these tests would cost me$10 ,000 elsewhere. And so you guys are obviously doing amazing things for cost in healthcare. But I think to the question about AI, we also, obviously, it's funny, BJ and I have talked about this a lot, but AI has way worse margins and is way more expensive than traditional software. But it is way cheaper than human services. And healthcare is a$4 trillion industry. That's like 90 % human services and a lot of expensive human services and doctors. And so I think we're going to see a lot of cost reduction from that.

58:48Dr. Mark Hyman:Yeah. I mean, it is striking to me how the value we're getting is so low in terms of the diseases going up, people getting sicker and sicker, rising costs, rising hospital burdens, rising disease burdens and we're spending more and more than any other nation and getting less and less. And that can't that can't stick. And, you know, I, you know, I meet with senators and congressmen and I work in Washington on food policy and health care policy. And, you know, I don't think any of them even have a clear view. I said to one of the other night, I said, you know, that 1.8 trillion dollars of the entire federal budget is spent, which is about a third of the entire federal budget is spent just on health care and not just through Medicare, but Medicaid, the Department of Defense, the Indian Health Services, VA, I mean, you name it, put it all together.

59:36Dr. Mark Hyman:It's a ton of dough and they're not even managing it. They're not even thinking about it as one problem. And so, and the reason I love function is that it, to me, it's kind of like this little rascal on the outside of healthcare that's trying to give people what they want and bypassing all the red tape, all the confusion, all the lack of transparency. I mean, like I said, I could literally get more than two function memberships for the price of one knee brace. It's like, that's nuts. The other thing that I think anyone who's gotten sick has seen or has loved ones that got sick is that you kind of have to be the one managing that process, right?

1:00:14You kind of like your house is a body and you have to be the general contractor for all the people coming to help fix it. And that's really hard to do. But if you realize that's what's going to happen if you get sick, I think you start having this mindset shift that maybe I can do that while I'm healthy. I don't have to wait till I'm sick to sort of be the general contractor there. I should be thinking about my health. I should be on top of this. And we see more and more people thinking that way with, you know, for all these different reasons, they come to it, that health care is top of mind. And then they start looking and they start looking for alternatives.

1:00:46And I think that's the opportunity. That's the market opportunity to present those alternatives.

1:00:49Dr. Mark Hyman:If you love this podcast, please share it with someone else you think would also enjoy it You can find me on all social media channels at dr. Mark Hyman. Please reach out I'd love to hear your comments and questions Don't forget to rate review and subscribe to the dr. Hyman show wherever you get your podcasts And don't forget to check out my youtube channel at dr. Mark Hyman for video versions of this podcast and more Thank you so much again for tuning in. We'll see you next time on the dr. Hyman show This podcast is separate from my clinical practice at the ultra wellness center my work at Cleveland Clinic and Function Health, where I am Chief Medical Officer.

1:01:21Dr. Mark Hyman:This podcast represents my opinions and my guests' opinions. Neither myself nor the podcast endorses the views or statements of my guests. This podcast is for educational purposes only and is not a substitute for professional care by a doctor or other qualified medical professional. This podcast is provided with the understanding that it does not constitute medical or other professional advice or services. If you're looking for help in your journey, please seek out a qualified medical practitioner. And if you're looking for a functional medicine practitioner, visit my clinic, the Ultra Wellness Center at ultrawellnesscenter.com and request to become a patient.

1:01:53Dr. Mark Hyman:It's important to have someone in your corner who is a trained, licensed healthcare practitioner and can help you make changes, especially when it comes to your health. This podcast is free as part of my mission to bring practical ways of improving health to the public. So I'd like to express gratitude to sponsors that made today's podcast possible. Thanks so much again for listening.