ZOE Science & Nutrition - The future is here: AI and personalized healthcare with Eric Topol

Episode Date: March 2, 2023

If you were to ask Siri, Alexa, or ChatGPT for medical advice right now, that would be a terrible idea.  But with recent developments in technology, this looks set to change. AI has become more intelligent, wearable devices - more accurate, and personalized medicine - increasingly mainstream. But is any of this safe? Should we really trust machines with our health? And will any of this actually happen? In today’s episode, Jonathan speaks to Eric Topol to explore how artificial intelligence may transform your next trip to the doctor. Eric Topol is one of the top 10 most-cited researchers in medicine, the author of 3 bestselling books on the future of medicine, and a practising cardiologist. Download our FREE guide — Top 10 Tips to Live Healthier: https://zoe.com/freeguide If Timecodes: 00:00 - Introduction 00:11 - Topic introduction 01:53 - Quickfire questions 04:17 - Doctor-patient relationship 05:49 - Jonathan’s story with Eric  08:02 - How has medicine changed? 13:54 - Is there an optimistic future for medicine, utilising AI? 17:46 - How close are we to utilizing AI-based solutions in medicine? 23:09 - Self-diagnosis and preventative care 27:05 - Is prevention possible through AI? 32:33 - Personalized healthcare 41:51 - Summary 43:45 - Goodbyes 44:01 - Outro Episode transcripts are available here. Follow Eric on Twitter: https://twitter.com/EricTopol Follow ZOE on Instagram: https://www.instagram.com/zoe/ Have an idea for a podcast? Contact Fascinate Productions to bring it to life.

Welcome to Zoe, Science and Nutrition, where world-leading scientists explain how their research can improve your health. Hey Siri, I have a headache and I'm a bit bunged up. What's your diagnosis? Hi Jonathan, you could be having a heart attack. Please call 999 as you need immediate treatment in hospital. Er, okay. Right now, asking Siri, Alexa, or ChatGPT for medical advice is a terrible idea. But with recent developments in technology, this looks set to change. AI has become more intelligent, wearable devices more accurate,

and personalized medicine increasingly mainstream. But hold on a second. Is any of this safe? Should we really trust machines with our health? Will any of this actually happen? In today's episode, we speak with Eric Topol to find some answers. Eric is one of the top 10 most cited medical researchers in the world. He's the author of three best-selling books on the future of medicine and a practicing cardiologist. He joins us to explore how artificial intelligence may transform your next trip to the doctor.

Eric, thank you for joining me today. I know you're a very busy man and it's a huge pleasure to be able to do this and to talk not only about COVID, which I know is a topic that you've been talking a lot about, but I think go to one of your big loves, which is really talking about the role of artificial intelligence and what it can mean in medicine. Great to be with you, Jonathan. So one of the things we always do at Zoe is we start with a quickfire round of questions from our listeners. And our scientists always find it really difficult because we have one rule, Eric, which is you can say yes or no, or you can give a one sentence answer, but you're not allowed more than one sentence. And we know that it will always make

you a bit uncomfortable, but are you willing to give it a go? I'll try. All right. So the first question that we had from one of our listeners was, in the future, when we feel sick, will we contact the artificial intelligence doctor on our phone as our first step? Not on your phone necessarily, but sometimes, yes. All right. Second question, do you think that regular home testing will become a normal part of our health, like visiting the dentist? More and more, yes. Do you think that wearables like the Apple Watch will play an important role in healthcare in the future? They will undoubtedly increase well beyond just the watch in the years ahead, yes.

Should doctors prescribe diet and fitness interventions in the way that they currently prescribe drugs? Well, prescribing it may not be the best, but certainly advocating diet and exercise as an essential part of one's lifestyle and health plan is critical. And last question, can artificial intelligence ever replace healthcare professionals?

We will go increasingly to a world that is somewhat autonomous and doctorless, but it will never replace. It will just supplant the role of clinicians. And I think that's something I'd love to get into, because I think there's always an enormous amount of fear whenever you talk about artificial intelligence. And my view of this is almost always when you see these new technologies, actually, they allow us to become more productive. No one got replaced with all the technology we brought into healthcare over the last 100 years. In fact, it's much harder to get to see the doctor now

than it was 100 years ago. So I assume that we will see the same thing, but maybe when we see the doctor, they'll have all of these great knowledge. And, you know, there's not a lot of that great insight from doctors. Right. I mean, we have problems for sure of being able to have time with patients. And there are solutions in sight if we work towards those. It's funny. My wife is a doctor. And so through that, I know a lot of doctors.

And I think often if you're not a doctor, you see this through the lens of being a patient and it can be very frustrating. I think it also could be quite scary. You know, most times when I see the doctor, I think there's something wrong and I don't know what it is. But talking to my wife and her friends, you know, the number one complaint they always talk about is feeling they haven't got enough time with the patient and that it's sort of consumed also in trying to get the information that they

really need in order to then do the bit that is really value-added. And, you know, my wife is sitting here in the UK. I mean, one of the things she feels is the time has got much worse in terms of availability. Is that like a global position? You're sitting in California. Is that the same, you know, around the world? I think that's unquestionable. There's been really a degradation of the patient-doctor relationship over the years. We have to turn that around. We can. That was the whole premise of the deep medicine book that I wrote about what AI can do to bring it back. It's the most important thing I think we can do with this technology in the years ahead, but it's going to take active, aggressive effort.

It's not going to happen by default because we can use these new tools to make things worse. And that's what we've been doing with technology like electronic health records and many other things for the past decade. So we've really doing with technology like electronic health records and many other things for the past decade. So we've really got to turn that around. I think, Eric, you're very rare. In general, what we see in health is this divide between people who are world-class physicians and scientists, and then this completely different world that talks about technology and AI. And in general, there's sort of no overlap at all. In fact, you may be on your own in this particular intersect.

So I think it's really fun to be able to have you here and talk with us. And actually, I want to share a story just with our listeners for a minute, because right at the very beginning of the journey with Zoe, actually, you were one of the first people that I got to go and meet. And so I was with Tim Spector and we were visiting California and San Diego where you are, which for those of you who aren't familiar with San Diego, it has basically the world's best weather. Is that fair, Eric? It's up there. It's one of the best for sure. Yeah. And Eric has this fantastic office with this great big glass window that looks out onto the sea, and you can see the beach.

And you've flown in from rainy London, and you're like, I've definitely not made the right life choices. And Eric has clearly made the right life choices. Tim had explained to me, you are, I don't need to say like incredibly well-known and respected physician. But we had this fascinating conversation where I came away with a real boost because I think I'd been meeting a lot of scientists and doctors who'd been very skeptical about the idea of applying machine learning, artificial intelligence into health care and also skeptical about doing the sort of enormous scale of studies that we were talking about. And you were one of very few people who was very excited about the idea and believe there was a lot of opportunity. So I'm not sorry I said that to you, but it was a real boost. And I think, you know, I came away thinking that although maybe this whole idea of Zoe was a little bit crazy, It wasn't completely crazy. So thank you. Well, I remember the meeting well, and I don't think it's crazy at all.

I think it's the future. We'll get there. It won't happen in the next few weeks or months, but we will get there. I'd love to start with that. I know you've written quite a bit about it. And for our listeners, though, I think this will be really new. Could you maybe start with how have you seen medicine changing maybe over the last decade or two? And what do you expect in the future? Where do you see this going? Well, I'm an old dog, Jonathan. I got out of medical school in 1979. So I started practicing as a cardiologist in 1985.

So I'm heading towards 40 years as a cardiologist in the next few. So I've had a lot of experience, and I still, of course, practice and see patients, and it's the best part of my week every week. And I've watched medicine with steady erosion, particularly in more recent years. The difference in the 80s when I came out, started practicing medicine, where the bond between patients and their physicians was precious. It was an intimate, tight relationship. There was trust. There was presence. There was an intimate, tight relationship. There was trust, there was presence. There was really good history taking and physical exam.

And you cared for patients and they felt cared for. Now it's a rush job. Patients have little sense of a real bond. So the humanity in medicine has been compromised. And as a result of that, we're in a desperate situation because that loss of trust, that loss of that remarkably important relationship, and the inability to listen to patients. We interrupt them within seconds, don't listen to their story. So we aren't really caring anymore to a large degree. Obviously, there are exceptions, Jonathan, and there are great doctors out there and

health systems where you have time. But the biggest insult is that we don't have time and we have shunted our efforts to being data clerks, pecking away at keyboards to enter data or put in orders or tests or whatnot. So we have the tools, I believe, to completely radically improve where healthcare is today and not only revert back to where it was in the 80s, but to even go beyond better than that. So that's, I think, really exciting.

And Eric, just before you talk about where we're going, because our listeners will be saying, you know, how comes it's worse than 40 years ago? And I think many of them will have experienced this. And it does seem as though this is a common pattern across many different countries. And there are people listening to this in the States, in Canada, in the UK, in Australia, all over. And it seems like you get a similar picture everywhere. We're richer than we were 40 years ago. We have more technology. Why is this worse and not better? Well, it's largely because medicine turned into a business. It's especially worse in the US because it's truly a pay-for-service model. But having spent time in the UK in the review of the NHS and other countries,

it's also a business. That is, the number of minutes, the time scheduling with patients has diminished over the years. And the expectations that doctors and nurses and clinicians across the board now have the re-added toll of having to enter all the data, typing it, and spending a lot of time on screens, not even with the patient, not even seeing the patient when the patient is in the room. So the electronic health record may have been the biggest insult, but this decay of priority for time and for empathy and communication, these are all things that have suffered vastly. So again, as I wrote about in Deep Medicine, when I started, the

average time for a new patient was an hour or more to a new consult and a return visit was 30 minutes at least. Wow. That sounds amazing. Now we're talking about 12 minutes for a new patient, which is the actual time with the patient. And a lot of that isn't even looking at the patient. Or seven minutes with a return visit in the United States. I have to say that in the UK, right, at the moment, so I'm here, you know, it's in the winter.

I mean, things seem to be under so much pressure that the idea that you would even get a doctor to speak to you on the phone for two minutes sounds like it would be a brilliant outcome. So I think we're really feeling under intense pressure at the moment. Well, in Asia, the average visit in many countries is two minutes to visit, not just a phone call. Yeah. So this has been a trend about the business of medicine and getting in patients like a factory, in and out, the squeeze, if you will. And the problem around the world is that doctors aren't any in control. This is run by administrators, the overlords. And their charge is to make things efficient and get those patients through and care.

The word care, which is a humanistic thing, that's not a top priority. You know what I mean? So part of this is really a profound flaw losing the humanity, the whole reason why we went into healthcare. I mean, this was the mission. This is what is alluring to people to go into the profession. And we can't even execute as we had hoped because of all these drawbacks that are really serious. you're going to now to flip this around and tell me that we're not on the one-way road to like my 10-second appointment with a doctor by the time, you know, I'm 75? No, I am an optimist and I have a solution. I propose a solution that I think will take, I hope to see it fully become the norm, the bane of medical practice. The main thing is to describe the unmet need and now take action to get us to where the exciting new place that we can be in the years ahead.

If we didn't have the way to get there, that would be depressing. But we have the eminent possibilities to fix this. So you've teased us. Tell us about it. Well, the fix is that all these different paths to get the gift of time. So you've teased us. Tell us about it. that there's a chance to really, that there's presence and that there's really a chance to communicate everything that needs to be expressed. And that's particularly listening to the patient's story, doing a really good exam and that sort of thing. Now, to get that time, I mentioned there's several paths to get that. One is, as you've already touched on in the questions, Jonathan,

is to give patients more charge, that they can do self-diagnosis screening, maybe not the final diagnosis, but a good screening. They can have their data and have algorithmic support to interpret it. They can have coaching done virtually of their conditions or conditions that they would otherwise like to prevent. And of course, things like improving their lifestyle so they have better health in general, which is preventing across all conditions. On the clinician side, we're talking about liberation from keyboards that they wouldn't even exist. We would do this through natural language processing and machine learning. We would have all the records and all the data teed up for the clinician so they don't have to go through page after page, screen after screen to try to aggregate that

information. And we would have, you know, so much of this automated so that the residual was, wow, we have time to be together. We have less need for in-person visits. And they're going to be for the important stuff, like to discuss a new diagnosis or to understand what our patient's deep concerns are, whatever it is. But there'll be a different look for why you see a doctor in the future. We already have many ways to make diagnoses through AI for the patient side. We have things like diagnosis of heart rhythm abnormalities through our watch, diagnosis of urinary tract infections through an AI kit you can get at a pharmacy in many countries. We have skin diagnoses of lesions, rashes, cancers, ear infections in children, and the list will just keep growing so that

most of the routine things that are not life-threatening will be capable of diagnosing through our phones and our wearables and our data. That's really important. That's what's missed a lot is that the patient side of this is going to be empowered like never before. Not every patient will use these tools, but yes. I think it's a really fascinating picture, right? All of these pieces sound amazing. And I guess my first question is, which parts of those are actually relatively near-term, Eric, where you feel actually, you know, these could be real things that we're doing within the next, you know, three to five years? Well, the list I just mentioned is here today,

this doctorless screening for diagnosis. Yes, yes. And I think that list is just going to expand quickly now. On the clinician side, for doctors, we are already seeing synthetic notes to replace all the work that's being done to enter notes and data by doctors and nurses so that synthetic notes are, I've already seen, they're so far better than the ones

that we have accustomed to based on the conversation, extracted from the conversation between a doctor and patient. So they just listen to the conversation a bit like when I'm talking to Siri or Alexa, and then they condense it down to something that looks like some doctor's notes about Jonathan has a sore throat and his knee hurts and we're going to do these tests. It can actually pull all of that together? Not only that, but it also says, well, you know, Jonathan, we're going to prescribe you this medicine. And so it already puts that into your pharmacy. We're going to have these tests ordered. They all get ordered.

We're going to have your next appointment, you know, in six months. That all gets arranged. You don't have to touch a keyboard, okay? And that's phenomenal because that's a liberation. And when I did the NHS review with the incredible team I was so privileged to work with, that was the one that everyone was cheering for. That was the one. And that's already started, of course, in many parts around the world. And it will become the norm in the years ahead. It's not far. We have the tools to do that. And is that live anywhere in the world today, Eric? Is that actually being experienced by patients? Absolutely. Oh, yeah. No,

in fact, it was already two years ago. It was live in Leeds, as I understood it, in their emergency department, of all places, interestingly. But no, it's starting to crop up in many parts of the U.S. Alaska, I learned about just recently in China. I mean, it's the real deal. But, you know, it takes time because getting across all specialties, across all of medicine, but it's on the way. And it makes the current way we chart look anemic because of its efficiency. It's like, why do you have to do this all over again if you could have a machine do it?

And by the way, it's improved more because the patient gets to edit the notes and access other notes. And that helps because now there's a work product that's done jointly. So the physician edits, but after the first 25, 30, 40 notes, they pretty much, the AI has the doc down, but each patient also can weigh in. So, you know, this is exciting because if we liberate from keyboards, I mean, that's big stuff. That's really interesting. I'm interested in how much you emphasize this idea that the doctor is now distracted by the computer and the screen and is not sort of looking directly at you. And it's not something I'd ever thought about before, but you're absolutely right,

of course, that when you're talking now, they are interacting a lot with the keyboard. And, you know, that's very different from, for example, the sort of interaction that a pediatrician has with like my child. You know, my son is now older, but, you know, with my daughter, because, of course, you've got to really give a three-year-old your full attention if you want to get anything out. And, of course, you see that's a very powerful sort of interaction that I'd never thought about. But you're right. You're sort of losing when suddenly the doctor is actually largely having to interact with this computer to put in all of this data. Right. Right. No, and that is a big deal when you don't even make eye contact. It's awful both

sides. I mean, it's unacceptable and it's been the norm for many years now. And I also want to add, Jonathan, it isn't just the time with the computer in the midst of seeing patients. It's all the added time off hours where you have to still do all your charting and stuff that should have been done in real time. So it's a burden, not just in the midst of seeing a patient, but also well beyond. And it's interesting. I see that with my wife, because again, as a patient, it's not something I'm ever really aware of, but there's an enormous amount of bureaucracy dealing with patients outside of the room. And I think as a patient, I never really thought about it. You thought the only time anyone's dealing anything with you is when they're there.

And then you see there's all sorts of other things they have to do, following up on the notes, making sure they're right, sending them, dealing with tests, looking at results, all these sorts of things are a big part. So that's very exciting. I would like to follow up on the other bit that you talked about, about the sort of patient self-diagnosis, because that's something that has obviously been really interesting for Zoe. We had this big experience through the Zoe COVID study of suddenly people logging their symptoms every day being able to use that to figure out whether people had covid you know what the risk factors were all the rest of it um what i'm struck by is that we had this amazing tool and experience and we still have hundreds of thousands of people who are continuing to use the the zoe health study to do this and it's it's in no way

connected to anything else that is going on in in health care and and and my experience is that there's um you know quite limited linkage of this idea of sort of self-reporting your data through to the the health system So you're being very optimistic, which I love. Where do you see this really working well? And what are the gaps to get to the point where we really could be... I always like to talk to people about this idea of preventative medicine. Surely you ought to be able to figure out things are not quite right a long time before you're really sick. And the reality is that our health systems are not really able to do this in most cases. Right. So, one of the problems we have right now is the level

of depth of data we have for each person. So like, you know, what you've done with your nutrition work is kind of futuristic because you not only need to have the electronic health record, and of course in some countries like the US it's highly fragmented, so you need many different EHR health system. But then of course you need to give things like

the biologic layers, that could be the gut microbiome or the patient's genome or at least their array SNP data. You'd like to have their physio, which is sensors, that you would be able to pick up key metrics from that. Their anatome, which is their scans of their relevant anatomy. Their exposome, the environmental factors and the social determinants. Their immunome, and on and on. It's a lot of stuff.

Yeah, a lot of stuff. And by the way, no human being could process that. Now, even, even some particularly confident doctors could never process all that data. All right. So we have to lean on machines, but what we're doing and you're doing as well, is pulling together all this data, multimodal AI, and processing it for the individual. And once you do that, you not only can manage a condition like diabetes or hypertension or depression, common conditions, obesity, you can help manage a person essentially in real time by having that data processed and get back to the person with algorithmic support. But you also, in the future, will be preventing conditions that people are at risk for, which is really exciting because then now we fulfill the

fantasy. The fantasy of medicine is to prevent serious conditions from ever occurring. And when you have all that data at the individual level and you can use it to prevent an illness, a serious illness, whether it be a heart condition or neurologic, you know, cancer, asthma, whatever, this is really where eventually we will be. And Eric, just as you say that, I just, you know, you've been voted the number one most influential physician leader in the United States, which is very impressive.

So I want to take this opportunity to say that we like to say that this is possible, but, you know, you're much more credible than I am. Do you truly believe this idea of prevention in healthcare is possible? Yes. I mean, it hasn't been actualized and proven, but theoretically, once you have a person's data, because the first step is to say each of us are unique,

except that each of us are truly unique. Even biologic twins, identical twins, have significant differences. So once you get past that and you say, okay, well, now we can get all the domains of data and we can process that data. That's one of the bottlenecks right now, by the way. And when we do that, not just at a personal level, we do that in the hundreds of thousands and millions of people, ultimately billions of people, then we have a way to, a path to not only treat people better, help them manage their conditions better, but also prevent illnesses. Yes.

I mean, we're a ways from that right now, but you can see we will get there. So it's a sort of, it's an ambitious goal. You believe we can get there, but we need to be realistic when you're talking about the stuff that's near and far, like the prevention in the sense of really being able to figure out that you're at very high risk of like uh of a stroke in 15 years like this is a long way off um perhaps prevention in the way that we think a lot about it which is improving you know diet and things like this we can see is you know i think we feel very good about impacting long-term health, but it doesn't mean we're actually figuring out, you know, way in advance what's going to go wrong. You know, the analogy I often like to talk about is just with our cars, where, you know, I take the car

to be serviced once a year, I still have a car, and they plug a computer into it, and they run some diagnostics, and they say, oh, you know, the fan belt is about to break and we're going to replace the fan belt and I drive it off. And as a result, the car never breaks for, you know, 12, 13, 14 years. And we're used to that in all these other aspects of our life. And I think the experience that, you know, all of us who aren't doctors have is, you know, you go to the doctor and if you're not like really sick with something, there isn't that equivalent of really have been able to do this diagnostic and say, you know what, Jonathan, I know you're worrying about Alzheimer's and heart disease and all the rest of it, but

actually, you know what, it's diabetes you've really got to worry about. And therefore, this is the stuff that you really need to think hard about. You know't, as a health system, in most cases, able to do that. Maybe if I have particularly strong family risk, or I've got a very rare gene, or I'm getting really sick. But in most cases, that's a long way on. And it's much harder to make the change when you're already sick than it is to get you much earlier. Do you recognize this picture I guess I'm painting? Yes. I mean, I wish we were as simple as cars.

I accept that. You can digitize a car. And what I've outlined is that we're going to be digitizing human beings. That sounds awful, right? Oh, we're going to be digitizing human beings. That sounds awful, right? Oh, we're going to digitize you. But no, it's for the singular purpose of what you just described, of being anticipatory for potential illnesses

that you specifically are at risk for and knowing someday we're going to have digital twins. And what does that mean, Eric? Yeah, we found these five people around the world that match you at every level as best, as close as possible. And by the way, some of them are much older than you. And this is what we learned how to prevent this condition or that condition. This is what really worked how to prevent this condition or that condition. This is what really

worked well to treat the cancer that you have or are going to get potentially. So, I mean, we have never done this before, learn from each other. We do these clinical trials and let's say we have 10 out of 100 people. That's a big success story in a clinical trial, that we found a treatment that helps 10 out of 100. What about the other 90 out of 100 that take the medicine every day for the rest of their lives? Well, what about if we start getting incredibly precise through digital twins? When we have hundreds of millions, ideally billions of people where we have all these levels of data

and we can help share and, you know, make matches so that people will know the best treatments, the best preventions. That's someday, that's further off. That's further off, Jonathan, than what we've described. I mean, I love that because you're sort of articulating in different language. I think a lot of the ideas that we have at Zoe that Tim and Sarah and George and I talk about quite a lot. And I think it's wonderful. I'd love to fill up a little bit. You've talked about personalization quite a bit here. And I think that's really interesting because, you know, I know that Tim and others talk about the way that, you know, when a doctor, everything is that it's a one-size-fits-all solution.

You might diagnose somebody with a particular disease, but then you don't further break this down into lots of different categories. You've got sort of this treatment. But a lot of what you've been talking about is how different we all are, I think. And I'd love for you to talk about how important you think that is. And I guess for people listening, is that really going to be able to affect the health care they get in a decade? Well, sure. I mean, I think what you've seen in your work with Tim and others is exactly what we've seen, which is it's just as simple as if you have a glucose sensor on and you eat something,

and some people have spikes of glucose to 180, 200, and some people totally flat, and the exact same food with the exact same portion. It was really Aaron Siegel and his colleagues at the Weissman Institute in Israel that made that first observation several years ago, which I thought was stunning. But that basically told the story. And it's the same across everything in health, everything. If it's as simple as what you eat, then you can imagine, and the fact that we treat people like cattle and we don't recognize their uniqueness insofar as our approach, general approach, that's also part of the problem. So we have a remedy. We have a fix for that. And it's across everything. And nutrition is one that I think I'm particularly

enamored by and wrote a lot about, deep diet in the book and the AI diet, if you will, that the New York Times called it. But I think this is an exciting area because we spend a lot of our time with what we eat and our sleep and our exercise, ideally. And a lot of those things can help us preserve health. As we think about the future, I think you've got this picture, I think, that we know we want to end up with, where almost everything has been monitored. There's all of this AI to figure out all of it. There's these incredible tools that support the doctor

to figure all of this out. And then I'm getting this completely personalized solution if I have a particular cancer or any of the rest of it. Clearly, we're going to go through some stages from here to there. And we will also, of course, have some missteps. And we'll think there's things that are really important that we should monitor and they turn out not to matter. I think one thing I'd be really interested in is, I guess, your view about what's the sort of things that we will want to be monitoring sort of over time on ourselves that you think have value and maybe those that don't. Because I am struck there there's also like a risk of a lot of companies selling, you know, a particular thing that you should monitor all the time. And I've seen a few of these where, you know, I'm a bit skeptical based upon what I've seen

from our data and other scientists. You know, not everything that you can monitor is necessarily important, right? We all know that actually, you know, if we think about our own children, there's all of this stuff going on. And actually, you're pretty good at figuring out actually they're not quite right, right? We all know that actually, you know, if we think about our own children, there's all of this stuff going on. And actually, you're pretty good at figuring out actually, they're not quite right, right? You're picking that up in some way. What do you think are the things that either already we know have value or are going to have value just, you know, based upon either what you've seen yourself or from the research. Well, I don't think they measure all things and all people. I mean, that in itself is particularized based on the different layers of data.

I do want to go back to your assertion that, you know, everybody's going to do this. I don't think that's ever going to happen. There's a lot of mistrust in data and privacy of data. There are solutions in sight for, you know, in AI, if you talk to AI computer scientists, every problem in AI, whether it's bias and whether it's privacy, you name it, there's a solution with AI, right? I mean, it's classic. But most of those are not true. But the one that does resonate is that we will do better with privacy and security, whether it's edge computing or swarm or federated or whatever it is, homomorphic encryption. So the reason I bring that up is that's a barrier, as is bias and as is other factors that play in this whole area.

But no matter what, we will have many people that are reluctant to use technology in healthcare. I mean, look what we've seen with vaccines, with science compelling, probably the most compelling data ever assembled in history of medicine. And look how much resistance there is. anyone to think that this is going to be, you know, a vast majority, but I think it's going to be substantial enough to be very, very important. So just make sure that that's clear, because we tend to get carried away that the way we think is the way everybody thinks, and that couldn't be further from the truth. Totally agree, Eric. I think trust is an enormous part of this. And the other part, of course,

is feeling that there's real value, right? So we always feel better about recording something or sharing our data with somebody like our doctor, because we know we're going to get something valuable back. For the people then who are saying, you know, I want to do this, I'm happy to go and, you know, wear a particular device or whatever. What do you think are, what are the sorts of things that are being, that are either being monitored today, or you can see being monitored

in the next couple of years that you think might have real medical value? Well, the first biosensor, which is now used in millions, of course, is glucose, continuous glucose. And that's changed the world for lots of type 1 diabetics. That's right. And that's blood sugar for anyone who's not familiar with it. So this is being able to monitor your blood sugar in real time with some little device you stick on

your arm, for example. Yeah. And this is a big deal because obviously people taking insulin are at risk for having very low blood sugars or not having good control of their blood sugars. So this is a whole lot better than getting a blood test every three months, like a hemoglobin A1C, which is used. So that's the first sensor that got into wide scale use. And then of course, with the fitness bands like Fitbit and smartwatches like Apple and many others now. We are seeing heart rate, heart rhythm, but there'll be others. And of course, you know, oximetry became important during the pandemic with pneumonia monitoring. This is the amount of oxygen on your blood, to make sure that's oximetry, is it? Exactly.

So, which can be monitored through a finger or the wrist very easily. But there's no limit. I mean, eventually we'll have high-frequency blood pressure, non-invasive passive monitoring, so you won't have to take out a device and measure it yourself. It'll be done automatically. But we already have things. To me, the most extraordinary thing is self-imaging. So using a smartphone with a high-resolution ultrasound probe that you put in the base of the smartphone, you can image any part of your body

except your brain. So this is basically the same as when you're pregnant and you do the ultrasound to find the baby, but you can plug it into your phone? Yes, now it wouldn't probably be good for a mother, expected mother to image their baby every few minutes. That's not what I'm getting at. But what I am suggesting, like we're already seeing in heart failure,

is that people can image their heart and send a loop to a doctor. And you don't have to have any training. The AI tells you how to get the image. All you have to do is be able to put the probe on the chest. That's amazing. So it's another one of these ways where you can push the technology right out to you at home, and you can give really valuable information back to the doctor. Exactly. I would like to just do a quick summary, which is what we always do at the end here. And I think this has been particularly visionary, which is really exciting. I think that my key takeaway is, from your

perspective, actually, healthcare has been sort of been getting worse over the last 40 years. And you paint a picture where it's really true that the relationship between the doctor and the patient is worse, and that actually the technology has sort of been getting in the way. But the good news is that you do see this sort of sunny, uplit future where the AI can really change that. And there's a lot of these technologies are sort of there. They're just not in the sort of mainstream deployment, but therefore they could be there in the next few years. You're not talking about decades away.

I think that some of these, we will just see when we visit our physician, our doctor, because suddenly, hopefully, they're going to be able to look at us and engage with us. And there's all of these things in the background. But the other element that you see, I think, becoming really significant is people tracking their own data. Now, what exactly that data will be that turns out to be high value is still being figured out.

And you talked about blood sugar as an example. You talked about some of the things like blood pressure, but we're going to learn a lot more. And I guess the final thing is, for you, personalization is central to all of this, that actually, in a way, medicine right now is this thing. You've got a drug that's going to work for, you said, 10 in 100 people.

How do you solve the other 90? How do you figure that out? And so, again, this data, hopefully, and this AI allows us to move to a world where not only can you think about prevention, but also you can really think about personalization. And I'm slightly putting words in your mouth, but I think you're therefore suggesting there could be a real transformation in the success of medicine if you can really understand that personalization. That's a great summary. Eric, it was such a pleasure. Thank you for taking the time. I look forward to following up and hopefully keeping you abreast of what we do at Zoe and

hopefully getting you back on again in the future. That's great. It's a real pleasure. Thank you, Eric. Bye-bye. Thank you, Eric, for joining me on Zoe Science and Nutrition today. If based on today's conversation, you'd like to understand the difference personalization could mean for your diet and your health, then you may want to try Zoe's personalized nutrition program. Your Zoe membership comes with our app, which uses artificial intelligence to score millions of foods and meals for you. You also get personalized meal and recipe recommendations

and can chat directly with our nutrition coaches. As a member, you start with an at-home test to understand your biology. We create your individual ZOE scores and a personalized program for you based on your test results and our scientific research. If you're interested in learning more about ZOE, you can head to join zoe.com

slash podcast and get 10 off your purchase if you enjoyed today's episode please be sure to subscribe and leave us a review as we love reading your feedback if this episode left you with questions please send them in on instagram or facebook and we will try to answer them in a future episode as always i'm your host, Jonathan Wolfe. Zoe's Science and Nutrition is produced by Fascinate Productions with support from Sharon Fedder, Yala Hewins-Martin and Alex Jones here at Zoe. See you next time.