Every so often a conversation reframes how you think about your own health, and this one did that for us.
Momo and Guru sat down with Vinod Khosla, the entrepreneur and investor who co-founded Sun Microsystems and later founded Khosla Ventures, and the throughline was simple but startling: the expertise that medicine has always rationed, because it was scarce and expensive, is becoming almost free. Vinod walks through why that changes preventive medicine from a nice idea into something practical, why engagement (not technology) is the real bottleneck, and why so many supplement studies get the wrong answer by never measuring what's actually happening in the body first. He and the hosts get into the messy middle too, the hallucinations that make raw chatbots risky in medicine, the "harnesses" that fix them, the human biases that can quietly degrade even a good AI, and the regulatory and payment systems that slow all of it down. What stayed with us most was the molecular-medicine thread: the idea that no human can hold thousands of interacting pathways in their head, but AI can, especially when it's reading both the activity of your microbiome and your body's response to it. Below is the full conversation so you can take it all in for yourself.
The full conversation
Momo: Hello everyone.
Guru: Hey, Momo.
Momo: Hello, Guru. Okay, so today we are joined by a super, super exciting guest. He's one of the most influential entrepreneurs and venture capitalists of our time. From co-founding Sun Microsystems back in the 1980s to backing groundbreaking companies with venture capital in AI, healthcare, clean energy and biotechnology, Vinod Khosla has spent more than four decades helping turn bold ideas into technologies that improve millions of lives. I'm really excited about this one.
Guru: Yeah, Momo. Growing up and going to school in the computing world, I have heard about Vinod Khosla's many different accomplishments, adventures, investments and all that stuff. And I've always kind of looked at him as a model for many people to follow, entrepreneurship-wise at least. And the other thing I really love about Vinod: I met him around the same time that you met him, which is when we were talking about investing in Viome back in 2016, 2017. What I was really impressed with about Vinod when I first met him was that he's, in equal parts, a big-picture visionary. And at the same time, he's very familiar with all the minutiae of the technologies, of the new developments, and he's able to engage you with very detailed information about many things, both on the tech side as well as on the medicine side. And so that makes him very unique, that he's got that breadth and that depth, that he's able to make the right decisions. So I'm super excited about talking to him.
Momo: Agreed, agreed. Just a very unique individual with a very rich background, so we're going to get into it soon. So I am Momo, a biochemist.
Guru: And I'm Guru, a data and AI expert.
Momo: You're two PhDs on a pod.
Guru: What's on your radar, Momo?
Momo: Well, currently summer is absolutely on my mind every day. Here in the Pacific Northwest, we have such long daytimes. The sun rises around five and sets around nine for two or three months, and the weather is just perfect. The highs are in the 60s and 70s, the lows are in the 50s, both on the coast and in the mountains, and it's just gorgeous out here. So next episode I'm going to show some pictures that I've taken, because I'm a very, very intense amateur photographer. But yeah, the summer here is just phenomenal. And then the other thing that I'm always excited about is cooking.
Guru: Wait, before you go to the second one, I just want to mention my brother just moved back to Seattle. So I will be visiting probably more often, or staying a little bit longer. I mean, I already visit Seattle quite often because you're located there and our Viome headquarters is over there, and so on. But I will be there even more frequently, I believe, and maybe we'll have a chance to go explore some of the Pacific Northwest wilderness.
Momo: Love that. Love that. Okay, great. Yes, good. So that's on my radar. And then of course, cooking is always on my radar because we live to eat and cook and so on. So recently what I'm really excited about is that I've been doing a lot of searching the ancient literature about mole recipes. So mole is a traditional Central American sauce. Now you can go to a Mexican restaurant and many of them will have moles: a green mole, red mole, black mole, typically those three. And these were recipes that were actually developed by Native Americans prior to 1492, but they were pretty much reserved for royalty. Well, the cocoa one was reserved for royalty and the chile one was reserved for royalty. There were others that were used in normal households. But anyway, I was able to research the history of mole, and there are pre-Columbian and post-Columbian recipes, and we decided that we should make a recipe from the 1500s that the Spaniards actually recorded. So this is somewhere in the 1550s, the first recipes of mole were documented, and we picked a black mole because I love cocoa and it's just so nutritious and so delicious. So yeah, made a black mole with sort of an authentic recipe that combines both New World and Old World foods, and it's just super rich and tasty. A very unique flavor that I don't think any other cuisine has.
Guru: Nice, nice, nice. Is it 100% vegetarian?
Momo: Yeah, it's all vegan. Absolutely. The sauce is 100% vegan, and then you can put it onto any kind of a protein source you'd like. The Central Americans obviously used turkey. That was their major source of meat, but they had other sources of meat as well. And then today we can of course choose tofu or anything you'd like.
Guru: That sounds great. Momo, it would be nice if you can put the recipe in the show notes, because I want to try this.
Momo: Yeah, I'll put the recipe in the show notes and I'll show pictures of all the ingredients in the next episode. So make sure you tune into the next episode. All right, so that was my radar. What's on your radar?
Guru: All right, I'll be short because I want to get to the discussion with Vinod as quickly as possible. So first, over the last couple of weeks, I have definitely had the FIFA World Cup football. I still call it football, although people in America call it soccer. I love watching those matches, especially the ones with, I call them artists, all the strong stars of football like Messi and Harry Kane from England. And my favorite is this new guy who's shown up on the scene called Erling Haaland from Norway. He's like a Viking dude, big guy, very powerful looking, but also very agile and very fast. And he's made all these goals and just amazing stuff. And today actually there's another match between Norway and England, so I'm excited about watching that. So that's one thing on my radar. The other thing on my radar for the last couple of weeks has been a bunch of acquisitions that Viome has been making and evaluating for expanding our portfolio of solutions for good health and longevity. So the idea of Viome has always been that we want to understand biology deeply, prevent and reverse chronic conditions, cancers, and aging. So we want to provide all kinds of solutions, something that's super integrated into your lifestyle like eating, nutrition, supplements. And now we are also considering other kinds of interventions that can help you get to better health and a longer health span, I should say. So in the not too distant future, I think we will announce these acquisitions.
Momo: So you're keeping them secret for now.
Guru: Yeah, I think we should keep them a little bit secret until we actually publicly announce them. But you know what? The way we'll do that is to maybe bring some of those people onto our show and have them discuss some of the things that they have brought into our portfolio. So that's on my radar.
Momo: That's awesome. If we go back to the future, for those who watch this a year from now, they can go back and find out what acquisitions we made and learn about them. So yeah, that's pretty exciting. Cool. Awesome. Let's get into it. Let's bring our guest. All right, let's do that. Okay. Well, welcome to another episode of Two PhDs on a Pod, and we have a super, super extraordinary human today as a guest. So this is Vinod Khosla, and he is going to talk to us about the future of medicine, the integration of AI, and investments into startups and some big companies. And so I'm going to introduce him. I've known Vinod since 2016, and I'm just super happy to have followed him and to be in discussions with him all the time. So first of all, I think of Vinod as a great human being. That's to me the most important thing. He's super nice, super knowledgeable, patient and reasonable. So that's super important. But let's talk a little bit about his background, because it's pretty staggering. He has an undergraduate degree in electrical engineering from the Institute of Technology in New Delhi. And then he came to the United States and got a master's in biomedical engineering. So he knows quite a bit of biology, which is very unusual for this kind of a profile. And then he has an MBA from Stanford. And then he co-founded Sun Microsystems. So that's one phase of his life, where he co-founded Sun Microsystems in 1984 and really shaped modern internet and enterprise computing. And then he moved over to Kleiner Perkins, which is an investment company, and backed many pioneering internet infrastructure companies such as Juniper Networks. And then in 2004, he started Khosla Ventures, which he has been running now for 22 years. And he's a great investor, one of the best, and won many awards and accolades and so on. And Vinod is really visionary in understanding which companies are going to change the world. He's not thinking about small projects and how to exit quickly and make some money. He's really thinking, how can we use venture capital to back companies that are going to transform the world in many, many different areas? And so that's really, I think, a foundational difference between Vinod and most other investors. So he has consistently championed technologies that are aimed at improving health and creating a better future for the world. I'll just list a few companies that he has backed very early, like one of the earliest investors in OpenAI, in Block or Square, which allows small merchants to be a part of the financial system. And then DoorDash and Rocket Lab and Guardant Health, and also Viome. He's a Series A major investor in Viome and has been such a big supporter of Viome. So we're just super grateful. So Vinod, thank you so much for so many things, as a member of society and as a co-founder of Viome and so on.
Guru: Welcome, Vinod. It's an honor for us that you joined us.
Vinod: No, happy to. Happy to. Very important. Very exciting times and an exciting topic to talk about.
Momo: Absolutely. Yeah. So let's focus on the future of medicine, focusing obviously on preventive medicine and the integration of AI. So I'll just start off with: okay, so we're shifting toward preventive medicine. We now have the tools and knowledge to get more involved, because so far medicine has been, to a very large degree, very reactionary, waiting until symptoms set in. So tell us please about your grand vision of true preventive medicine and how AI fits in that model.
Vinod: Well, the first thing to realize is AI has made enough progress. Modulo a few things that need to be fixed, and we can come back and talk about it, the expertise of any human doctor or researcher can be built into AI quite easily today. So the idea that we should gate or limit the amount of physician time is a silly idea now. It made sense when humans had to do the job, and you went to a nurse first, and then a doctor, a primary care doctor, and then a specialist. The more skilled the professional, the more gated the access to them. You went through four doctors before you saw a neurologist or a brain surgeon because they were more expensive. That notion is collapsing very quickly, because the cost of all expertise is a dollar or two an hour, and we shouldn't be gating it. That comes back to your question on preventive medicine. We don't use experts in preventive medicine because they're too expensive, but if they're near free, it's the cost to compute it, then we should use them abundantly as first-line therapy. So preventive medicine becomes much more feasible in the world of AI. We can also make it very available for the consumer, and we should talk about this. So I think the big issue in healthcare is engagement. People don't think about their health because they don't deal with it very often.
Momo: Exactly.
Vinod: In fact, the most frequent thing people deal with in their health is supplements or things like that. There was a recent study on Alexa: if you just reminded people of a chronic disease like hypertension or diabetes, simply, nothing fancy, just talking to them first thing in the morning with two or three questions, which is a reminder that you have the disease more than anything else, there was a dramatic reduction in blood pressure and blood sugar.
Momo: Wow.
Vinod: It says just reminding people is sufficient, and they're a little more cautious that day. In other parts of social media, we've learned how to engage users. This is one little example, but in the world of Facebook and TikTok and Instagram, we've learned how shades of color on the ad behind you dramatically change engagement. If we could do something similar for healthcare and engage people in some sort of more engaging thing, like, do you know the most recent science relevant to your condition? And I don't know exactly what that is, but we've done it in so many other spaces that we should be able to do it in healthcare. If we do, we've made huge progress. Then downstream of that, we can direct a lot of behavior and take advantage of the fact we were talking about earlier, which is that expertise is all free. Give them every specialist, because they all cost a dollar or two an hour.
Momo: Oh, go ahead, Guru.
Guru: No, I was going to say, every time I make a decision in my daily life, what to eat. I eat three times a day and snack and all of that stuff. And every time I go out to a restaurant or to buy groceries, or do things with other people that have to do with my health, which is, for example, exercise or play a game or something like this, every time something that is relevant to health happens in my life, I think your point is that if you somehow engage them and say, "Hey, this is what it means to your health," that keeps it front of mind, and maybe it'll change their behavior for a day. That makes a huge difference.
Vinod: Yeah, no, it'll make a huge difference. So you've seen a lot of talk about AI that sees what you see, hears what you hear. There are glasses that may be looking at your food and looking at the conversations. It uses that ambient listening and watching to trigger behavior and say, maybe you should have half that dessert.
Momo: Exactly. Yeah, you don't need four scoops of ice cream. I love this idea, Vinod. And I think that since you're a big investor, of course, this can potentially inspire many potential entrepreneurs here to think about how they can create a social media platform that both entertains people but also provides this sort of visual or audio guidance during the day.
Guru: You know what? I would call it ambient health, Momo. It's ambient health. It's around all the time.
Momo: Spontaneous health, daily health, everyday health, something like that. So entrepreneurs, think about how you can leverage existing technology such as video glasses and audio listening devices to basically remind people. And like Vinod said, maybe it's not something so intrusive that it's every minute of every day, but even just a gentle reminder in the morning, or maybe a couple of times a day, is going to make a big difference. So I think that basically a company that will engage people in preventive health, that's the key. Come up with a business idea and pitch it to Vinod, and maybe there'll be a big successful company there. Calling on all entrepreneurs.
Vinod: People are trying it, but yes, somebody will get it right, and then we will be on the path, because you can't have clinical interventions until first you have engagement.
Guru: Agreed. Exactly. And by the time you have clinical engagement, it may already be too late, right? Because these chronic diseases take so long to develop that by the time you realize that you need to go talk to a doctor, it's already probably quite a bit progressed.
Momo: Super important point. Yes. Okay. So we have a part of the demographic that's not yet engaged in preventive medicine, but we do have a part of the demographic that actually wants to actively pursue preventive medicine. And those guys are watching YouTube videos, they're listening to podcasts, they're reading scientific papers. They're really into this. They're testing different supplements, they're testing different diets. How can AI today, and what's it going to look like two, three, four years down the road, enable those people who are engaged to actually practice preventive medicine without having to go through four layers of specialists and doing a lot of testing that's guided by different doctors? Tell us about that please.
Vinod: Well, again, AI can help a lot. In the past, first it was expensive to take a blood test that had, say, a hundred variables every quarter. It's sort of what I do. I measure a hundred blood parameters every quarter. First, it's expensive, but then you have to have somebody go through the results and say, as a result of this test, you should do X. If your vitamin B12 is low, that's a pretty simple interpretation. But as you know, many of these relationships are complex and multivariate. And this is why I believe most of the studies that say vitamins and supplements don't help are wrong, because they didn't measure anything in the blood and then recommend a supplement. They just put together everybody taking the supplement and said, what was the result? If you don't need a supplement, then it's going to have no effect. And if 90% of the people don't need that particular supplement, then the results will be washed out by the 90% instead of the 10% who benefited. So I think the very nature of these studies has been pretty flawed. I haven't seen a good study.
Momo: Well, I'd like to add that they're also short-term. We have to think about our health as a decades-long process. And so giving someone a multivitamin pill for three months and then looking for clinical outcomes, you may not observe any changes in three months. It's just too short of a period.
Vinod: Absolutely. Absolutely. And most diseases, we used to be in the world of infectious diseases. We are now in the world of mostly chronic diseases as being the bulk of healthcare in the West. Chronic diseases start 30 years before they manifest. I remember doing a calcium scoring test when I was 30, 40 years ago. And I was in the 90th percentile, not unusual for Indians who are very at risk of cardiac disease. And I said, it'd be nice to do something. I talked to my doctor and he says, "Oh, don't worry about it. You're 30." I wish I had worried about it. So the establishment is not very good. Now AI can get very, very personalized and help define strategies and maybe even give you real trade-offs. If you want to put in this much effort, this is what you should do. Give you a menu of choices, or remind you periodically what the trade-offs are. So you can get extremely personalized, hyper-personalized with AI in a way you can't afford when you're using a physician making $250,000 a year, or a nutritionist or something. So hyper-personalized attention, attention to these details, deciding which are the right trade-offs. I'll give you my favorite study. It almost is unbelievable. Patients visiting the NHS service in the UK, just from their medical records, they're not visiting for cancer or oncology or any specific condition, you screen them. You can tell with fairly high sensitivity and specificity whether they have cancer from just the data in their medical record. And NHS records tend to be more complete than records here in the US. Way more sensitive than a test we think of as early cancer detection, like GRAIL. In fact, I would say they've detected a hundred times more cancers in the UK than GRAIL has detected worldwide.
Momo: And this is done by AI, or some algorithm that a computer at Oracle...
Vinod: Look, AI is algorithms, but yes. And so it's a dramatic enrichment of the population that should be tested for cancer. When you have a generic screening test like the GRAIL test, 1% of the people may have cancer, but the 99% false positives will swamp the results of the 1%. And so these statistics have to be understood well. You can't run screening tests unless there's some other criteria for screening, otherwise they're not cost-effective and they lead to a lot of heartburn from wrong information. But if you can enrich a population so you have a 60, 70% probability of having cancer, then it's worth looking. Then finding it six months earlier or 12 months earlier, which is what we found, it's pretty damn good. That's worth spending the money, because you'll save the money. And I don't know whether you call it preventive or post-preventive, but pre-these, whatever you call it.
Momo: Early detection.
Vinod: Screening.
Momo: That's when it...
Vinod: Becomes really cost-effective.
Momo: Yeah. So this is now a tool that is integrated into NHS, or not yet integrated?
Vinod: Well, they're doing it by patient record for primary care practices that want to screen their patients for it.
Momo: Okay. But this is...
Vinod: On the order of half a million people have been tested, and 15% of the people had an anomaly of this sort. Now, these are patients seeking help, so they're not a random population survey, but...
Momo: Still pretty impressive.
Vinod: Pretty impressive.
Momo: Pretty impressive. So let's talk about, when we talk about AI, let's get a little more specific. AI is sort of this system-wide capability, but let's talk about something a little more specific. So let's say there's a 50-year-old person and they have not paid attention to their health, but now they woke up and they're like, wow, I really want to intentionally, every day, do this. They're inspired to actually make daily changes in their nutrition and lifestyle. How can AI help them today? Do you recommend something like ChatGPT, or what is your recommendation today?
Vinod: You bring up an important point. I don't recommend things like Anthropic or ChatGPT straight out of the box. Why? We all know these systems hallucinate. So we just did a study using GPT-5, and the same is true of Google's AMIE product, and said, how good are they at triage? If you look at triage, they generally sound pretty damn good. But you look at the triage error rate, it's north of 30%, because of hallucination, because of other things like missed questions, questions the AI failed to ask in doing its differential diagnosis. Now, what we did, my son runs an AI primary care company called Cura, we have a whole harness around GPT-5. So they're using GPT-5, always using the best model, but the harness adds a whole bunch of other systems to complete the diagnosis, to add safety checks, to do the appropriate triage when you're uncertain, to a human being for now. With all these systems, the error rate went from 30% to 0%. It's a formal study they did. These systems with the harness reduce error rates. And that's what all the coding startups have also done, added harnesses that put constraints and safety-check systems, and that's the right way to do it. So these are specialized... Hold on. Let me...
Guru: Let me ask a question about the harnesses, because I think our audience here is both medical as well as AI oriented. So let's just get into a little bit more detail on the harness part. Does the harness use ground truth of any type that is curated well, or is it human-in-the-loop type of training for a significant period of time? What are the techniques people use for developing these harnesses?
Vinod: So there are many ways. There's literature, there are old systems. We've used every possible system. We've used medical records. None of them are particularly effective, but a safety system we've built off multiple experts, to put it more technically, a mixture-of-experts approach, with each system having a different slight bias, one for accuracy, one for imagination, one for exploration, you start to get the right answers. And so it takes years of iterative development beyond just GPT-5. But you want to do it in a way that when GPT-6 comes out, you use GPT-6. You don't set back to GPT-4 where you developed the system. So the harness has to be independent of the AI system you're using. I saw this publication in Nature called the fragile nature of GPT-4 or -5 in medicine. I looked at it and I said it's a complete abomination of how bad the researchers were in defining the problem. It wasn't GPT-5. They just used it the wrong way, because when we used it the right way, none of that showed up. Now, the flip side of it, which is equally important to talk about, is what I'd be comparing against. So Arnie Milstein, who's probably the best person on quality of medical care in this country, a very traditional MD, sits on most of the quality boards and things, did a study of complex diagnosis. It's a multicenter study with multiple academic medical centers. Human accuracy in doing complex diagnosis had 73% accuracy, which means 27% of the patients got the wrong or suboptimal diagnosis.
Momo: Or no diagnosis.
Vinod: Or no diagnosis. That's like, if you're driving to work in the morning, only once a week will you have an accident. Worse than that. So we have to compare to what is the best we have available, which is good doctors. And I'm not critiquing doctors here, because medicine has improved every decade for the last hundred years. It's gotten better and better and better, but it's not good enough if we have a better alternative. When we have an alternative, we have to use that. AI with the right kind of safety and triage and other accompaniments is so much better than humans. We should always use that first. And we should get to this issue of what it will take to do that. There's a fundamental problem in the FDA system, but if that's available, let me finish my story. 73% accuracy. Then they used an AI system. It had 88% accuracy. Then they gave the AI to the doctors to use. And guess what? The doctors improved but degraded the AI. So they improved from 73% to 76, but the AI degraded from 88 to 76.
Momo: Yikes.
Vinod: So doctors made the AI worse, because they have prebuilt biases. They have recency bias. Recently I saw a patient like this, or I just read about ADHD in the New York Times, so maybe you have an ADHD diagnosis. It's well established: the New York Times publishes an article on ADHD, the diagnosis goes up the following few weeks, because there's this recency bias. Humans have about 20 different types of biases. I first met Arnie Milstein because many years ago he was characterizing the kinds of biases that show up in human-driven medicine, long before AI was even a thing. And so these biases do show up. So we have to say the right AI systems can do much better than humans, and every diagnosis should start there. My son's company, almost all the dialogue is handled by the AI directly with the patient today. Almost all of it. The AI might do 20 questions back and forth because of regulatory requirements. When the AI is done, it makes a diagnosis, maybe testing recommendations, maybe prescription recommendations, including dosage and all that, but they can't give it to the patient. So a physician comes on, qualified in that state, and asks a few more questions, maybe adds three or four more questions, and then they can issue a prescription, which is fine for now because it helps verification of the system. But in the end, the right system should be able to work. So that leads to the question, what's the right way to say, "Hey, GPT-5 is not good enough, but your AI system is better," or "Anthropic isn't good enough, some other system is better"? We have a process for that, which is called FDA approval. If we have FDA approval of software as a medical device, which is a known category, then we should be able to do it. Only one problem: you have to do it de novo, or you can have a predicate device. I've argued with the FDA that humans should be a predicate device to compare any new software device's performance against.
Guru: Very interesting.
Vinod: Congress never anticipated that, so it's not in the FDA mandate formally, either included or excluded. So Congress just has to clarify language saying it's okay to use humans as a predicate device, in which case you would have a mechanism to approve a new doctor, say, if it performs better than humans.
Guru: That makes sense. Wow.
Vinod: So that's what's needed. And it doesn't matter whether it's oncology or radiology or primary care or gastroenterology. It's the same mechanism. The nice thing in AI is the primary care physician is also a great gastroenterologist, because it's the same AI, or the best endocrinologist, because it's the same AI. People haven't gotten this notion. So we keep putting AI back in the old context instead of imagining how the system should look in this world. So that's probably the starting point. There are a couple of other things that we don't talk a lot about in medicine. A big thing in medicine in the US is medical fraud. Every AI encounter will be auditable. In fact, you could audit 100% of them offline. And so you could ensure nothing got coded that shouldn't have been coded, because you have the exact conversation between the AI and the patient, and another AI can monitor for fraud. That's what we do in financial systems for fraud. We have systems monitoring the transactions and fraud and history-taking and all that stuff. So we could eliminate fraud, and that would really remove a lot of the constraints. Half the constraints in medicine are because we are afraid of fraud. So there are a lot of consequences downstream for this system.
Momo: Okay. I have some questions, Vinod. So going back to that 50-year-old who wants to get into longevity medicine, that person wants to delay disease onset for as long as possible. So there's this Cura, which is your son's company. Is that covered by insurance? Can anyone just go to Cura and get healthcare there?
Vinod: Yes, they can. And Cura will build their health insurer. By the way, you can access Cura on the Walmart website too.
Momo: Okay, great. Okay. So that's basically the democratization of AI access and healthcare. That's basically the best tool. But there is...
Vinod: Still a problem. The American Medical Association is the one that approves CPT codes. They approve what gets paid and what doesn't and how much. It's based on physician time. Physician time in AI is approaching zero. And every time Cura does a visit, some doctor doesn't get an in-clinic visit, so they don't get paid. The AMA has generally been opposed to the use of AI because it reduces their billings. And most insurers, against their own interest, are paying less for an AI encounter than for an in-clinic encounter, which is silly. An in-clinic encounter might cost $150. Your patient goes to a doctor, that visit is billed $150 depending upon where and who and all that. If a patient does telemedicine, they get paid $50 by the same insurer for the same visit, when it could be 10 times cheaper if it was AI only, with much more auditability, much more accuracy. But insurers aren't yet paying at parity because they have doctors and the AMA controlling payment mechanisms. The fundamental problem of AI in medicine is not AI's performance in medicine. It's the reimbursement of AI-based medicine. And there are established interests who benefit a lot from the current system that don't want it to change. That's a big problem. So I wrote a blog in the beginning of 2025 for JPM saying AI in medicine really works well in capitated care or at-risk care or Medicare Advantage, not when you're paid per visit, because then you're trying to maximize the number of visits, not maximize patient care. In Medicare Advantage, in capitated care or IPAs, you are trying to minimize the number of visits yet meet all the patient's needs and not have their condition escalate where it becomes even more expensive for you, because you are at risk. Of course, there's this additional issue: most patients are paid by an insurer for one or two or three years, but not for 10 years. And so if you do much more preventive medicine, you're not going to get the benefit for four or five years, and the patient may not be your patient as a payer.
Guru: So Vinod, along those lines, I had two points to connect to preventive medicine. One, when we focus on preventive medicine, you may not have enough encounters with doctors or claims or lab data or anything else. Therefore, you may not have data in the UK Biobank or in the NHS health system, because you're still working like you normally work in your day-to-day life and you're trying to do the best you can to prevent diseases. So number one, do you think that molecular data, let's say non-invasive molecular data like what we are trying to do in Viome with stool, with saliva, with finger-prick blood and so forth, is that a necessary, essential component for achieving this idea of preventive medicine, even before you engage with the...
Vinod: I'm glad you brought this up, because I didn't answer Momo's question earlier around supplements. It may be one supplement, but it may be you need three things fixed for the system to behave differently. There's a great set of science in network medicine by a professor at Northeastern. He has a book called Network Medicine, where it's gene networks that affect the result. So it's not a single point of intervention. Now, taking it beyond supplements and all that to molecular medicine, if you know what's happening to the transcriptome of the body, it helps a lot to know what genes you're trying to drug regularly. So today's clinical medicine, humans can barely do, because there's so much science, new science every year. When you add molecular medicine, what do you do with a million transcriptomes? And what do you do with a million transcriptomes for the microbiome and the corresponding body's reaction, the human transcriptome in the blood? Which is the exciting part about Viome. You get what the microbiome's doing, and you get the body's response, the host's response to the microbiome, which depends on everything you eat. That kind of complex system can only be tackled by an AI. There's no hope a human being can ever do complex systems. So whenever a system is high-dimensionality, humans can't handle it. Many, many years ago, I think it was 2001, I was a postdoc at the Santa Fe Institute. And I did a little bit of work with this professor who was there. I was a postdoc for four months. My geeky side, I took a sabbatical from venture capital to be a postdoc at the Santa Fe Institute. I moved there with the whole family. The human body, just in the blood, is a few thousand metabolic pathways interacting through one mixing agent, which is the blood. Each marker doing multiple things. So it's not a simple system, and biology didn't design it to be elegant, just to be functional and efficient. AI can inverse that and build a model for human biology. That's real medicine. In 2016, I wrote a hundred-page document called "20% Doctor Included." I was wrong. It doesn't need to be 20%. I was trying to be polite to doctors, but these complex systems are far beyond human comprehension. We no longer let humans mostly fly planes. It's too complex. Why should we let humans manage a system with 3,000 metabolic pathways in one complex system? You add other organs like the brain and organ-level behavior, you're talking about very, very complex systems only AI can handle. There is no other way except AI. Humans have no role in this kind of molecular medicine. And when we do it the right way, with the kinds of data that Viome is collecting, the variables you're collecting, all that interacted together, you are going to get much higher quality medicine at a fraction of the price, and much more globally accessible. In 2016, I wrote about this, and I talked about molecular medicine in 2016 and what AI would do. It's on our website. It's on the web somewhere. "20% Doctor Included." I said, very likely. And today I believe this more than ever. In a village in India, I will get better cardiac care than I will get at Stanford. Why? Because the human expert will still be here, and there'll be no human expert in this village in India, so we'll rely on AI and get better care.
Guru: They will leapfrog the human expert and go directly to AI.
Vinod: Absolutely. And so I do absolutely believe this. I first wrote about all this in 2012, a blog in TechCrunch called "Do We Need Doctors." In 2016, I expanded it into a hundred-page thesis on medicine. And we don't know how bad medicine is today. It's the best it can be. It's the best it's ever been, but it's still pretty bad. And I'd define where it is today, or where it was in 2016, and go on to say where it needs to go. But molecular medicine is absolutely a critical part of this.
Guru: Thank you. So 2016 to 2026, 10 years since you wrote that paper. Do you see all of your predictions from 2016 happening today? And then I want to know what you think will happen in the next 10 years, like 2036.
Vinod: I would say in 2016 I thought it would take 25 years, or till 2040, to get there. I was wrong. It's happened now. So in 2016, I was wrong by 15 years in the first 10 years. I was too pessimistic. I think, look, the thing that gets in the way is regulation. The thing that gets in the way is human biases and humans' unwillingness to believe that AI can be better.
Momo: And the systems that are in place already.
Vinod: Yeah. And so we can talk about what it will take to break this system.
Guru: Yes, please. Let's do that.
Vinod: And extend it all the way into molecular medicine, wearable medicine. We can read facial expressions. There was a great sleep study foundation model, based on sleep studies out of Stanford, that recently detected 120 disease conditions. Now, granted, it was retrospective, so it's not a true study, but even with the caveat, they detected 120 different disease conditions in patients from just their sleep study data. These are patients who went into a sleep clinic to get a sleep study done because they had a sleep condition, nothing to do with the 119 other conditions they may have, but all detectable in EEG data. That's pretty stunning. Even I couldn't believe it. All those signals will come to pass and be part of medicine by 2035, if we let it. If the establishment lets it. Imagine cutting the cost of healthcare in half. How many people would object to it? It's their bread and butter. In fact, very likely in 10 years we can cut it by 75%. I just saw an article on the first humanoid robots doing surgery on animals. I just saw that this week. So everything can be reduced by 75%. Even medicines can be changed. We haven't talked about pharmaceuticals. We are starting a new effort. So on our website is a talk by Sid Sijbrandij. Sid was the CEO of a software company, GitLab. Any software person knows GitLab. He was a founder in our portfolio. Company done real well, went public, then he got cancer. And the doctors gave him very little time. So he decided he'd be his own medical director, orchestrate his own care, from directing his care to designing his own cancer vaccines with AI to designing small drugs, everything he could throw at it. Five years later, he's still alive, doing real well. And this was before AI was mature. And now AI is mature. So a software engineer with no knowledge of medicine outpaced any possible treatment the medical establishment, through the care pathway they had established, could do. He did much, much better with no knowledge of medicine, just because he needed to save his own life.
Guru: So Vinod, how do we get past the establishment? I mean, this is a big question for the next 10 years, so please help us think through that.
Vinod: So what's different today? Almost certainly most cancer patients will be able to design their own care and have it be cheaper than taking Keytruda. We have a company called Nabla. It can design an antibody to any antigen. So we can figure out the antigens on your cancer cells, design an antibody. Soon we'll be able to do bispecific or trispecific antibodies for your cancer cells. So personalized care, what I call N-equal-to-one medicine, will be possible. Why? Because the expertise is free, so you don't need somebody to design one drug for a billion people. It's so cheap, you can design it for one person. You can bypass regulatory mostly, because you can't have a trial if your population size is one. How do you do a trial? So you'll probably have to go through approval of the process, not the drug. So lots of interesting things ahead of us, lots of uncertainty, lots of regulatory barriers, but a pretty exciting time.
Momo: Amazing. Very, very exciting. Super amazing. We could go on for hours, but let's go ahead and switch to investments. We had a series of questions for you, but we're just going to narrow it down to one. What are you excited about in terms of companies pitching to you for investments? What are you hoping for in the next, let's say, 12 months, that you're going to get a pitch for that you think is going to make the biggest advancement in this integration of AI into healthcare?
Vinod: Well, very narrowly, I would say N-equal-to-one medicine. And whether it's for inflammatory disease, you've got tens of billions of dollars of value of a single drug that's supposed to serve seven or eight billion people in the anti-TNF inhibitor set. But you could do it for one person based on their transcriptome. Maybe you have CAR-T therapy for their immune cells that are their autoimmune cells. It's starting to happen and starting to be tried in diseases like long COVID and ME/CFS. That's pretty exciting.
Momo: Okay. But it needs to be...
Vinod: It needs to be scalable and inexpensive, and doing well with patient engagement. That's not fancy. That's sort of normal software product management. So there's a wide range. I think most diseases are curable in the next 10 years. They can get very specific to a patient, detecting chronic disease early and preventing it for people who want it prevented. I wish I had some tools 40 years ago. I'm 72 now. When I said, oh, I got my calcium score as a curiosity, and then when I got it in the 90th percentile, I got scared, but there was nothing to do. Nobody would do anything in the medical establishment. By the way, I'm probably the only person who's had cardiac bypass surgery without ever having a symptom. Bypassing every treadmill test. I just said, I'm looking at the level of LAD occlusion. I'm going to have a bypass, and then I'm going to do preventive care on top. And I believe that's saved my life.
Guru: Yes, preventive.
Vinod: I don't consider myself as having diabetes, which I did at age 40. I don't consider myself today as having cardiac disease, though my medical record says I had bypass surgery. I do annual checks on all these things at that fine-grained level, and I design solutions. But this is not possible for every person. But when it's embodied in an AI that can go to the molecule level, it'll be possible for every person to do.
Guru: Amazing. Absolutely amazing. Vinod, as a final question, can I ask one last question before we go? So there are people who believe that longevity medicine is getting to the point where, in the not too distant future, I don't know exactly what the timeframe is going to be, but in the not too distant future, every year that actually passes, you will actually get a little bit younger than a year, because of...
Vinod: Well, the right way to put it is, it's reasonable to say by 2035 or 2040, you'll gain more than one year of life expectancy every year you're alive.
Guru: There you go. There you go. So that'll happen in your lifetime, our lifetime, right? So you expect that to happen in 2040. And what do you think are going to be the biggest breakthroughs to get there?
Vinod: Well, it's hard to tell. There's simple stuff to do. I recommend anybody over the age of... I used to say anybody over the age of 65. Now I say anybody over the age of 55 should take rapamycin. It's not proven, though I personally financed some clinical studies in things like long COVID and ME/CFS, and the results are pretty damn good. Most people don't know about these studies, but they were done for a disease condition, not for general longevity. But the data is pretty... the risk-reward is very much in favor of taking rapamycin after age 55. And it's an immune regulator, not an immune suppressor, which is where most doctors think it's an immune suppression agent. It's an immune regulator.
Momo: Depends on the concentration, right?
Vinod: One can never be certain. So the risk-reward is clear. There are other things you can do that are higher risk and higher reward, and the older you get, the more risk you should take. The younger you are, the fewer risks, but you have a better chance of fixing the problem, or not letting it progress. So every person has to make their own decision here on longevity. No question. We are starting to make rapid progress on point solutions in longevity. At some point it'll evolve into a full systemic solution for longevity. The good news, for the first time ever, and the FDA didn't consider aging as a disease, it gave us aging as an indication in dogs in one of our companies called Loyal. You can have a claim of longevity or aging. And that's a good start. Doing it in dogs first then lets you go to humans, because age wasn't considered a disease, it was natural. But people didn't consider the fact that almost all diseases of aging go up dramatically in risk as you age. So they are all diseases of aging. Though aging may not be a disease, it should be considered a disease.
Momo: Amazing.
Vinod: So I'm not a fan of living forever either. I'm much more for health span over lifespan.
Momo: Of course.
Vinod: Society would be too static, too many MAGA people still hanging around.
Guru: Yeah, we need recycling in society.
Vinod: Absolutely, we need recycling in society.
Momo: Fresh ideas. Excellent. Vinod, it's been a huge pleasure to host you. We value your advice and your opinions, and we will see you again whenever we can get together and host you again to see how your predictions are working out.
Guru: We look forward to doing that again. Thank you so much.
Momo: Great. Thank you. Thank you, Vinod. Best wishes.
Vinod: Thanks.
Momo: Wow, that was great to have Vinod, and we could have talked for hours. He's got just so much experience and knowledge. It's amazing.
Guru: Yeah, it is. Just to remind you... actually, you know what? Hopefully we'll be able to get him back on the show in, let's say, six months or a year or something, and talk about all the progress that's happening right now.
Momo: Of course, we can get him back anytime. He's a friend of both us and Viome. So yeah, it's going to be very easy. Okay, so the Viome Monthly Challenge, just a reminder that for July, we're still just looking for good questions posted on our episode. So just ask away, and we will pick the best question posted in July, and that person will win a Full Body Intelligence Test from Viome. And then go ahead, Guru, what's in the next episode?
Guru: Yeah. So our audience may remember that we announced we have a new product called Gut Health Pro now, for providers, gastroenterologists, longevity medicine doctors, functional medicine doctors, and so forth who are interested in gut health. So this coming episode, we are going to have a deep dive into the Gut Health Pro product. We're going to talk about what the capabilities are, what the clinical utility of this test is. And we're going to talk about many use cases, decision support that could be helpful for people and so forth, specifically for doctors and patients also to know what would be useful for them from this test. And we are going to have a special guest who is a gastroenterologist. His name is Dr. Mike Bass. He's definitely a very valuable member of our team and also practices gastroenterology every day, every week, and has a lot of experience in this space, with both entrepreneurial activities as well as his MD-based medical practice and so on. So it's going to be tremendous, talking to him about the full spectrum, the breadth and the depth of the Gut Health Pro test.
Momo: Yeah, a sneak peek there is when we talked to Vinod about molecular medicine. This is truly an example of a product that's currently available on the market. Providers can actually order it today, and it's really measuring the deepest, deepest corners of human biology, understanding which parts are functioning fine and which parts are not functioning fine, and how to fix those parts that are not functioning fine, years or decades before disease onset. So that's pretty amazing.
Guru: Absolutely.
Momo: All right, so I'm Momo, a biochemist.
Guru: And I'm Guru, a data and AI scientist. We're two PhDs on a pod. See everybody in a couple of weeks.
Momo: See you next time. Thank you.
Guru: Bye.
