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Owen Tripp: Why Can't I Find and Get to the Right Doctor? Jul 13, 2025

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Eric Topol (00:06):Hello, this is Eric Topol from Ground Truths, and I'm delighted to welcome Owen Tripp, who is a CEO of Included Health. And Owen, I'd like to start off if you would, with the story from 2016, because really what I'm interested in is patients and how to get the right doctor. So can you tell us about when you lost your hearing in your right ear back, what, nine years ago or so?Owen Tripp (00:38):Yeah, it's amazing to say nine years, Eric, but obviously as your listeners will soon understand a pretty vivid memory in my past. So I had been working as I do and noticed a loss of hearing in my right ear. I had never experienced any hearing loss before, and I went twice actually to a sort of national primary care chain that now owned by Amazon actually. And they described it as eustachian tube dysfunction, which is a pretty benign common thing that basically meant that my tubes were blocked and that I needed to have some drainage. They recommended Sudafed to no effect. And it was only a couple weeks later where I was walking some of the senior medical team at my company down to the San Francisco Giants game. And I was describing this experience of hearing loss and I said I was also losing a little bit of sensation in the right side of my face. And they said, that is not eustachian tube dysfunction. And well, I can let the story unfold from there. But basically my colleagues helped me quickly put together a plan to get this properly diagnosed and treated. The underlying condition is called vestibular schwannoma, even more commonly known as an acoustic neuroma. So a pretty rare benign brain tumor that exists on the vestibular nerve, and it would've cost my life had it not been treated.Eric Topol (02:28):So from what I gather, you saw an ENT physician, but that ENT physician was not really well versed in this condition, which is I guess a bit surprising. And then eventually you got to the right ENT physician in San Francisco. Is that right?Owen Tripp (02:49):Well, the first doctor was probably an internal medicine doctor, and I think it's fair to say that he had probably not seen many, if any cases. By the time I reached an ENT, they were interested in working me up for what's known as sudden sensorineural hearing loss (SSHL), which is basically a fancy term for you lose hearing for a variety of possible pathologies and reasons, but you go through a process of differential diagnosis to understand what's actually going on. By the time that I reached that ENT, the audio tests had showed that I had significant hearing loss in my right ear. And what an MRI would confirm was this mass that I just described to you, which was quite large. It was already about a centimeter large and growing into the inner ear canal.Eric Topol (03:49):Yeah, so I read that your Stanford brain scan suggested it was about size of a plum and that you then got the call that you had this mass in your brainstem tumor. So obviously that's a delicate operation to undergo. So the first thing was getting a diagnosis and then the next thing was getting the right surgeon to work on your brain to resect this. So how did you figure out who was the right person? Because there's only a few thousand of these operations done every year, as I understand.Owen Tripp (04:27):That's exactly right. Yeah, very few. And without putting your listeners to sleep too early in our discussion, what I'll say is that there are a lot of ways that you can actually do this. There are very few cases, any approach really requires either shrinking or removing that tumor entirely. My size of tumor meant it was really only going to be a surgical approach, and there I had to decide amongst multiple potential approaches. And this is what's interesting, Eric, you started saying you wanted to talk about the patient experience. You have to understand that I'm somebody, while not a doctor, I lead a very large healthcare company. We provide millions of visits and services per year on very complex medical diagnoses down to more standard day-to-day fare. And so, being in the world of medical complexity was not daunting on the basics, but then I'm the patient and now I have to make a surgical treatment decision amongst many possible choices, and I was able to get multiple opinions.Owen Tripp (05:42):I got an opinion from the House clinic, which is closer to you in LA. This is really the place where they invented the surgical approach to treating these things. I also got an approach shared with me from the Mayo Clinic and one from UCSF and one from Stanford, and ultimately, I picked the Stanford team. And these are fascinating and delicate structures as you know that you're dealing with in the brain, but the surgery is a long surgery performed by multiple surgeons. It's such an exhausting surgery that as you're sort of peeling away that tumor that you need relief. And so, after a 13 hour surgery, multiple nights in the hospital and some significant training to learn how to walk and move and not lose my balance, I am as you see me today, but it was possible under one of the surgical approaches that I would've lost the use of the right side of my face, which obviously was not an option given what I given what I do.Eric Topol (06:51):Yeah, well, I know there had to be a tough rehab and so glad that you recovered well, and I guess you still don't have hearing in that one ear, right?Owen Tripp:That's right.Eric Topol:But otherwise, you're walking well, and you've completely recovered from what could have been a very disastrous type of, not just the tumor itself, but also the way it would be operated on. 13 hours is a long time to be in the operating room as a patient.Owen Tripp (07:22):You've got a whole team in there. You've got people testing nerve function, you've got people obviously managing the anesthesiology, which is sufficiently complex given what's involved. You've got a specialized ENT called a neurotologist. You've got the neurosurgeon who creates access. So it's quite a team that does these things.Eric Topol (07:40):Yeah, wow. Now, the reason I wanted to delve into this from your past is because I get a call or email or whatever contact every week at least one, is can you help me find the right doctor for such and such? And this has been going on throughout my career. I mean, when I was back in 20 years ago at Cleveland Clinic, the people on the board, I said, well, I wrote about it in one of my books. Why did you become a trustee on the board? And he said, so I could get access to the right doctor. And so, this is amazing. We live in an information era supposedly where people can get information about this being the most precious part, which is they want to get the right diagnosis, they want to get the right treatment or prevention, whatever, and they can't get it. And I'm finding this just extraordinary given that we can do deep research through several different AI models and get reports generated on whatever you want, but you can't get the right doctor. So now let's go over to what you're working on. This company Included Health. When did you start that?Owen Tripp (08:59):Well, I started the company that was known as Grand Rounds in 2011. And Grand Rounds still to this day, we've rebranded as Included Health had a very simple but powerful idea, one you just obliquely referred to, which is if we get people to higher quality medicine by helping them find the right level and quality of care, that two good things would happen. One, the sort of obvious one, patients would get better, they'd move on with their lives, they'd return to health. But two and critically that we would actually help the system overall with the cost burden of unnecessary, inappropriate and low quality care because the coda to the example you gave of people calling you looking for a physician referral, and you and I both know this, my guess is you've probably had to clean plenty of it up in your career is if you go to the wrong doctor, you don't get out of the problem. The problem just persists. And that patient is likely to bounce around like a ping pong ball until they find what they actually need. And that costs the payers of healthcare in this country a lot of money. So I started the company in 2011 to try to solve that problem.Eric Topol (10:14):Yeah, one example, a patient of mine who I've looked after for some 35 years contacted me and said, a very close friend of mine lives in the Palm Springs region and he has this horrible skin condition and he's tortured and he's been to six centers, UCSF, Stanford, Oregon Health Science, Eisenhower, UCLA, and he had a full workup and he can't sleep because he's itching all the time. His whole skin is exfoliating and cellulitis and he had biopsies everywhere. He’s put on all kinds of drugs, monoclonal antibodies. And I said to this patient of mine I said, I don't know, this is way out of my area. I checked at Scripps and turns out there was this kind of the Columbo of dermatology, he can solve any mystery. And the patient went to see him, and he was diagnosed within about a minute that he had scabies, and he was treated and completely recovered after having thousands and thousands of dollars of all these workups at these leading medical centers that you would expect could make a diagnosis of scabies.Owen Tripp (11:38):That’s a pretty common diagnosis.Eric Topol (11:40):Yeah. I mean you might expect it more in somebody who was homeless perhaps, but that doesn't mean it can't happen in anyone. And within the first few minutes he did a scrape and showed the patient under the microscope and made a definitive diagnosis and the patient to this day is still trying to pay all his bills for all these biopsies and drugs and whatnot, and very upset that he went through all this for over a year and he thought he wanted to die, it was so bad. Now, I had never heard of Included Health and you have now links with a third of the Fortune 100 companies. So what do you do with these companies?Owen Tripp (12:22):Yeah, it's pretty cool. These companies, so very large organizations like Walmart and JPMorgan Chase and the rest of the big pioneers of American industry and business put us in as a benefit to help their employees have the same experience that I described to provide almost Eric Topol like guidance service to help people find access to high quality care, which might be referring them into the community or to an academic medical center, but often is also us providing care delivery ourselves through on-demand primary care, urgent care, behavioral health. And now just last year we introduced a couple of our first specialty lines. And the idea, Eric, is that these companies buy this because they know their employees will love it and they do. It is often one of, if not the most highly rated benefits available. But also because in getting their employees better care faster, the employees come back to work, they feel more connected to the company, they're able to do better and safer and higher quality work. And they get more mileage out of their health benefits. And you have to remember that the costs of health benefits in this country are inflating even in this time of hyperinflation. They're inflating faster than anything else, and this is one of most companies, number one pain points for how they are going to control their overall budget. So this is a solution that both give them visibility to controlling cost and can deliver them an excellent patient experience that is not an offer that they've been able to get from the traditional managed care operators.Eric Topol (14:11):So I guess there's a kind of multidimensional approach that you're describing. For one, you can help find a doctor that's the right doctor for the right patient. And you're also actually providing medical services too, right?Owen Tripp (14:27):That's right.Eric Topol (14:30):Are these physicians who are employed by Included Health?Owen Tripp (14:34):They are, and we feel very strongly about that. We think that in our model, we want to train people, hire people in a specific way, prepare them for the kind of work that we do. And there's a lot we could spend time talking about there, but one of the key features of that is teamwork. We want people to work in a collaborative model where they understand that while they may be expert in one specific thing that is connected to a service line, they're working in a much broader team in support of the member, in support of that patient. And we talk about the patients being very first here, and you and I had a laugh on this in the past, so many hospitals will say we're patient first. So many managed care companies will say they're patient first, but it is actually hard the way that the system is designed to truly be patient first. At Included Health, we measure whether patients will come back to us, whether they tell their friends about us, whether they have high quality member satisfaction and are they living more healthy days. So everybody gets surveyed for patient reported outcomes, which is highly unusual as you know, to have both the clinical outcomes and the patient reported outcomes as well.Eric Topol (15:41):Is that all through virtual visits or are there physical visits as well?Owen Tripp (15:47):Today that is all through virtual visits. So we provide 24/7/365 access to urgent care, primary care, behavioral health, the start of the specialty clinic, which we launched last year. And then we provide support for patients who have questions about how these things are going to be billed, what other benefits they have access to. And where appropriate, we send them out to care. So obviously we can't provide all the exams virtually. We can't provide everything that a comprehensive physical would today, but as you and I know that is also changing rapidly. And so, we can do things to put sensors and other observational devices in people's homes to collect that data positively.Eric Topol (16:32):Now, how is that different than Teladoc and all these other telehealth based companies? I mean because trying to understand on the one hand you have a service that you can provide that can be extremely helpful and seems to be relatively unique. Whereas the other seems to be shared with other companies that started in this telehealth space.Owen Tripp (16:57):I think the easiest way to think about the difference here is how a traditional telemedicine company is paid and how we're paid because I think it'll give you some clue as to why we've designed it the way we've designed it. So the traditional telehealth model is you put a quarter in the jukebox, you listen to a song when the song's over, you got to get out and move on with the rest of your life. And quite literally what I mean is that you're going to see one doctor, one time, you will never see that same doctor again. You are not going to have a connected experience across your visits. I mean, you might have an underlying chart, but there's not going to be a continuity of care and follow up there as you would in an integrated setting. Now by comparison, and that's all derived from the fact that those telehealth companies are paid by the drink, they're paid by the visit.Owen Tripp (17:49):In our model, we are committing to a set of experience goals and a set of outcomes to the companies that you refer to that pay our bill. And so, the visits that our members enjoy are all connected. So if you have a primary care visit, that is connected to your behavioral health visit, which is great and is as it should be. If you have a primary care appointment…

Full show notes at the publisher

Priscilla Chan & Jennifer Doudna: New Center for Pediatric CRISPR Cures Jul 08, 2025

Show notes

Eric Topol (00:05):Hello, it's Eric Topol from Ground Truths, and I've got some really exciting stuff to talk to you about today. And it's about the announcement for a new Center for pediatric CRISPR Cures. And I'm delight to introduce doctors Jennifer Doudna and Priscilla Chan. And so, first let me say this is amazing to see this thing going forward. It's an outgrowth of a New England Journal paper and monumental report on CRISPR in May. [See the below post for more context]Let me introduce first, Dr. Doudna. Jennifer is the Li Ka Shing Chancellor's Chair and a Professor in the departments of chemistry and of molecular and cell biology at the University of California Berkeley. She's also the subject of this book, one of my favorite books of all time, the Code Breaker. And as you know, the 2020 Nobel Prize laureate for her work in CRISPR-Cas9 genome editing, and she founded the Innovative Genomics Institute (IGI) back 10 years ago. So Jennifer, welcome.Jennifer Doudna (01:08):Thank you, Eric. Great to be here.Eric Topol (01:10):And now Dr. Priscilla Chan, who is the co-founder of the Chan Zuckerberg Initiative (CZI) that also was started back in 2015. So here we are, a decade later, these two leaders. She is a pediatrician having trained at UCSF and is committed to the initiative which has as its mission statement, “to make it possible to cure, prevent, and manage all diseases in this century.” So today we're going to talk about a step closer to that. Welcome, Priscilla.Priscilla Chan (01:44):Thank you. Thanks for having me.Eric Topol (01:46):Alright, so I thought we'd start off by, how did you two get together? Have you known each other for over this past decade since you both got all your things going?Jennifer Doudna (01:56):Yes, we have. We've known each other for a while. And of course, I've admired the progress at the CZI on fundamental science. I was an advisor very early on and I think actually that's how we got to know each other. Right, Priscilla?Priscilla Chan (02:11):Yeah, that's right. We got to know each other then. And we've been crisscrossing paths. And I personally remember the day you won the Nobel Prize. It was in the heart of the pandemic and a lot of celebrations were happening over Zoom. And I grabbed my then 5-year-old and got onto the UCSF celebration and I was like, look, this is happening. And it was really cool for me and for my daughter.Eric Topol (02:46):Well, it's pretty remarkable convergence leading up to today's announcement, but I know Priscilla, that you've been active in this rare disease space, you've had at CZI a Rare As One Project. Maybe you could tell us a bit about that.Priscilla Chan (03:01):Yeah, so at CZI, we work on basic science research, and I think that often surprises people because they know that I'm a pediatrician. And so, they often think, oh, you must work in healthcare or healthcare delivery. And we've actually chosen very intentionally to work in basic science research. In part because my training as a pediatrician at UCSF. As you both know, UCSF is a tertiary coronary care center where we see very unusual and rare cases of pediatric presentations. And it was there where I learned how little we knew about rare diseases and diseases in general and how powerful patients were. And that research was the pipeline for hope and for new discoveries for these families that often otherwise don't have very much access to treatments or cures. They have a PDF that maybe describes what their child has. And so, I decided to invest in basic science through CZI, but always saw the power of bringing rare disease patient cohorts. One, because if you've ever met a parent of a child with rare disease, they are a force to be reckoned with. Two, they can make research so much better due to their insights as patients and patient advocates. And I think they close the distance between basic science and impact in patients. And so, we've been working on that since 2019 and has been a passion of ours.Eric Topol (04:40):Wow, that's great. Now Jennifer, this IGI that you founded a decade ago, it's doing all kinds of things that are even well beyond rare diseases. We recently spoke, I know on Ground Truths about things as diverse as editing the gut microbiome in asthma and potentially someday Alzheimer’s. But here you were very much involved at IGI with the baby KJ Muldoon. Maybe you could take us through this because this is such an extraordinary advance in the whole CRISPR Cures story.Jennifer Doudna (05:18):Yes, Eric. It's a very exciting story and we're very, very proud of the teamwork that went into making it possible to cure baby KJ of his very rare disease. And in brief, the story began back in August of last year when he was born with a metabolic disorder that prevented him from digesting protein, it's called a urea cycle disorder and rare, but extremely severe. And to the point where he was in the ICU and facing a very, very difficult prognosis. And so, fortunately his clinical team at Children's Hospital of Philadelphia (CHOP) reached out to Fyodor Urnov, who is the Director of Translational Medicine at the IGI here in the Bay Area. They teamed up and realized that they could quickly diagnose that child because we had an IRB approved here at the IGI that allowed us to collect patient samples and do diagnosis. So that was done.Jennifer Doudna (06:26):We created an off-the-shelf CRISPR therapy that would be targeted to the exact mutation that caused that young boy's disease. And then we worked with the FDA in Washington to make sure that we could very safely proceed with testing of that therapy initially in the lab and then ultimately in two different animal models. And then we opened a clinical trial that allowed that boy to be enrolled with, of course his parents' approval and for him to be dosed and the result was spectacular. And in fact, he was released from the hospital recently as a happy, healthy child, gaining lots of weight and looking very chunky. So it's really exciting.Eric Topol (07:16):It's so amazing. I don't think people necessarily grasp this. This timeline [see above] that we'll post with this is just mind boggling how you could, as you said Jennifer, in about six months to go from the birth and sequencing through cell specific cultures with the genome mutations through multiple experimental models with non-human primates even, looking at off-target effects, through the multiple FDA reviews and then dosing, cumulatively three dosing to save this baby's life. It really just amazing. Now that is a template. And before we go to this new Center, I just wanted to also mention not just the timeline of compression, which is unimaginable and the partnership that you've had at IGI with I guess Danaher to help manufacture, which is just another part of the story. But also the fact that you're not just even with CRISPR 1.0 as being used in approvals previously for sickle cell and β-thalassemia, but now we're talking about base editing in vivo in the body using mRNA delivery. So maybe you could comment on that, Jennifer.Jennifer Doudna (08:38):Yeah, very good point. So yeah, we used a version of CRISPR that was created by David Liu at the Broad Institute and published and available. And so, it was possible to create that, again, targeted to the exact mutation that caused baby KJ’s disease. And fortunately, there was also an off-the-shelf way to deliver it because we had access to lipid nanoparticles that were developed for other purposes including vaccinations. And the type of disease that KJ suffered from is one that is treatable by editing cells in the liver, which is where the lipid nanoparticle naturally goes. So there were definitely some serendipity here, but it was amazing how all of these pieces were available. We just had to pull them together to create this therapy.Eric Topol (09:30):Yeah, no, it is amazing. So that I think is a great substrate for starting a new Center. And so, maybe back to you Priscilla, as to what your vision was when working with Jennifer and IGI to go through with this.Priscilla Chan (09:45):I think the thing that's incredibly exciting, you mentioned that at CZI our mission is to cure, prevent, and manage all disease. And when we talked about this 10 years ago, it felt like this far off idea, but every day it seems closer and closer. And I think the part that's super exciting about this is the direct connection between the basic science that's happening in CRISPR and the molecular and down to the nucleotide understanding of these mutations and the ability to correct them. And I think many of us, our imaginations have included this possibility, but it's very exciting that it has happened with baby KJ and CHOP. And we need to be able to do the work to understand how we can treat more patients this way, how to understand the obstacles, unblock them, streamline the process, bring down the cost, so that we better understand this pathway for treatment, as well as to increasingly democratize access to this type of platform. And so, our hope is to be able to do that. Take the work and inspiration that IGI and the team at CHOP have done and continue to push forward and to look at more cases, look at more organ systems. We're going to be looking in addition to the liver, at the bone marrow and the immune system.Priscilla Chan (11:17):And to be able to really work through more of the steps so that we can bring this to more families and patients.Eric Topol (11:30):Yeah, well it's pretty remarkable because here you have incurable ultra-rare diseases. If you can help these babies, just think of what this could do in a much broader context. I mean there a lot of common diseases have their roots with some of these very rare ones. So how do you see going forward, Jennifer, as to where you UC Berkeley, Gladstone, UCSF. I'm envious of you all up there in Northern California I have to say, will pull this off. How will you get the first similar case to KJ Muldoon going forward?Jennifer Doudna (12:13):Right. Well, IGI is a joint institute, as you probably know, Eric. So we were founded 10 years ago as a joint institute between UC Berkeley and UCSF. And now we have a third campus partner, UC Davis and we have the Gladstone Institute. So we've got an extraordinary group of clinicians and researchers that are coming together for this project and the Center to make it a success. We are building a clinical team at UCSF. We have several extraordinary leaders including Jennifer Puck and Chris Dvorak, and they are both going to be involved in identifying patients that could be enrolled in this program based on their diagnosis. And we will have a clinical advisory group that will help with that as well. So we'll be vetting patients probably right after we announce this, we're going to be looking to start enrolling people who might need this type of help.Eric Topol (13:18):Do you think it's possible to go any faster right now than the six months that it took for KJ?Jennifer Doudna (13:26):I think it could be. And here's the reason. There's a very interesting possibility that because of the type of technology that we're talking about with CRISPR, which fundamentally, and you and I have talked about this previously on your other podcast. But we've talked about the fact that it's a programmable technology and that means that we can change one aspect of it, one piece of it, which is a piece of a molecule called RNA that's able to direct CRISPR to the right sequence where we want to do editing and not change anything else about it. The protein, the CRISPR protein stays the same, the delivery vehicle stays the same, everything else stays the same. And so, we're working right now with FDA to get a platform designation for CRISPR that might allow streamlining of the testing process in some cases. So it'll obviously come down to the details of the disease, but we're hopeful that in the end it will be possible. And Priscilla and I have talked about this too, that as AI continues to advance and we get more and more information about rare diseases, we'll be able to predict accurately the effects of editing. And so, in some cases in the future it may be possible to streamline the testing process even further safely.Eric Topol (14:51):And I also would note, as you both know, well this administration is really keen on genome editing and they've had a joint announcement regarding their support. And in my discussions with the FDA commissioner, this is something they are very excited about. So the timing of the new Center for pediatric CRISPR Cures is aligned with the current administration, which is good to see. It's not always the case. Now going back, Priscilla, to your point that not just for the liver because delivery has been an issue of course, and we're going to try to get after a lot of these really rare diseases, it's going to go beyond there. So this is also an exciting new dimension of the Center, as you said, to go after the bone marrow for hematopoietic cells, perhaps other organs as well.Priscilla Chan (15:42):I mean what the expertise and feasibility, the immune system is going to be the next target. Jennifer Puck has been a pioneer in this work. She's the one who designed the newborn screen that will be the tool that picks up these patients as they are born. And I think the thing that's tremendous is the immune system, first of all is active in many, many diseases, not just these cases of children born with partial or absence of immune systems. And the course right now that these babies are left with is complete isolation and then a very long and arduous course of a bone marrow transplant with high morbidity and mortality. And even if after the transplant you have complications like graft versus host and immunosuppression. And so, the idea of being able to very specifically and with less the conditioning and morbidity and mortality of the treatment, being able to address this is incredible. And the implications for other diseases like blood cancers or other hematopoietic diseases, that's incredible. And that actually has an incredibly broad base of patients that can benefit from the learnings from these babies with severe combined immunodeficiencies.Eric Topol (17:10):Yeah, I think that goes back to a point earlier maybe to amplify in that previous CRISPR generation, it required outside the body work and it was extremely laborious and time consuming and obviously added much more to the expense because of hospitalization time. This is different. This is basically doing this inside the affected patient's body. And that is one of the biggest reasons why this is a big step forward and why we're so fortunate that your Center is moving forward. Maybe before we wrap up, you might want to comment, Jennifer on how you were able to bring in to build this platform, the manufacturing arm of it, because that seems to be yet another dimension that's helpful.Jennifer Doudna (18:01):Indeed, yes. And we were again fortunate with timing because you mentioned briefly that the IGI had set up a program with the Danaher Corporation back in January of last year. We call it our Beacon project. And it's focused on rare disease. And it's a really interesting kind of a unique partnership because Danaher is a manufacturing conglomerate. So they have companies that make molecules, they make proteins, they make RNA molecules, they make delivery molecules. And so, they were excited to be involved with us because they want to be a provider of these types of therapies in the future. And they can see the future of CRISPR is very excit…

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Adam Kucharski: The Uncertain Science of Certainty Jun 29, 2025

Show notes

“To navigate proof, we must reach into a thicket of errors and biases. We must confront monsters and embrace uncertainty, balancing — and rebalancing —our beliefs. We must seek out every useful fragment of data, gather every relevant tool, searching wider and climbing further. Finding the good foundations among the bad. Dodging dogma and falsehoods. Questioning. Measuring. Triangulating. Convincing. Then perhaps, just perhaps, we'll reach the truth in time.”—Adam KucharskiMy conversation with Professor Kucharski on what constitutes certainty and proof in science (and other domains), with emphasis on many of the learnings from Covid. Given the politicization of science and A.I.’s deepfakes and power for blurring of truth, it’s hard to think of a topic more important right now.Audio file (Ground Truths can also be downloaded on Apple Podcasts and Spotify)Eric Topol (00:06):Hello, it's Eric Topol from Ground Truths and I am really delighted to welcome Adam Kucharski, who is the author of a new book, Proof: The Art and Science of Certainty. He’s a distinguished mathematician, by the way, the first mathematician we've had on Ground Truths and a person who I had the real privilege of getting to know a bit through the Covid pandemic. So welcome, Adam.Adam Kucharski (00:28):Thanks for having me.Eric Topol (00:30):Yeah, I mean, I think just to let everybody know, you're a Professor at London School of Hygiene and Tropical Medicine and also noteworthy you won the Adams Prize, which is one of the most impressive recognitions in the field of mathematics. This is the book, it's a winner, Proof and there's so much to talk about. So Adam, maybe what I'd start off is the quote in the book that captivates in the beginning, “life is full of situations that can reveal remarkably large gaps in our understanding of what is true and why it's true. This is a book about those gaps.” So what was the motivation when you undertook this very big endeavor?Adam Kucharski (01:17):I think a lot of it comes to the work I do at my day job where we have to deal with a lot of evidence under pressure, particularly if you work in outbreaks or emerging health concerns. And often it really pushes the limits, our methodology and how we converge on what's true subject to potential revision in the future. I think particularly having a background in math’s, I think you kind of grow up with this idea that you can get to these concrete, almost immovable truths and then even just looking through the history, realizing that often isn't the case, that there's these kind of very human dynamics that play out around them. And it's something I think that everyone in science can reflect on that sometimes what convinces us doesn't convince other people, and particularly when you have that kind of urgency of time pressure, working out how to navigate that.Eric Topol (02:05):Yeah. Well, I mean I think these times of course have really gotten us to appreciate, particularly during Covid, the importance of understanding uncertainty. And I think one of the ways that we can dispel what people assume they know is the famous Monty Hall, which you get into a bit in the book. So I think everybody here is familiar with that show, Let's Make a Deal and maybe you can just take us through what happens with one of the doors are unveiled and how that changes the mathematics.Adam Kucharski (02:50):Yeah, sure. So I think it is a problem that's been around for a while and it's based on this game show. So you've got three doors that are closed. Behind two of the doors there is a goat and behind one of the doors is a luxury car. So obviously, you want to win the car. The host asks you to pick a door, so you point to one, maybe door number two, then the host who knows what's behind the doors opens another door to reveal a goat and then ask you, do you want to change your mind? Do you want to switch doors? And a lot of the, I think intuition people have, and certainly when I first came across this problem many years ago is well, you've got two doors left, right? You've picked one, there's another one, it's 50-50. And even some quite well-respected mathematicians.Adam Kucharski (03:27):People like Paul Erdős who was really published more papers than almost anyone else, that was their initial gut reaction. But if you work through all of the combinations, if you pick this door and then the host does this, and you switch or not switch and work through all of those options. You actually double your chances if you switch versus sticking with the door. So something that's counterintuitive, but I think one of the things that really struck me and even over the years trying to explain it is convincing myself of the answer, which was when I first came across it as a teenager, I did quite quickly is very different to convincing someone else. And even actually Paul Erdős, one of his colleagues showed him what I call proof by exhaustion. So go through every combination and that didn't really convince him. So then he started to simulate and said, well, let's do a computer simulation of the game a hundred thousand times. And again, switching was this optimal strategy, but Erdős wasn't really convinced because I accept that this is the case, but I'm not really satisfied with it. And I think that encapsulates for a lot of people, their experience of proof and evidence. It's a fact and you have to take it as given, but there's actually quite a big bridge often to really understanding why it's true and feeling convinced by it.Eric Topol (04:41):Yeah, I think it's a fabulous example because I think everyone would naturally assume it's 50-50 and it isn't. And I think that gets us to the topic at hand. What I love, there's many things I love about this book. One is that you don't just get into science and medicine, but you cut across all the domains, law, mathematics, AI. So it's a very comprehensive sweep of everything about proof and truth, and it couldn't come at a better time as we'll get into. Maybe just starting off with math, the term I love mathematical monsters. Can you tell us a little bit more about that?Adam Kucharski (05:25):Yeah, this was a fascinating situation that emerged in the late 19th century where a lot of math’s, certainly in Europe had been derived from geometry because a lot of the ancient Greek influence on how we shaped things and then Newton and his work on rates of change and calculus, it was really the natural world that provided a lot of inspiration, these kind of tangible objects, tangible movements. And as mathematicians started to build out the theory around rates of change and how we tackle these kinds of situations, they sometimes took that intuition a bit too seriously. And there was some theorems that they said were intuitively obvious, some of these French mathematicians. And so, one for example is this idea of you how things change smoothly over time and how you do those calculations. But what happened was some mathematicians came along and showed that when you have things that can be infinitely small, that intuition didn't necessarily hold in the same way.Adam Kucharski (06:26):And they came up with these examples that broke a lot of these theorems and a lot of the establishments at the time called these things monsters. They called them these aberrations against common sense and this idea that if Newton had known about them, he never would've done all of his discovery because they're just nuisances and we just need to get rid of them. And there's this real tension at the core of mathematics in the late 1800s where some people just wanted to disregard this and say, look, it works for most of the time, that's good enough. And then others really weren't happy with this quite vague logic. They wanted to put it on much sturdier ground. And what was remarkable actually is if you trace this then into the 20th century, a lot of these monsters and these particularly in some cases functions which could almost move constantly, this constant motion rather than our intuitive concept of movement as something that's smooth, if you drop an apple, it accelerates at a very smooth rate, would become foundational in our understanding of things like probability, Einstein's work on atomic theory. A lot of these concepts where geometry breaks down would be really important in relativity. So actually, these things that we thought were monsters actually were all around us all the time, and science couldn't advance without them. So I think it's just this remarkable example of this tension within a field that supposedly concrete and the things that were going to be shunned actually turn out to be quite important.Eric Topol (07:53):It's great how you convey how nature isn't so neat and tidy and things like Brownian motion, understanding that, I mean, just so many things that I think fit into that general category. In the legal, we won't get into too much because that's not so much the audience of Ground Truths, but the classic things about innocent and until proven guilty and proof beyond reasonable doubt, I mean these are obviously really important parts of that overall sense of proof and truth. We're going to get into one thing I'm fascinated about related to that subsequently and then in science. So before we get into the different types of proof, obviously the pandemic is still fresh in our minds and we're an endemic with Covid now, and there are so many things we got wrong along the way of uncertainty and didn't convey that science isn't always evolving search for what is the truth. There's plenty no shortage of uncertainty at any moment. So can you recap some of the, you did so much work during the pandemic and obviously some of it's in the book. What were some of the major things that you took out of proof and truth from the pandemic?Adam Kucharski (09:14):I think it was almost this story of two hearts because on the one hand, science was the thing that got us where we are today. The reason that so much normality could resume and so much risk was reduced was development of vaccines and the understanding of treatments and the understanding of variants as they came to their characteristics. So it was kind of this amazing opportunity to see this happen faster than it ever happened in history. And I think ever in science, it certainly shifted a lot of my thinking about what's possible and even how we should think about these kinds of problems. But also on the other hand, I think where people might have been more familiar with seeing science progress a bit more slowly and reach consensus around some of these health issues, having that emerge very rapidly can present challenges even we found with some of the work we did on Alpha and then the Delta variants, and it was the early quantification of these.Adam Kucharski (10:08):So really the big question is, is this thing more transmissible? Because at the time countries were thinking about control measures, thinking about relaxing things, and you've got this just enormous social economic health decision-making based around essentially is it a lot more spreadable or is it not? And you only had these fragments of evidence. So I think for me, that was really an illustration of the sharp end. And I think what we ended up doing with some of those was rather than arguing over a precise number, something like Delta, instead we kind of looked at, well, what's the range that matters? So in the sense of arguing over whether it's 40% or 50% or 30% more transmissible is perhaps less important than being, it's substantially more transmissible and it's going to start going up. Is it going to go up extremely fast or just very fast?Adam Kucharski (10:59):That's still a very useful conclusion. I think what often created some of the more challenges, I think the things that on reflection people looking back pick up on are where there was probably overstated certainty. We saw that around some of the airborne spread, for example, stated as a fact by in some cases some organizations, I think in some situations as well, governments had a constraint and presented it as scientific. So the UK, for example, would say testing isn't useful. And what was happening at the time was there wasn't enough tests. So it was more a case of they can't test at that volume. But I think blowing between what the science was saying and what the decision-making, and I think also one thing we found in the UK was we made a lot of the epidemiological evidence available. I think that was really, I think something that was important.Adam Kucharski (11:51):I found it a lot easier to communicate if talking to the media to be able to say, look, this is the paper that's out, this is what it means, this is the evidence. I always found it quite uncomfortable having to communicate things where you knew there were reports behind the scenes, but you couldn't actually articulate. But I think what that did is it created this impression that particularly epidemiology was driving the decision-making a lot more than it perhaps was in reality because so much of that was being made public and a lot more of the evidence around education or economics was being done behind the scenes. I think that created this kind of asymmetry in public perception about how that was feeding in. And so, I think there was always that, and it happens, it is really hard as well as a scientist when you've got journalists asking you how to run the country to work out those steps of am I describing the evidence behind what we're seeing? Am I describing the evidence about different interventions or am I proposing to some extent my value system on what we do? And I think all of that in very intense times can be very easy to get blurred together in public communication. I think we saw a few examples of that where things were being the follow the science on policy type angle where actually once you get into what you're prioritizing within a society, quite rightly, you've got other things beyond just the epidemiology driving that.Eric Topol (13:09):Yeah, I mean that term that you just use follow the science is such an important term because it tells us about the dynamic aspect. It isn't just a snapshot, it's constantly being revised. But during the pandemic we had things like the six-foot rule that was never supported by data, but yet still today, if I walk around my hospital and there's still the footprints of the six-foot rule and not paying attention to the fact that this was airborne and took years before some of these things were accepted. The flatten the curve stuff with lockdowns, which I never was supportive of that, but perhaps at the worst point, the idea that hospitals would get overrun was an issue, but it got carried away with school shutdowns for prolonged periods and in some parts of the world, especially very stringent lockdowns. But anyway, we learned a lot.Eric Topol (14:10):But perhaps one of the greatest lessons is that people's expectations about science is that it's absolute and somehow you have this truth that's not there. I mean, it's getting revised. It's kind of on the job training, it's on this case on the pandemic revision. But very interesting. And that gets us to, I think the next topic, which I think is a fundamental part of the book distributed throughout the book, which is the different types of proof in biomedicine and of course across all these domains. And so, you take us through things like randomized trials, p-values, 95 percent confidence intervals, counterfactuals, causation…

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Eric Topol With Devi Sridhar on her new book- How Not to Die (Too Soon) Jun 17, 2025

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Thanks to so many of you who joined our live conversation with Devi Sridhar!

Professor Devi Sridhar is the Chair of Global Public Health at the University of Edinburgh. Over the past 2 decades she has become one of the world’s leading authorities and advisors for promoting global health. Her new book —How No to Die Too Soon—provides a unique outlook for extending healthspan with a global perspective admixed with many personal stories.

We talked about lifestyle factors with lessons from Japan (on diet) and the Netherlands (on physical activity), ultra-processed foods, air pollution and water quality, the prevention model in Finland, guns, inequities, the US situation for biomedical research and public health agency defunding, and much more.

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Matthew Walker: Promoting Our Sleep Health Jun 14, 2025

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My conversation with Matthew Walker, PhD on faculty at UC Berkeley where he is a professor of neuroscience and psychology, the founder and director of the Center for Human Sleep Science, and has a long history of seminal contributions on sleep science and health. Audio File (also downloadable at Apple Podcast and Spotify)“Sleep is a non-negotiablebiological state required for the maintenance of human life . . . our needsfor sleep parallel those for air, food, and water.”—Grandner and FernandezEric Topol (00:07):Hello, it's Eric Topol with Ground Truths, and I am really delighted to welcome Matt Walker, who I believe has had more impact on sleep health than anyone I know. It's reflected by the fact that he is a Professor at UC Berkeley, heads up the center that he originated for Human Sleep Science. He wrote a remarkable book back in 2017, Why We Sleep, and also we'll link to that as well as the TED Talk of 2019. Sleep is Your Superpower with 24 million views. That's a lot of views here.Matt Walker:Striking, isn't it?Eric Topol:Wow. I think does reflect the kind of impact, you were onto the sleep story sooner, earlier than anyone I know. And what I wanted to do today was get to the updates because you taught us a lot back then and a lot of things have been happening in these years since. You're on it, of course, I think you have a podcast Sleep Diplomat, and you're obviously continued working on the science of sleep. But maybe the first thing I'd ask you about is in the last few years, what do you think has been, are there been any real changes or breakthroughs in the field?What Is New?Matt Walker (01:27):Yeah, I think there has been changes, and maybe we'll speak about one of them, which is the emergence of this brain cleansing system called the glymphatic system, but spreading that aside for potential future discussion. I would say that there are maybe at least two fascinating areas. The first is the broader impact of sleep on much more complex human social interactions. We think of sleep at maybe the level of the cell or systems or whole scale biology or even the entire organism. We forget that a lack of sleep, or at least the evidence suggests a lack of sleep will dislocate each other, one from the other. And there's been some great work by Dr. Eti Ben Simon for example, demonstrating that when you are sleep deprived, you become more asocial. So you basically become socially repellent. You want to withdraw, you become lonely. And what's also fascinating is that other people, even they don't know that you sleep deprived, they rate you as being less socially sort of attractive to engage with.Matt Walker (02:35):And after interacting with you, the sleep deprived individual, even though they don't know you're sleep deprived, they themselves walk away feeling more lonely themselves. So there is a social loneliness contagion that happens that a sleep deprived lonely individual can have almost a viral knock on effect that causes loneliness in another well-rested individual. And then that work spanned out and it started to demonstrate that another impact of a lack of sleep socially is that we stop wanting to help other people. And you think, well, helping behavior that's not really very impactful. Try to tell me of any major civilization that has not risen up through human cooperation and helping. There just isn't one. Human cooperative behavior is one of our innate traits as homo sapiens. And what they discovered is that when you are insufficiently slept, firstly, you don't wish to help other people. And you can see that at the individual level.Matt Walker (03:41):You can see it in groups. And then there was a great study again by Dr. Eti Ben Simon that demonstrated this at a national level because what she did was she looked at this wonderful manipulation of one hour of sleep that happens twice a year to 1.6 billion people. It's called daylight savings time at spring. Yeah, when you lose one hour of sleep opportunity. She looked at donations across the nation and sure enough, there was this big dent in donation giving in the sleepy Monday and Tuesday after the clock change. Because of that sleep, we become less willing to empathetically and selflessly help other individuals. And so, to me I think it's just a fascinating area. And then the other area I think is great, and I'm sorry I'm racing forward because I get so excited. But this work now looking at what we call genetic short sleepers and sort of idiots like me have been out there touting the importance of somewhere between seven to nine hours of sleep.Matt Walker (04:48):And once you get less than that, and we'll perhaps speak about that, you can see biological changes. But there is a subset of individuals who, and we've identified at least two different genes. One of them is what we call the DEC2 gene. And it seems to allow individuals to sleep about five hours, maybe even a little bit less and show no impairment whatsoever. Now we haven't tracked these individuals across the lifespan to truly understand does it lead to a higher mortality risk. But so far, they don't implode like you perhaps or I would do when you are limited to this anemic diet of five hours of sleep. They hang in there just fine. And I think philosophically what that tells me, and by the way, for people who are listening thinking, gosh, I think I'm probably one of those people. Statistically, I think you are more likely to be struck by lightning in your lifetime than you are to have the DEC2 gene. Think about what tells us, Eric. It tells us that there is a moment in biology in the evolution of this thing called the sleep physiological need that has changed such that mother nature has found a genetic way to ZIP file sleep.Matt Walker (06:14):You can essentially compress sleep from seven to nine hour need, down to five to six hour need. To me, that is absolutely fascinating. So now the race is on, what are the mechanisms that control this? How do we understand them? I'm sure much to my chagrin, society would like to then say, okay, is there a pill that I can take to basically ZIP file my own sleep and then it becomes an arms race in my mind, which is then all of a sudden six hours becomes the new eight hours and then everyone is saying, well, six hours is my need. Well I'll go to four hours and then it's this arms race of de-escalation of sleep. Anyway, I'm going on and on, does that help give you a sense of two of the what I feel the more fascinating areas?Eric Topol (07:01):Absolutely. When I saw the other recent report on the short sleep gene variant and thought about what the potential of that would be with respect to potential drug development or could you imagine genome editing early in life that you don't need any sleep? I mean crazy stuff.Matt Walker (07:19):It was amazing.Glymphatics and Deep Sleepfor more, see previous Ground Truths on this topic Eric Topol (07:22):No, the mechanism of course we have to work out and also what you mentioned regarding the social and the behavior engagement, all that sort of thing, it was just fascinating stuff. Now we touched on one thing early on to come back to the glymphatics these channels to get rid of the waste metabolites from the brain each night that might be considered toxic metabolites. We've learned a lot about those and of course there's some controversy about it. What are your thoughts?Matt Walker (07:55):Yeah, I think there's really quite comprehensive evidence suggesting that the brain has this cleansing system like the body has one the lymphatic system, the brain has one the glymphatic system named after these glial cells that make it up. And I think there's been evidence from multiple groups across multiple different species types, from mouse models all the way up to human models suggesting that there is a state dependent control of the brain cleansing system, which is a fancy way of saying if you are awake in light NREM, deep NREM or perhaps you're just quiet and you are resting in your wakefulness, the glymphatic system is not switched on at the same rate across all of those different brain states. And I think the overwhelming evidence so far using different techniques in different species from different groups is that sleep is a preferential time. It's not an exclusive time, it's a preferential time when that brain cleansing system kicks into gear because as some people have, I think argued, and you could say it's hyperbolic, but wakefulness is low level from a biochemicals perspective, it's low level brain damage and sleep is therefore your sanitary salvation that combat that biochemical cascade.Matt Walker (09:15):So in other words, a better way of putting it would be, sleep is the price that you pay for wakefulness in some ways. And I think there was a recent controversial study that came out in 2022 or 2023, and they actually suggested quite the opposite. They said using their specific imaging methods, they found that the sort of clearance, the amount of cerebral spinal fluid, which is what washes through the brain to cleanse the toxins, the rate of that flow of cerebral spinal fluid was highest during wakefulness and lowest during deep NREM sleep, the exact opposite of what others have found. Now, I think the defendants of the glymphatic sleep dependent hypothesis pushed back and said, well, if you look at the imaging methods. Firstly, they’re nonstandard. Secondly, they were measuring the cerebral spinal flow in an artificial way because they were actually perfusing solutions through the brain rather than naturally letting it flow and therefore the artificial forcing of fluid changed the prototypical result you would get.Matt Walker (10:27):And they also argued that the essentially kind of the sampling rate, so how quickly are you taking snapshots of the cerebral spinal fluid flow. Those were different and they were probably missing some of the sleep dependent slow oscillations that seemed to sort of drive that pulsatile flow. Honestly, I think that paper was still very well done, and I still think there is right now, I would still cleave to the majority of overwhelming evidence considering it's not just from one group in one species, but across multiple species, multiple groups. And I think it's nevertheless a weight of burden that has pushed back. And my sense right now, I used to think and cleaves to the notion that it was a sleep expressly selective process. Now I don't think that that's the case anymore. I think that the glymphatic system is a dynamic system, but it's always looking for the opportunity to go into cleansing mode. And you can kind of go into almost like a low battery mode when you are awake, but in quiet rest. And I think that can drive some already early clearance from the brain and then when you go into sleep, it's like powering your phone off entirely. It truly gets the chance to cleanse and reboot the biochemical system. But I think it's really interesting. I think there's a lot of work still yet to be done. It's not quite as case closed as we used to think.Eric Topol (12:03):Yeah, I mean first of all, it's great that you straighten out the controversy because that's exactly what I was referring to. And secondly, as you also pointed out, the weight of the evidence is that it's a sleep dependent phenomena, particularly during flow wave deep sleep is at least what I've seen.Matt Walker (12:21):Yes.Eric Topol (12:22):What's also interesting, your point about it being dynamic, which fascinating, there was a paper in my field of cardiology, people with atrial fibrillation had less active glymphatic, less clearance which was really interesting. And then the other finding that's also noteworthy was that Ambien made things worse. What do you think about that?We Are An Embodied OrganismMatt Walker (12:45):I think it's really interesting, and just to come back to your point about the AFib paper, what we know is that this cleansing system in the brain does seem to track the big slow brainwaves of deep slow wave sleep, but it's not only tracking the big slow brainwaves. If anything, there's something to do with the cardiorespiratory cycle, the respiration rate and the cardiac signal that may actually sink with the brainwaves. And it's essentially a cardiorespiratory neurophysiological coupling, which is a lot of ways, which is to say heart, lungs and brain coupled together. And it's the coupling of the cardiorespiratory slow oscillations that drive these pulsatile fluid mechanical, it's literally a hydro mechanical, hydro meaning cerebral spinal fluid push and pull in and out of the system drawing those metabolites out. So ago, if you have a disrupted either cardiac or respiratory or neurophysiological signal, no wonder the glymphatic system isn't going to work as efficiently.Matt Walker (14:00):I think that's a beautiful demonstration of the hemineglect that people like me who study sleep largely from the neck upwards would miss. But if you think about sleep is not just for the brain, it's for the body and it's not just for the body, it's for the brain. And we're an embodied organism. We study the organism in silos, neurology, psychiatry, cardiology, respiratory, but they all interact. And so, I think what's lovely about your example is the reminder that if you don't study the body in this study of the glymphatic system, you could miss out a profound explanation that possibly accounts for the head scratching, I don't know why we're getting this result. So that's a long way to come back to it. But the same group that was the pioneer in the discovery of the glymphatic system led by Maiken Nedergaard at the University of Rochester.In SUPER AGERS, p. 57. SRI-sleep regulatory indexSleep MedicationsMatt Walker (15:01):She has gone on to then look to say, well, if this is a sleep dependent process of brain cleansing during deep sleep, what about sleeping pills because so many people are either taking or are addicted to sleeping pills. And we've gone through, we’re in the era of web 3.0 with sleeping pills, we started off web 1.0 which were the benzos, the kind of temazepam, diazepam, lorazepam. Then we went to web 2.0, which was sort of the Ambien (zolpidem), Lunesta, Sonata. And what was common about those two classes of drugs is that they both went after something called the GABA receptor in the brain, which is this major inhibitory receptor in the brain. And essentially, they were called sedative hypnotics because they sedated your cortex. And when you take an Ambien and not going to argue you're awake. You're clearly not awake, but to argue you're a naturalistic sleep, if you look at this, physiology is an equal fallacy.Matt Walker (16:01):They made this interesting experimental hypothesis that when you take Ambien, you sleep longer and based on how you score deep sleep, it would seem as though Ambien increases the amount of minutes that you spend in deep sleep. But if you look at the electrical signature during that “increased deep sleep” it's not the same. Ambien takes a big bite. There's a big dent out of the very slowest of the slow brainwaves, and it's the slowest of the slow brainwaves that drive the glymphatic system. So what they found was that when you take Ambien or you give mice Ambien. Yes, they sleep longer, they seem to have more deep sleep, but the brain cleansing mechanism seem to be reduced by anywhere between 30-40%, which is counterintuitive. If you are sleeping more and you're getting more deep sleep and the glymphatic system is active during deep sleep, you should get greater clea…

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Katie Couric and Eric Topol: On the State of US Life Science and Extending Healthspan Jun 12, 2025

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Thank you Richard DeWald, Michael Mann, Dr Avneesh Khare, Maud Pasturaud, Lower Dementia Risk, and many others for tuning into my live video with Katie Couric! Join me for my next live video in the app.

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Sir John Bell: Transforming Life Science and Medicine's Future May 26, 2025

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Audio FileGround Truths can also be found on Apple Podcasts, Spotify and YouTube.The UK is the world leader in human genomics, and laid the foundation for advancing medicine with the UK Biobank, Genomes England and now Our Future Health (w/ 5 million participants). Sir John Bell is a major force in driving and advising these and many other initiatives. After 22 years as the Regius Professor of Medicine at the University of Oxford he left in 2024 to be President of the Ellison Institute of Technology. Professor Bell has been duly recognized in the UK: knighted in 2015 and appointed Companion of Honor in 2023. In our conversation, you will get a sense for how EIT will be transformational for using A.I. and life science for promoting human health.Transcript with audio links Eric Topol (00:06):Hello, this is Eric Topol from Ground Truths. And I'm really delighted to welcome today, Sir John Bell who had an extraordinary career as a geneticist, immunologist, we'll talk about several initiatives he's been involved with during his long tenure at University of Oxford, recently became head of the Ellison Institute of Technology (EIT) in the UK. So welcome, John.Sir John Bell (00:30):Thanks, Eric. Thanks very much for having me.Eric Topol (00:34):Well, I think it's just extraordinary the contributions that you have made and continue to make to advance medicine, and I thought what we could do is get into that. I mean, what's interesting, you have had some notable migrations over your career, I think starting in Canada, at Stanford, then over as Rhodes Scholar in Oxford. And then you of course had a couple of decades in a very prestigious position, which as I understand was started in 1546 by King Henry VII, and served as the Regius Professor of Medicine at the University of Oxford. Do I have that right?Sir John Bell (01:11):It was actually Henry VIII, but you were close.Eric Topol (01:14):Henry VIII, that's great. Yeah. Okay, good. Well, that's a pretty notable professorship. And then of course in recent times you left to head up this pretty formidable new institute, which is something that's a big trend going on around the world, particularly in the US and we'll talk about. So maybe we can start with the new thing. Tell us more about the Ellison Institute of Technology (EIT), if you will.Sir John Bell (01:47):Yeah. So as you know, Larry Ellison has been one of the great tech entrepreneurs focused really on developing terrific databases over his career and through Oracle, which is the company that he founded. And Larry is really keen to try and give back something substantial to the world, which is based on science and technology. So he and I did quite a bit together over the Covid pandemic. He and I talked a lot about what we're doing and so on. He came to visit afterwards and he had, I think he decided that the right way to make his contributions would be to set up an institute that would be using the state-of-the-art science and technology with a lot of AI and machine learning, but also some of the other modern tools to address the major problems in healthcare, in food security, in green energy and climate change and in global governance.Sir John Bell (02:49):So anyway, he launched this about 18 months ago. He approached me to ask whether I would run it. He wanted to set it up outside Oxford, and he wanted to do something which is a bit different than others. And that is his view was that we needed to try and create solutions to these problems which are commercially viable and not all the solutions are going to be commercially viable, but where you can create those, you make them sustainable. So the idea is to make sure that we create solutions that people want to buy, and then if they buy them, you can create a sustainable solution to those issues. So we are actually a company, but we are addressing many of the same problems that the big foundations are addressing. And the big issues that you and I talk about in health, for example, are all on our list. So we're kind of optimistic as to where this will go and Larry's supporting the project and we're going to build out an institute here which will have about 5,000 people in it, and we'll be, I think a pretty exciting new addition to the science and technology ecosystem globally.Eric Topol (04:02):Well, I know the reverberations and the excitement is palpable and some of the colleagues I've spoken to, not just in England, but of course all over the world. So congratulations on that. It was a big move for you to leave the hardcore academics. And the other thing I wanted to ask you, John, is you had distinguished your career in immunology, in genetics, type 1 diabetes and other conditions, autoimmune conditions, and now you've really diversified, as you described with these different areas of emphasis at the new institute. Is that more fun to do it or do you have deputies that you can assign to things like climate change in other areas?Sir John Bell (04:50):Trust me, Eric, I'm not making any definitive decisions about areas I know nothing about, but part of this is about how do you set up leadership, run a team, get the right people in. And I have to say one of the really interesting things about the institute is we've been able to recruit some outstanding people across all those domains. And as you know, success is almost all dependent on people. So we're really pretty optimistic we're going to have a significant impact. And of course, we also want to take risks because not a lot of point in us doing stuff that everybody else is doing. So we're going to be doing some things that are pretty way out there and some of them will fail, so we are just going to get used to trying to make sure we get a few of them across the finish line. But the other thing is that, and you've experienced this too, you never get too old to learn. I mean, I'm sucking up stuff that I never thought I would ever learn about, which is fun actually, and really marvel.Eric Topol (05:55):It's fantastic. I mean, you've really broadened and it's great that you have the runway to get these people on board and I think you're having a big building that's under construction?Sir John Bell (06:07):Yeah, we've got the original building that Larry committed to is about 330,000 square feet of space. I mean, this is completely amazing, but we are of course to accommodate up to 5,000 people, we're going to need more than that. So we are looking at a much wider campus here that'll involve more than just that building. I think we'll end up with several million square feet of space by the time we're finished. So mean, it's a really big project, but we've already made progress in some domains to try and get projects and the beginnings of companies on the road to try and solve some of the big problems. So we're quite excited about it.Eric Topol (06:49):Now you, I assume it's pretty close to Oxford, and will you have some kind of inter interactions that are substantial?Sir John Bell (06:58):Yeah, so the university's been terrific about this actually, because of course most universities would say, well, why don't you do it inside the university and just give us the money and it'll all be fine. So of course Larry. Larry wasn't born yesterday, so I said, well, thank you very much, but I think we'll probably do this nearby. But the university also realized this is a really exciting opportunity for them and we've got a really good relationship with them. We've signed an agreement with them as to who will work where. We've agreed not to steal a lot of their staff. We're going to be bringing new people into the ecosystem. Some of the university people will spend some time with us and sometime in the university, so that will help. But we're also bringing quite a few new people into the setting. So the university has been really positive. And I think one of the things that's attractive to the university, and you'll be familiar with this problem in the UK, is that we're quite good. The discovery science here is pretty good.Sir John Bell (08:06):And we do startups now at scale. So Oxford does lots of little startup companies in the biotech space and all the rest of it, but we never scale any of these companies because there isn't the depth of capital for scaling capital to get these things scaled. And so, in a way what we're trying to do here at Ellison actually avoids that problem because Larry knows how to scale companies, and we've got the financial support now. If we have things that are really successful, we can build the full stack solution to some of these problems. So I think the university is really intrigued as to how we might do that. We're going to have to bring some people in that know how to do that and build billion dollar companies, but it's sufficiently attractive. We've already started to recruit some really outstanding people. So as a way to change the UK system broadly, it's actually quite a good disruptive influence on the way the thing works to try and fix some of the fundamental problems.Eric Topol (09:07):I love that model and the ability that you can go from small startups to really transformative companies have any impact. It fits in well with the overall objectives, I can see that. The thing that also is intriguing regarding this whole effort is that in parallel we've learned your influence. The UK is a genomics world leader without any question and no coincidence that that's been your area of emphasis in your career. So we've watched these three initiatives that I think you were involved in the UK Biobank, which has had more impact than any cohort ever assembled. Every day there's another paper using that data that's coming out. There's Genomes England, and then now Our Future Health, which a lot of people don't know about here, which is well into the 5 million people enrollment. Can you tell us about, this is now 15 years ago plus when these were started, and of course now with a new one that's the biggest ever. What was your thinking and involvement and how you built the UK to be a world leader in this space?Sir John Bell (10:26):So if you turn the clock back 20 years, or actually slightly more than 25 years ago, it was clear that genomics was going to have a play. And I think many of us believed that there was going to be a genetic element to most of the major common disease turn out to be true. But at the time, there were a few skeptics, but it seemed to us that there was going to be a genetic story that underpinned an awful lot of human disease and medicine. And we were fortunate because in Oxford as you know, one of my predecessors in the Regius job was Richard Doll, and he built up this fantastic epidemiology capability in Oxford around Richard Peto, Rory Collins, and those folks, and they really knew how to do large scale epidemiology. And one of the things that they'd observed, which is it turns out to be true with genetics as well, is a lot of the effects are relatively small, but they're still quite significant. So you do need large scale cohorts to understand what you're doing. And it was really Richard that pioneered the whole thinking behind that. So when we had another element in the formula, which was the ability to detect genetic variation and put that into the formula, it seemed to me that we could move into an era where you could set up, again, large cohorts, but build into the ability to have DNA, interrogate the DNA, and also ultimately interrogate things like proteomics and metabolomics, which were just in their infancy at that stage.Sir John Bell (12:04):Very early on I got together because I was at that stage at the Nuffield Chair of Medicine, and I got together, Rory and Richard and a couple of others, and we talked a little bit about what it would look like, and we agreed that a half a million people late to middle age, 45 and above would probably over time when you did the power calculations, give you a pretty good insight in most of the major diseases. And then it was really a question of collecting them and storing the samples. So in order to get it funded at the time I was on the council of the MRC and George Radda, who you may remember, was quite a distinguished NMR physiologist here. He was the chief executive of the MRC. So I approached him and I said, look, George, this would be a great thing for us to do in the UK because we have all the clinical records of these people going back for a decade, and will continue to do that.Sir John Bell (13:01):Of course, we immediately sent it out to a peer review committee in the MRC who completely trashed the idea and said, you got to be joking. So I thought, okay, that’s how that lasted. And I did say to George, I said, that must mean this is a really good idea because if it had gone straight through peer review, you would've known you were toast. So anyway, I think we had one more swing at peer review and decided in the end that wasn't going to work. In the end, George to his credit, took it to MRC council and we pitched it and everybody thought, what a great idea, let's just get on and do it. And then the Wellcome came in. Mark Walport was at the Wellcome at the time, great guy, and did a really good job at bringing the Wellcome on board.Sir John Bell (13:45):And people forget the quantum of money we had to do this at the time was about 60 million pounds. I mean, it wasn’t astonishly small. And then of course we had a couple of wise people who came in to give us advice, and the first thing they said, well, if you ever thought you were really going to be able to do genetics on 500,000 people, forget it. That'll never work. So I thought, okay, I'll just mark that one out. And then they said, and by the way, you shouldn't assume you can get any data from the health service because you'll never be able to collect clinical data on any of these people. So I said, yeah, yeah, okay, I get it. Just give us the money and let us get on. So anyway, it's quite an interesting story. It does show how conservative the community actually is for new ideas.Sir John Bell (14:39):Then I chaired the first science committee, and we decided about a year into it that we really needed the chief executive. So we got Rory Collins to lead it and done it. I sat on the board then for the next 10 years, but well look, it was a great success. And as you say, it is kind of the paradigm for now, large genetic epidemiology cohorts. So then, as you know, I advise government for many years, and David Cameron had just been elected as Prime Minister. This was in about 2010. And at the time I'd been tracking because we had quite a strong genomics program in the Wellcome Trust center, which I'd set up in the university, and we were really interested in the genetics of common disease. It became clear that the price of sequencing and Illumina was now the clear leader in the sequencing space.Sir John Bell (15:39):But it was also clear that Illumina was making significant advances in the price of sequencing because as you remember, the days when it cost $5,000 to do a genome. Anyway, it became clear that they actually had technology that gets you down to a much more sensible price, something like $500 a genome. So I approached David and I said, we are now pretty sure that for many of the rare diseases that you see in clinical practice, there is a genetic answer that can be detected if you sequenced a whole genome. So why don't we set something up in the NHS to provide what was essentially the beginnings of a clinical service to help the parents of kids with various disab…

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Tyler Cowen: The Prototypic Polymath May 10, 2025

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Audio file, also on Apple and SpotifyTyler Cowen, Ph.D, is the Holbert L. Harris Professor of Economics at George Mason University. He is the author of 17 books, most recently Talent.: How to Identify Energizers, Creatives, and Winners Around the World. Tyler has been recognized as one of the most influential economists of the past decade. He initiated and directs the philanthropic project Emergent Ventures, writes a blog Marginal Revolution, and a podcast Conversations With Tyler, and also writes columns for The Free Press." He is writing a new book (and perhaps his last) on Mentors. “Maybe AGI [Artificial General Intelligence] is like porn — I know it when I see it. And I’ve seen it.”—Tyler CowenOur conversation on acquiring information, A.I., A.G.I., the NIH, the assault on science, the role of doctors in the A.I. era,, the meaning of life, books of the future, and much more.Transcript with linksEric Topol (00:06):Well, hello. This is Eric Topol with Ground Truths, and I am really thrilled today to have the chance to have a conversation with Tyler Cowen, who is, when you look up polymath in the dictionary, you might see a picture of him. He is into everything. And recently in the Economist magazine 1843, John Phipps wrote a great piece profile, the man who wants to know everything. And actually, I think there's a lot to that.Tyler Cowen (00:36):That's why we need longevity work, right?Eric Topol (00:39):Right. So he's written a number of books. How many books now, Tyler?Tyler Cowen:17, I'm not sure.Eric Topol:Only 17? And he also has a blog that's been going on for over 20 years, Marginal Revolution that he does with Alex Tabarrok.Tyler Cowen (00:57):Correct.Eric Topol (00:57):And yeah, and then Conversations with Tyler, a podcast, which I think an awful lot of people are tuned into that. So with that, I'm just thrilled to get a chance to talk with you because I used to think I read a lot, but then I learned about you.“Cowen calls himself “hyperlexic”. On a good day, he claims to read four or fivebooks. Secretly, I timed him at 30 seconds per page reading a dense tract byMartin Luther. “—John Phipps, The Economist’s 1843I've been reading more from the AIs lately and less from books. So I'll get one good book and ask the AI a lot of questions.Eric Topol (01:24):Yeah. Well, do you use NotebookLM for that?Tyler Cowen (01:28):No, just o3 from OpenAI at the moment, but a lot of the models are very good. Claude, there's others.Eric Topol (01:35):Yeah, yeah. No, I see how that's a whole different way to interrogate a book and it's great. And in fact, that gets me to a topic I was going to get to later, but I'll do it now. You're soon or you have already started writing for the Free Press with Barri Weiss.Tyler Cowen (01:54):That’s right, yes. I have a piece coming out later today. It's been about two weeks. It's been great so far.“Tyler Cowen has a mind unlike any I've ever encountered. In a single conversation, it’s not at all unusual for him to toggle between DeepSeek, GLP-1s, Haitian art, sacred Tibetan music, his favorite Thai spot in L.A., and LeBron James”—Bari WeissYeah, so that's interesting. I hadn't heard of it until I saw the announcement from Barri and I thought what was great about it is she introduced it. She said, “Tyler Cowen has a mind unlike any I've ever encountered. In a single conversation, it’s not at all unusual for him to toggle between DeepSeek, GLP-1s, Haitian art, sacred Tibetan music, his favorite Thai spot in L.A., and LeBron James. Now who could do that, right. So I thought, well, you know what? I need independent confirmation of that, that is as being a polymath. And then I saw Patrick Collison, who I know at Stripe and Arc Institute, “you can have a specific and detailed discussion with him about 17th-century Irish economic thinkers, or trends in African music or the history of nominal GDP targeting. I don't know anyone who can engage in so many domains at the depth he does.” So you're an information acquirer and one of the books you wrote, I love the title Infovore.Tyler Cowen (03:09):The Age of the Infovore, that’s right.Eric Topol (03:11):I mean, have people been using that term because you are emblematic of it?“You can have a specific and detailed discussion with him about 17th-century Irish economic thinkers, or trends in African music or the history of nominal GDP targeting. I don't know anyone who can engage in so many domains at the depth he does.”—Patrick CollisonIt was used on the internet at some obscure site, and I saw it and I fell in love with that word, and I thought I should try to popularize it, but it doesn't come from me, but I think I am the popularizer of it.Yeah, well, if anybody was ingesting more information and being able to work with it. That's what I didn't realize about you, Tyler, is restaurants and basketball and all these other fine arts, very impressive. Now, one of the topics I wanted to get into you is I guess related to a topic you've written about fair amount, which is the great stagnation, and right now we're seeing issues like an attack on science. And in the past, you've written about how you want to raise the social status of scientists. So how do you see this current, I would even characterize as a frontal assault on science?Tyler Cowen (04:16):Well, I'm very worried about current Trump administration policies. They change so frequently and so unpredictably, it's a little hard to even describe what they always are. So in that sense, it's a little hard to criticize them, but I think they're scaring away talent. They might scare away funding and especially the biomedical sciences, the fixed costs behind a lot of lab work, clinical trials, they're so high that if you scare money away, it does not come back very readily or very quickly. So I think the problem is biggest perhaps for a lot of the biomedical sciences. I do think a lot of reform there has been needed, and I hope somehow the Trump policies evolve to that sort of reform. So I think the NIH has become too high bound and far too conservative, and they take too long to give grants, and I don't like how the overhead system has been done. So there's plenty of room for improvement, but I don't see so far at least that the efforts have been constructive. They've been mostly destructive.Eric Topol (05:18):Yeah, I totally agree. Rather than creative destruction it’s just destruction and it's unfortunate because it seems to be haphazard and reckless to me at least. We of course, like so many institutions rely on NIH funding for the work, but I agree that reform is fine as long as it's done in a very thought out, careful way, so we can eke out the most productivity for the best investment. Now along with that, you started Emergent Ventures where you're funding young talent.Tyler Cowen (05:57):That's right. That's a philanthropic fund. And we now have slightly over 1000 winners. They're not all young, I'd say they're mostly young and a great number of them want to go into the biomedical sciences or have done so. And this is part of what made me realize what an incredible influx of talent we're seeing into those areas. I'm not sure this is widely appreciated by the world. I'm sure you see it. I also see how much of that talent actually is coming from Canada, from Ontario in particular, and I've just become far more optimistic about computational biology and progress in biology and medical cures, fixes, whatever you want to call it, extending lives. 10 years ago, I was like, yeah, who knows? A lot of things looked pretty stuck. Then we had a number of years where life expectancy was falling, and now I think we're on the verge of a true golden age.Eric Topol (06:52):I couldn't agree with you more on that. And I know some of the people that you funded like Anne Wylie who developed a saliva test for Covid out of Yale. But as you say, there's so many great young and maybe not so young scientists all over, Canada being one great reservoir. And now of course I'm worried that we're seeing emigration rather than more immigration of this talent. Any thoughts about that?Tyler Cowen (07:21):Well, the good news is this, I'm in contact with young people almost every day, often from other countries. They still want to come to the United States. I would say I sign an O-1 letter for someone about once a week, and at least not yet has the magic been dissipated. So I'm less pessimistic than some people are, but I absolutely do see the dangers. We’re just the biggest market, the freest place we have by far the most ambitious people. I think that's actually the most significant factor. And young people sense that, and they just want to come here and there's not really another place they can go that will fit them.Eric Topol (08:04):Yeah, I mean one of the things as you've probably noted is there's these new forces that are taking on big shouldering. In fact, Patrick Collison with Arc Institute and Chan Zuckerberg for their institute and others like that, where the work you're doing with Emergent Ventures, you're supporting important projects, talents, and if this whole freefall in NIH funding and other agency funding continues, it looks like we may have to rely more on that, especially if we're going to attract some talent from outside. I don't know how else we're going to make. You're absolutely right about how we are such a great destination and great collaborations and mentors and all that history, but I'm worried that it could be in kind of a threatened mode, if you will.Tyler Cowen (08:59):I hope AI lowers costs. As you probably know at Arc, they had Greg Brockman come in for some number of months and he's one of the people, well, he helped build up Stripe, but he also was highly significant in OpenAI behind the GPT-4 model. And to have Greg Brockman at your institute doing AI for what, six months, that's a massive acceleration that actually no university had the wisdom to do, and Arc did. So I think we're seeing just more entrepreneurial thinking in the area. There's still this problem of bottlenecks. So let's say AI is great for drug discovery as it may be. Well, clinical trials then become a bigger bottleneck. The FDA becomes a bigger bottleneck. So rapid improvement in only one area while great is actually not good enough.Eric Topol (09:46):Yeah, I'm glad you brought up that effect in Arc Institute because we both know Patrick Hsu, who's a brilliant young guy who works there and has published some incredible large language models applied to life science in recent months, and it is impressive how they used AI in almost a singular way as compared to as you said, many other leading institutions. So that is I think, a really important thing to emphasize.Tyler Cowen (10:18):Arc can move very quickly. I think that's not really appreciated. So if Patrick Hsu decides Silvana Konermann, Patrick Collison, if they decide something ought to be bought or purchased or set in motion, it can happen in less than a day. And it does happen basically immediately. And it's not only that it's quicker, I think when you have quicker decisions, they're better and it's infectious to the people you're working with. And there's an understanding that the core environment is not a bureaucratic one. So it has a kind of multiplier effect through the institution.Eric Topol (10:54):Yeah, I totally agree with you. It's always been a philosophy in your mind to get stuff done, get s**t done, whatever you want to call it. They're getting it done. And that's what's so impressive. And not just that they've got some new funds available, but rather they're executing in a way that's parallel to the way the world's evolving in the AI front, which is I think faster than most people would ever have expected, anticipated. Now that gets me to a post you had on Marginal Revolution just last week, which one of the things I love about Marginal Revolution is you don't have to read a whole lot of stuff. You just give the bullets, the juice, if you will. Here you wrote o3 and AGI, is April 16th AGI day? And everybody's talking about artificial general intelligence is here. It's going to be here five years, it's going to be seven years.Eric Topol (11:50):It certainly seems to be getting closer. And in this you wrote, “I think it is AGI, seriously. Try asking it lots of questions, and then ask yourself: just how much smarter was I expecting AGI to be? As I’ve argued in the past, AGI, however you define it, is not much of a social event per se. It still will take us a long time to use it properly. Benchmarks, benchmarks, blah blah blah. Maybe AGI is like porn — I know it when I see it. And I’ve seen it.” I thought that was really well done, Tyler. Anything you want to amplify on that?Tyler Cowen (12:29):Look, if I ask at economics questions and I'm trained as an economist, it beats me. So I don't care if other people don't call it AGI, but one of the original definitions of AGI was that it would beat most experts most of the time on most matters, say 90% or above, and we're there. So people keep on shifting the goalposts. They'll say, well, sometimes it hallucinates or it's not very good at playing tic-tac toe, or there's always another complaint. Those are not irrelevant, but I'll just say, sit down, have someone write at a test of 20 questions, you're a PhD, you take the test, let o3 take the test, then have someone grade, see how you've done, then form your opinion. That's my suggestion.Eric Topol (13:16):I think it's pretty practical. I mean, enough with the Turing test, I mean, we've had that Turing test for decades, and I think the way you described it is a little more practical and meaningful these days. But its capabilities to me at least, are still beyond belief eke out of current, not just the large language models, but large reasoning models. And so, it's just gotten to a point where and it's accelerating, every week there's so many other, the competition is good for taking it to the next level.Tyler Cowen (13:50):It can do tasks and it self improves. So o3-pro will be out in a few weeks. It may be out by the time you're hearing this. I think that's obviously going to be better than just pure o3. And then GPT-5 people have said it will be this summer. So every few months there are major advances and there's no sign of those stopping.Eric Topol (14:12):Absolutely. Now, of course, you've been likened to “Treat Tyler like a really good GPT” that is because you're this information meister. What do you ask the man who you can ask anything? That's kind of what we have when we can go to any one of these sites and start our prompts, whatever. So it's kind of funny in some ways you might've annotated this with your quest for knowledge.Tyler Cowen (14:44):Well, I feel I understand the thing better than most people do for that reason, but it's not entirely encouraging to me personally, selfishly to be described that way, whether or not it's accurate. It just means I have a lot more new competition.Eric Topol (14:59):Well, I love this one. “I'm not very interested in the meaning of life, but I'm very interested in collecting information on what other people think is the meaning of life. And it's not entirely a joke” and that's also what you wrote about in the Free Press thing, that most of the things that are going to be written are going to…

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Bob Bordone and Joel Salinas: How to Deal With Conflict May 05, 2025

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In our divided world we face or avoid conflicts on a frequent basis. I turned to Bob Bordone and Joel Salinas to find out the best strategies to deal with these, including having them take on a mock conflict between each other on the merits of Covid research.Audio fileYou can also find this on Spotify and Apple podcasts with Ground Truths.The video is also posted on YouTubeTranscript with Audio LinksEric Topol (00:06):Well, hello. It's Eric Topol with Ground Truths, and we're going to get into a new book called Conflict Resilience: Negotiating Disagreement Without Giving Up or Giving In, and we're lucky to have its two authors, Bob Bordone, who is a Senior Fellow at Harvard Law School, and Joel Salinas, who is a physician, neurologist, a clinician scientist at NYU. So welcome both Bob and Joel.Bob Bordone and Joel Salinas (00:34):Thank you for having us. Yeah, looking forward to the conversation.Eric Topol (00:37):Yeah. So first, how did you guys get together? This is a pretty diverse, you got law and medicine, usually they don't talk to each other very much.Bob Bordone (00:46):Well, we were very fortunate. I mean, we basically were friends, but part of that friendship, I think emerged from work that I do around conflict issues in the Mass General system and then just the larger, bigger Mass General, Harvard community. Yeah, so this began really as a friendship where we were each swimming in very different waters, but then as we would start to talk, we realized there was a lot of connection and maybe the possibility to bring two different disciplines together in a way that might be practically useful and make an impact. And even when we started writing this, which was during Covid, what seemed to be some pretty polarizing times that were unlikely to resolve by the time the book would come out.Eric Topol (01:44):Yeah, well you sure hit it with the divisiveness and the polarized world that we live in is perhaps worse than ever, certainly in all my years, and probably long before then as well. So this topic of resilience, it's a very interesting concept because some people might think of resilience as just being tough. So go into a conflict and just go heavy tough. That obviously is not what you're writing about. And I guess maybe we can start off, what was the goal here? Obviously, there's other books that have addressed this topic, I'm sure, but yours is somewhat unique in many respects because it brings in the science of it and many strategies perhaps that have never been developed. But when you got together, what was the mission that you set out to do?Joel Salinas (02:38):Yeah, well maybe I can start out and then you can add on. So my research has been all around understanding how social relationships influenced brain health, and one of the things that I was seeing was social isolation and loneliness had been steadily increasing. Want to figure out what kind of interventions or what are the factors that are involved here? And I think one of the things that has stood out is just the difficulty with being able to navigate conflict in different contexts. And so, the idea around conflict resilience is really, even though there's been lots of books on what to say and what specific tactics to use, I think that there was this skillset around just being able to sit with the discomfort of that disagreement, which will ultimately help make it much more useful to take on those tactics. One way to think about it, if it's like all these tactics are like learning how to cook with a set of recipes in the kitchen, what we're really proposing here is that you also need to be able to stand the heat of the kitchen to even be able to cook.Eric Topol (03:47):Okay. Go ahead, Bob.Bob Bordone (03:49):Yeah, and I would say I was starting to write about my first kind of piece on this topic where I use the word conflict resilience was in 2018, and it really came from an observed dynamic that I was seeing in my teaching of Harvard Law School students. I was on the admissions committee, I'd been on the admissions committee for many years. I knew that we worked very hard and were quite successful in fact, at bringing together a very diverse student body, including politically. And people sometimes maybe think of elite law schools as being very progressive. But Harvard Law School, the biggest student organization is actually the Federalists, which is the conservative students. And despite that effort, what I noticed in the classroom was a reduction in conversation, diversity of viewpoint across the board, interesting classrooms became boring. And even though I was teaching around conflict and negotiation and difficult conversations, I would read in students' journals things like, I want to avoid conflict or I don't want to get into it.Bob Bordone (04:59):And so, it occurred to me that quite a part, as Joel said, from any skills, if we don't develop this capacity to sit with disagreement, then we will never get to problem solving. I'm in favor of problem solving. But this paper on conflict resilience, its original title was called Against Problem Solving. Mostly because I thought that if we had opened the possibility of problem solving as a precondition for entering the room, then we might never enter the room, particularly if we've told the demonized and dehumanized story about them. And so, that somehow we had to make the case that sitting with the discomfort of the disagreement, even if it didn't mean problem solving, although we hope for that, even if we didn't mean that it was worthwhile and it was important. And so, part of what was really attractive to me about joining up with Joel is that he just brought all of this brain science aspect to it that I had this kind of teaching and kind of academic in the negotiation and dispute resolution research experience, but couldn't bring to bear the kind of brain science parts of, well, what is going on in our brain when we do want to run or when we get into that really unproductive battle.Eric Topol (06:27):Yeah, I agree that the unique part here is that whole scaffolding with the neuroscience, the behavioral science, and those five Fs that you mentioned. You alluded to fight, flight, freeze, fawn, or fester. Yeah, so avoidance of conflict has kind of been the default for many people now because we have political divides, we have anti-science versus pro-science divides and on and on. There's a quote in the book that I thought we'd start off with because it really lays the groundwork from you both. “The biggest hidden barrier to being conflict resilient stems from the inability or unwillingness to face and sit with our own internal conflicts - the negotiations between our divided and sometimes contradictory “selves.” Even more surprising is that although there are dozens of self-help books on negotiation and conflict resolution, almost none of them spend any meaningful time on this critical intrapersonal barrier to handing conflict.” So maybe Joel, maybe start you off here. I guess you were bullied as a kid, and maybe that gives you a little background here. Joel, tell us about that if you would.Bob Bordone (07:46):Hey, Eric. On our bad days sometimes I probably inadvertently bully Joel still today, but he's pretty resilient now.Joel Salinas (07:53):Yeah, I'm a Teflon. So I think I am generally conflict of what an individual, and I think a lot of listeners and viewers can relate with that experience. And I think that also kind of speaks to some of the neuroscience that comes into this, which is that our brain has really evolved to be a fortune telling machine. It takes all of our past experiences, turns them into memories, and then makes projections about what's going to happen. And this projection or prediction of what's going to happen might as well be reality for our brain's sake. And so, if we had really negative experiences with conflict in the past growing up, whether through our families or the schoolyard or others, there'll be likely a very negative charge of negative emotional charge that comes with that. And what that does is that it increases the chances that you'll trigger this system for salience and arousal, which then sets off the alarms essentially in your body that then creates these fight or flight type responses where you're more likely to fall back on these really reflexive behaviors to make the bad thing less bad.Joel Salinas (09:08):And when you do that, whether it's through avoiding or to blowing through conflict like a battering ram that then trains your brain to assign some kind of a reward using the orbital frontal cortex, a system that kind of keeps tabs over how much reward you get for a behavior, it makes it much more likely that you'll do it again. And so, we from a very young age, develop a propensity to either avoid conflict or tackle it. And it varies depending on the context and how you're feeling, but it just makes it much, much harder to be able to bring on a much more thoughtful and deliberative approach to conflict.Eric Topol (09:49):Yeah, I mean, I think one of the salient points is that avoiding the conflict can make things worse. And as you described that it's not, I would've thought that there are some people who are just innately gifted to being diplomatic and artful about having to deal with the conflict issue and others, there's just no hope. But in fact, it can be acquired. And you alluded to this kind of neuroplasticity, the brain and you advocate for chair work. Can you tell us about chair work, because that's something I wouldn't have thought would help in this manner.Bob Bordone (10:30):Sure. I mean, I'll say a little bit work about that. A big part of this chair work idea, frankly, is influenced by work in internal family systems. And I was very fortunate early in my career, even though I was at teaching at law school to start partnering with some folks who did IFS work, they call it peace work often. But the chair work is really identifying some of these conflicted sides of ourself, right? The side of ourself that maybe feels like it's important and okay to raise this issue because it's something that matters to me and maybe the side of ourself that feels like it's pointless and it will hurt the relationship and maybe the side of ourself that's fearful and to name each of them. And then to actually give each in preparation a physical chair where we sit in that chair and give voice to each of those sides.Bob Bordone (11:32):And I'm imagining that at least some people listening to this will say, this sounds very hokey, and does he really mean going to the chairs? And the answer is, yes, I do mean that because there is something about the physicality of it that forces you to give voice to something that is true and real in you. And the chair work is very helpful to set up what an opening might be into a hard conversation, meaning that all of the chairs are real and authentic and okay, they're worthy of getting some voice. So as someone who teaches in a law school, it's all about advocacy. And you would find students who would be very good at advocating on behalf of a client would be incredibly poor at advocating on behalf of themself. And so, separating out the side that maybe has a little bit of feeling, it's selfish, but actually giving it a legitimate voice, help them when they get to the table to be able to say, I'm worried about this, or I realize I may be wrong about this, or it might be upsetting. And also, it's important and deserves to be heard because one of the things around avoidance is we often do avoidance in service of preserving the relationship or not disrupting. And we do maybe preserve the relationship for the time being of the person across the table, except we go home and there's still the side of us that is not feeling good about it, and the person we're not preserving the relationship with is that side, then we just get to have a sleepless night. And so, that's really the kind of idea behind the chair work.Eric Topol (13:22):That's helpful, Bob. I guess managing conflict, of course, I think we know you don't get emotional. Okay, sure. But yeah, there's three parts of that, three components, self-awareness. We've been talking about that deep listening, which of course when you're engaging in a discussion that's potentially leading to escalation of a conflict or the amplification that is really important. And then effective assertion. Now, that's where it seems to me things fall apart. If you're making effective assertion, then everything kind of blows up. So tell us about how you can be assertive and still, you're not trying to win the argument. I get that, but how can you be assertive and still come out in a positive way?Joel Salinas (14:16):Maybe I can start, Bob.Joel Salinas (14:19):I think one of the things that really is a good predictor of how effective you'll be at effective assertion is how good you were at the deep listening part. So the more genuine you are and curious you are about the perspective of the other person, really understanding what are the set of facts, experiences, beliefs that eventually lead up to that headline of what their position is or what their interests are. The better you'll be able articulate your own perspective while still engaging in the conversation. And the other thing that's really important here is that in that listening piece, it's really essential to be able to bring in tenets of really great listening that includes eliminating distractions, both external and internal. It involves having a nonjudgmental position toward the other person and being able to reflect an understanding of what the other person is saying. But all of that does not mean that you are endorsing their point of view. And I think that's really essential. It's really about getting as clear as you can about where the other person is coming from. So that way when you have an opportunity to share your perspective, you're able to really speak to the concerns of the other person and your own.Eric Topol (15:46):Yeah. Well, in reading the book, it took me, interestingly to an evening discussion I had with a very close friend.Eric Topol (15:56):And he was saying, we do need a randomized trial of the measles vaccine, MMR for autism. And I said, what? And I started thinking about, well, I'm going to hear him out because there's so much evidence now that you would think this has been totally debunked. And his view is, well, it can't hurt. And I'm thinking, well, so in that discussion, a lot of these points that you've been raising help me to come not to a point where basically I was trying to put a bow on it, as you said, or trying to externalize or abstract it. But to have a happy ending with him about this saying, okay, well it's never going to get done, but if you want to get it, I'm supportive of that. We don't do enough of this. I had to listen to what he had to say. I had to deal with my own confirmation biases and not get emotional and all that stuff, right. Now, I'd like the two of you to role play on something like that if you would. And let me just give you an example. Maybe you can run with it. Let's go to Covid, okay?Eric Topol (17:14):So one of you will take the side that we shouldn't do any more Covid research because the pandemic is over and we need to be efficient and not use these funds for other things. Covid is over, Long Covid is a hoax, and the other person will take the side that, no, this is a really big deal because Covid has not gone away and there's still a endemic of the virus, Long Covid…

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Steve Quake and Charlotte Bunne: The Holy Grail of Biology Mar 18, 2025

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“Eventually, my dream would be to simulate a virtual cell.”—Demis HassabisThe aspiration to build the virtual cell is considered to be equivalent to a moonshot for digital biology. Recently, 42 leading life scientists published a paper in Cell on why this is so vital, and how it may ultimately be accomplished. This conversation is with 2 of the authors, Charlotte Bunne, now at EPFL and Steve Quake, a Professor at Stanford University, who heads up science at the Chan-Zuckerberg Initiative The audio (above) is available on iTunes and Spotify. The full video is linked here, at the top, and also can be found on YouTube.TRANSCRIPT WITH LINKS TO AUDIO Eric Topol (00:06):Hello, it's Eric Topol with Ground Truths and we've got a really hot topic today, the virtual cell. And what I think is extraordinarily important futuristic paper that recently appeared in the journal Cell and the first author, Charlotte Bunne from EPFL, previously at Stanford’s Computer Science. And Steve Quake, a young friend of mine for many years who heads up the Chan Zuckerberg Initiative (CZI) as well as a professor at Stanford. So welcome, Charlotte and Steve.Steve Quake (00:42):Thanks, Eric. It's great to be here.Charlotte Bunne:Thanks for having me.Eric Topol (00:45):Yeah. So you wrote this article that Charlotte, the first author, and Steve, one of the senior authors, appeared in Cell in December and it just grabbed me, “How to build the virtual cell with artificial intelligence: Priorities and opportunities.” It's the holy grail of biology. We're in this era of digital biology and as you point out in the paper, it's a convergence of what's happening in AI, which is just moving at a velocity that's just so extraordinary and what's happening in biology. So maybe we can start off by, you had some 42 authors that I assume they congregated for a conference or something or how did you get 42 people to agree to the words in this paper?Steve Quake (01:33):We did. We had a meeting at CZI to bring community members together from many different parts of the community, from computer science to bioinformatics, AI experts, biologists who don't trust any of this. We wanted to have some real contrarians in the mix as well and have them have a conversation together about is there an opportunity here? What's the shape of it? What's realistic to expect? And that was sort of the genesis of the article.Eric Topol (02:02):And Charlotte, how did you get to be drafting the paper?Charlotte Bunne (02:09):So I did my postdoc with Aviv Regev at Genentech and Jure Leskovec at CZI and Jure was part of the residency program of CZI. And so, this is how we got involved and you had also prior work with Steve on the universal cell embedding. So this is how everything got started.Eric Topol (02:29):And it's actually amazing because it's a who's who of people who work in life science, AI and digital biology and omics. I mean it's pretty darn impressive. So I thought I'd start off with a quote in the article because it kind of tells a story of where this could go. So the quote was in the paper, “AIVC (artificial intelligence virtual cell) has the potential to revolutionize the scientific process, leading to future breakthroughs in biomedical research, personalized medicine, drug discovery, cell engineering, and programmable biology.” That's a pretty big statement. So maybe we can just kind of toss that around a bit and maybe give it a little more thoughts and color as to what you were positing there.Steve Quake (03:19):Yeah, Charlotte, you want me to take the first shot at that? Okay. So Eric, it is a bold claim and we have a really bold ambition here. We view that over the course of a decade, AI is going to provide the ability to make a transformative computational tool for biology. Right now, cell biology is 90% experimental and 10% computational, roughly speaking. And you've got to do just all kinds of tedious, expensive, challenging lab work to get to the answer. And I don't think AI is going to replace that, but it can invert the ratio. So within 10 years I think we can get to biology being 90% computational and 10% experimental. And the goal of the virtual cell is to build a tool that'll do that.Eric Topol (04:09):And I think a lot of people may not understand why it is considered the holy grail because it is the fundamental unit of life and it's incredibly complex. It's not just all the things happening in the cell with atoms and molecules and organelles and everything inside, but then there's also the interactions the cell to other cells in the outside tissue and world. So I mean it's really quite extraordinary challenge that you've taken on here. And I guess there's some debate, do we have the right foundation? We're going to get into foundation models in a second. A good friend of mine and part of this whole I think process that you got together, Eran Segal from Israel, he said, “We're at this tipping point…All the stars are aligned, and we have all the different components: the data, the compute, the modeling.” And in the paper you describe how we have over the last couple of decades have so many different data sets that are rich that are global initiatives. But then there's also questions. Do we really have the data? I think Bo Wang especially asked about that. Maybe Charlotte, what are your thoughts about data deficiency? There's a lot of data, but do you really have what we need before we bring them all together for this kind of single model that will get us some to the virtual cell?Charlotte Bunne (05:41):So I think, I mean one core idea of building this AIVC is that we basically can leverage all experimental data that is overall collected. So this also goes back to the point Steve just made. So meaning that we basically can integrate across many different studies data because we have AI algorithms or the architectures that power such an AIVC are able to integrate basically data sets on many different scales. So we are going a bit away from this dogma. I'm designing one algorithm from one dataset to this idea of I have an architecture that can take in multiple dataset on multiple scales. So this will help us a bit in being somewhat efficient with the type of experiments that we need to make and the type of experiments we need to conduct. And again, what Steve just said, ultimately, we can very much steer which data sets we need to collect.Charlotte Bunne (06:34):Currently, of course we don't have all the data that is sufficient. I mean in particular, I think most of the tissues we have, they are healthy tissues. We don't have all the disease phenotypes that we would like to measure, having patient data is always a very tricky case. We have mostly non-interventional data, meaning we have very limited understanding of somehow the effect of different perturbations. Perturbations that happen on many different scales in many different environments. So we need to collect a lot here. I think the overall journey that we are going with is that we take the data that we have, we make clever decisions on the data that we will collect in the future, and we have this also self-improving entity that is aware of what it doesn't know. So we need to be able to understand how well can I predict something on this somewhat regime. If I cannot, then we should focus our data collection effort into this. So I think that's not a present state, but this will basically also guide the future collection.Eric Topol (07:41):Speaking of data, one of the things I think that's fascinating is we saw how AlphaFold2 really revolutionized predicting proteins. But remember that was based on this extraordinary resource that had been built, the Protein Data Bank that enabled that. And for the virtual cell there's no such thing as a protein data bank. It's so much more as you emphasize Charlotte, it's so much dynamic and these perturbations that are just all across the board as you emphasize. Now the human cell atlas, which currently some tens of millions, but going into a billion cells, we learned that it used to be 200 cell types. Now I guess it's well over 5,000 and that we have 37 trillion cells approximately in the average person adult's body is a formidable map that's being made now. And I guess the idea that you're advancing is that we used to, and this goes back to a statement you made earlier, Steve, everything we did in science was hypothesis driven. But if we could get computational model of the virtual cell, then we can have AI exploration of the whole field. Is that really the nuts of this?Steve Quake (09:06):Yes. A couple thoughts on that, maybe Theo Karaletsos, our lead AI person at CZI says machine learning is the formalism through which we understand high dimensional data and I think that's a very deep statement. And biological systems are intrinsically very high dimensional. You've got 20,000 genes in the human genome in these cell atlases. You're measuring all of them at the same time in each single cell. And there's a lot of structure in the relationships of their gene expression there that is just not evident to the human eye. And for example, CELL by GENE, our database that collects all the aggregates, all of the single cell transcriptomic data is now over a hundred million cells. And as you mentioned, we're seeing ways to increase that by an order of magnitude in the near future. The project that Jure Leskovec and I worked on together that Charlotte referenced earlier was like a first attempt to build a foundational model on that data to discover some of the correlations and structure that was there.Steve Quake (10:14):And so, with a subset, I think it was the 20 or 30 million cells, we built a large language model and began asking it, what do you understand about the structure of this data? And it kind of discovered lineage relationships without us teaching it. We trained on a matrix of numbers, no biological information there, and it learned a lot about the relationships between cell type and lineage. And that emerged from that high dimensional structure, which was super pleasing to us and really, I mean for me personally gave me the confidence to say this stuff is going to work out. There is a future for the virtual cell. It's not some made up thing. There is real substance there and this is worth investing an enormous amount of CZIs resources in going forward and trying to rally the community around as a project.Eric Topol (11:04):Well yeah, the premise here is that there is a language of life, and you just made a good case that there is if you can predict, if you can query, if you can generate like that. It is reminiscent of the famous Go game of Lee Sedol, that world champion and how the machine came up with a move (Move 37) many, many years ago that no human would've anticipated and I think that's what you're getting at. And the ability for inference and reason now to add to this. So Charlotte, one of the things of course is about, well there's two terms in here that are unfamiliar to many of the listeners or viewers of this podcast, universal representations (UR) and virtual instrument (VIs) that you make a pretty significant part of how you are going about this virtual cell model. So could you describe that and also the embeddings as part of the universal representation (UR) because I think embeddings, or these meaningful relationships are key to what Steve was just talking about.Charlotte Bunne (12:25):Yes. So in order to somewhat leverage very different modalities in order to leverage basically modalities that will take measurements across different scales, like the idea is that we have large, may it be transformer models that might be very different. If I have imaging data, I have a vision transformer, if I have a text data, I have large language models that are designed of course for DNA then they have a very wide context and so on and so forth. But the idea is somewhat that we have models that are connected through the scales of biology because those scales we know. We know which components are somewhat involved or in measurements that are happening upstream. So we have the somewhat interconnection or very large model that will be trained on many different data and we have this internal model representation that somewhat capture everything they've seen. And so, this is what we call those universal representation (UR) that will exist across the scales of biology.Charlotte Bunne (13:22):And what is great about AI, and so I think this is a bit like a history of AI in short is the ability to predict the last years, the ability to generate, we can generate new hypothesis, we can generate modalities that we are missing. We can potentially generate certain cellular state, molecular state have a certain property, but I think what's really coming is this ability to reason. So we see this in those very large language models, the ability to reason about a hypothesis, how we can test it. So this is what those instruments ultimately need to do. So we need to be able to simulate the change of a perturbation on a cellular phenotype. So on the internal representation, the universal representation of a cell state, we need to simulate the fact the mutation has downstream and how this would propagate in our representations upstream. And we need to build many different type of virtual instruments that allow us to basically design and build all those capabilities that ultimately the AI virtual cell needs to possess that will then allow us to reason, to generate hypothesis, to basically predict the next experiment to conduct to predict the outcome of a perturbation experiment to in silico design, cellular states, molecular states, things like that. And this is why we make the separation between internal representation as well as those instruments that operate on those representations.Eric Topol (14:47):Yeah, that's what I really liked is that you basically described the architecture, how you're going to do this. By putting these URs into the VIs, having a decoder and a manipulator and you basically got the idea if you can bring all these different integrations about which of course is pending. Now there are obviously many naysayers here that this is impossible. One of them is this guy, Philip Ball. I don't know if you read the language, How Life Works. Now he's a science journalist and he's a prolific writer. He says, “Comparing life to a machine, a robot, a computer, sells it short. Life is a cascade of processes, each with a distinct integrity and autonomy, the logic of which has no parallel outside the living world.” Is he right? There's no way to model this. It's silly, it's too complex.Steve Quake (15:50):We don't know, alright. And it's great that there's naysayers. If everyone agreed this was doable, would it be worth doing? I mean the whole point is to take risks and get out and do something really challenging in the frontier where you don't know the answer. If we knew that it was doable, I wouldn't be interested in doing it. So I personally am happy that there's not a consensus.Eric Topol (16:16):Well, I mean to capture people's imagination here, if you're successful and you marshal a global effort, I don't know who's going to pay for it because it's a lot of work coming here going forward. But if you can do it, the question here is right today we talk about, oh let's make an organoid so we can figure out how to treat this person's cancer or understand this person's rare disease or whatever. And instead of having to wait weeks for this culture and all the expense and whatnot, yo…

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