The a16z Show - America's Autism Crisis and How AI Can Fix Science with NIH Director Jay Bhattacharya

Episode Date: September 23, 2025

Dr. Jay Bhattacharya is one of the country’s top medical experts and a 24-year professor of medicine at Stanford. After being censored and deplatformed during COVID for his role in opposing harsh lockdowns, he was appointed Director of the National Institutes of Health by President Trump in 2025.a16z General Partners Erik Torenberg, Vineeta Agarwala, and Jorge Conde join Dr. Bhattacharya to discuss the administration’s role in tackling the autism crisis, how to restore public trust in health authorities, how to make the NIH more dynamic and efficient, and how to streamline publishing and restore academic freedom.Timecodes: 0:00 Introduction1:30 Autism Initiative & New Research2:45 Drug Discoveries: Leucovorin & Tylenol Caution4:35 Preterm Birth & Broader Health Initiatives5:45 The Replication Crisis in Science8:50 Reforming NIH Funding & Scientific Culture14:00 Allocation vs. Execution at NIH17:30 Political & Scientific Decision-Making22:30 Addressing Life Expectancy & Chronic Disease27:00 Supporting Early Career Investigators34:50 Academic Freedom & Open Science37:30 Rebuilding Public Trust in Public Health41:00 Communicating Science Amid Uncertainty47:50 NIH Priorities: Nutrition, Chronic Disease, AI50:00 The Future of AI in Science & Medicine53:30 Advice for Rising Scientists55:00 The Role and Limits of AI in Science Resources:Find Dr. Bhattacharya on X: https://x.com/DrJBhattacharya and https://x.com/NIHDirector_JayFind Erik on X: https://x.com/eriktorenbergFind Jorge on X: https://x.com/JorgeCondeBioFind Vineeta on X: https://x.com/vintweetaLearn more about the NIH: https://www.nih.gov/ Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The American people are not stupid. In fact, they're quite smart. And when we talk to them in ways where we show respect for their intelligence with data, allow people to disagree, but then have the evidence right there in front of people. I think people will respond with trust where the evidence actually leads. We need kind of that Silicon Valley spirit. We should stop punishing scientists who fail. If they fail productively, let them publish in a journal to explain why they're,

what they learn from it. That Silicon Valley spirit, I think, needs to come to science a little bit more. Autism funding, old drugs with new promise, and a reset on American science. Today, we're joined by Dr. J. Badacharya, Director of the NIH with A16Z Health and Bio General Partners, Vanita Agarwalha and Jorge Condi. We cover the NIH's new $50 million autism initiative, Lucavoren's potential, and fresh scrutiny of Tylenol and pregnancy. We also dig into the replication crisis, bold funding models, rebuilding public trust, and how AI can transform health care from drug discovery to clinical care. Let's get into it.

We'll talk to Dr. Bunchartre. Thank you so much for coming on the podcast. We're stoked to have you. I'm delighted to be here. So good to talk with you. I'm a little jealous of not in Menlo Park to be there with you on this. Exactly. And we're talking Monday, September 22nd. There's big news coming out today. The Times piece on you just came out and what you reflect on that as well. But maybe you could share with us the big news and why it's so impactful. Sure. So roughly six months ago when I first started this job, Secretary Kennedy challenged me to help get answers for families with autistic kids. I mean, the prevalence has been rising for decades,

like 1 in 31 kids, I think is the CDC's latest numbers on this. That's an incredible number. I mean, we don't have answers. A lot of times families, they have these behavioral therapies that don't really work very well for a lot of their kids. We don't know the cause, so we don't know how to prevent it. And so I'd launched, worked really hard to launch this new initiative, 50 million new dollars, 250 teams applied for large research grants,

and we're going to announce today that 13 teams, are going to be granted, you know, these grants for this autism data science initiative. The other thing, there's two other things that are going to get announced today that it sort of came out of this process of working with Mehmet Oz at the Center for Medicare Medicaid Services and Marty McCarrie and Secretary Kennedy, Marty McCarrie's FDA Commissioner. One is a drug, a very common old drug called Lukovorin. It's basically like a, it's folinic acids, but it's like it serves almost like a way to deliver folate to the brain, where for when some kids have folate process, deficiency deficiency folate, you know, something you get in vegetables, right? But some kids have this

difficulty processing folate. Turns out that a lot of doctors have experience using folinic acid, lukavoren, in treating autistic kids. And kids who have this folate deficiency in their brain, it actually works. And 20% of the kids, I think, to restore speech, up to 60% of the kids, they get much better. Now, not every autistic kid is going to get better with this. You have to have the specific thing that's happening in your brain. But, you know, making that more widely available, I think this is a really good thing. The other one is a sort of a caution on Tylenol, and acetaminopin. That is a, you know, obviously very common pain reliever. It's used, it's the only sort of pain reliever and fever reducer

used recommended during pregnancy. But there's been new evidence that's emerged. And what actually highlighted by a new study put out by the Dean of the Harvard School of Public Health, just recently, actually, that suggests that use in pregnancy can correlate with subsequent autism diagnoses later on for the kids. Now, I think there's a lot of controversy still over that in the scientific literature. But it's enough, I think, to say to moms, look, just be careful. I mean, you know, you don't use it all the time. Use it only really when you really need it for high fevers, just to think prudently about it. I don't want to panic anybody. It's not the kind of result that should panic anybody. It's just a reminder that you should use

any medicine carefully, especially during pregnancy. Will there be any revised guidelines around the use of a cinnamon in pregnancy to help moms and parents sort of make a decision or have a judgment call on what they should do? There will be, yeah. So that's something that Dr. McCarrie, the FDA commissioner, is working on. And there'll be also changes in like how Medicare pays,

CMS, Medicare and Medicaid pay for Luca Vorin. So it's a cross-agency collaboration for all of that. So both the guidelines for parents, as well as sort of payment for drugs. And then we got the, I'm the most boring part. I just get to launch vast, interesting science projects for the first, over the next, that hopefully will produce answers over the next few years.

And you're also paying attention to preterm birth, and you've launched a really fascinating initiative there to, again, you know, launch not only fascinating science projects, hopefully, but also science projects, which lead to clinical insight into why that's happening to moms across America. And so, you know, that's another really interesting, adjacency, if you will, to some of the announcements that you just made today.

Yeah, I mean, the preterm birth thing is, it's really interesting. Like, we have worse outcomes in the United States than Europe does. And, you know, we don't really have great answers for why. I mean, there's lots of contributors to preterm birth. Of course, prenatal care is so important during pregnancy. Making sure you have access to that is really important. So that's part of it, but it's not the whole answer. And we need to get answers to families on all these things that concern us.

I've heard from so many people around the country telling me asking me answers these questions hard without excellent science. And that's my job is to make sure that we have rigorous, excellent science to address these questions. It's hard because, you know, like, science is difficult, right? You got an answer, you think is right. And then, you know, eggs were bad for me in when I was 18, it turns out, but then like later, it turns out eggs are great for you.

And I, you know, I was fearful eating eggs forever, because the science in 1985 told me that eggs are bad for you. And of course, now eggs are good for you. Just, you know, it's one of the first. One of those things where like, science is difficult, but we have to hold ourselves to higher standards. We have to be, when we talk about people about science, that's to be rigorous and reproducible,

something I've been focused on really sharply as my time as NIH directors to make sure that we invest in replication. The standard for truth in science ought to be replication. Independent teens, you don't just don't believe me, just because I say something is true. Other people, independently looking at the same thing, should arrive the same answer. Then we know, more likely, we have more,

we have more confidence that it's true rather than just, you know, high authority says so. For the layperson listening to this, what's sort of been the cause for the loss, I'll say the loss of vigor in science or the law or the challenges around being able to replicate science? What is the underlying cause for this trend? I mean, the underlying problem is just that science is hard. I mean, that's really the bottom line. And then the secondary cause is that there's just a lot of it, a lot more than there was. Like once upon a time, you know, you go back to 1900 or something, every scientist knew each other or basically knew almost every other scientist and everyone was checking each other.

That was just a normal course. Now you have vast fields where it's very specialized, and it's hard to get people to check other people's work. There's no return for it. If I spend my career checking other people's work, I'm not going to get a professorship at a fancy university. And science is hard, right? It's very easy for a scientist to latch onto an idea and say,

this is right. I know this is right. but it may not be right. And so what matters is other people looking at it find the same thing. But often when other people look at it, they don't find the same thing, but we don't learn about that, right? There's been the last two decades, there's been a replication crisis in science with increasing realization.

The standards we hold ourselves to science in determining truth are too low. We basically, you can get a paper published a peer-reviewed journal. I've had 180 of them myself, which I apologize for everyone. But the thing is, the fact that it's published in a journal doesn't mean it's right. It doesn't mean it's true. It's useful. That's my expression of my belief about that scientific idea.

I think most of my things are true, but every scientist thinks that everything they publish is true. That's not enough. You have to have replication. You have to have other people checking each other's work because it's so easy to convince yourself in science that you're right. And so it's really those two things.

The volume of science means that people are so specialized and there's no returns, there's no incentives to check each other's work as much as we ought to. And then the publication standards are too, because science is too hard, science is so hard, and publication standards are not high enough, really. That's really the reason for the replication crisis. Well, first, I just want to comment.

There was a joke going around yesterday, sort of a quote tweet on Twitter in response to sort of any potential reduction in autism that someone said this is a direct attack on Silicon Valley startup productivity. And what will this mean for startups? But yeah. My goodness.

Exciting news there. Say more just in terms of maybe we could zoom out. You mentioned, you know, took over six months ago. What are your reflections so far in terms of your activity and achievements to date and then what you hope to, you know, achieve going forward? Well, I mean, we've done a lot. So, like, one of the first things I did was we looked at, you know, the way we fund foreign collaborations, right?

So it turns out that we fund foreign collaborations, but it's very difficult for the NIH check that the money is going to the right things. We couldn't audit. Like the Wuhan Lab. The NIH had sent. money to the lab, but we could not audit it. So we put in a new system, like I think foreign collaboration is really important for science, but we need

to do it in a way where I can look to the American people in the eye and say, look, we're actually tracking the money, we're checking to make sure things are going the right place, doing the right thing. I put it in a new system. The frustrating thing about that is like we put that in and all of a sudden I'm seeing reports that I want to end all foreign collaborations. I mean, couldn't be further from the truth. I just want to make make sure that we do it in a way that's auditable. I can go to

in front of Congress and say, yeah, I know we sent money to do it on a lab, and here's the lab notebooks that they worked on, which we couldn't do under the old system. We've changed the way that we evaluate grants. So we have a fantastic, at the NIH, we have a great way of valuing grants called the Center for Scientific Review. It's a world's best peer review organization. Turns out the bunch of the institutes, the 27 institutes,

a bunch of the institutes had their own parallel review system. So we centralized that, made it so that everyone is viewed the same way. The other thing, actually, this is related to Silicon Valley, it's something we're working on right now. Okay, you guys are going to tell me that I don't know anything about Silicon Valley, because I didn't work for A16Z, but I just tell you, my view of this is, like, the reason why you all are so successful is that if you as a 16Z,

you have a portfolio of 50 projects, and you fund 50 of them, and 49 of them fail, and the 50th is, you know, Google or something, you view that portfolio as a tremendous success. And the people that, that those 49 companies, they're going to get a second chance, especially if their failure was productive. You don't punish failure that much. You're willing to have a portfolio where you think big, right?

I think that spirit needs to come to science. I did publish work before the pandemic asking, essentially, is the NIH willing to think big? And too often the answer in recent decades has been no. If you look at back in the 1980s and 1990s, the NIH was funding ideas that were like zero, one, two years old. The typical scientific problem, funded by the NIH in the early 2000s and

2000s was like six, seven, eight years old. We just became too scared of trying new ideas out. We need kind of that Silicon Valley spirit so that, and we should stop punishing scientists who fail. If they fail productively, let them publish in a journal to explain what they learn from it. Like that Silicon Valley spirit, I think, needs to come to science a little bit more.

And do you think that the mechanism for reviewing the grants, say, at the NIH, became overly cautious, or did the scientists themselves become overly cautious? Well, I mean, those are closely linked. It's a peer review organization. I mean, I sat on those scientific view panels for a decade, two decades, and I watched what happens. So suppose a new idea comes in front of me, right? Well, I'm really good at methods, and especially methods related with the old idea that's,

this, a new idea is not competing with my idea, right? And so, like, I look at the new idea, I go, this, there's no way it can work. And I say that to this peer review panel, and everyone says, yeah, there's no way it can work. So easy to do, right? I'm sure you face the temptation too at A-16. You get a thing, you look at the thing. You're like, this guy's obviously a genius, but he has an idea that couldn't possibly work.

That temptation is very strong. And too often in science, we say, yeah, in scientific funding, we say, yeah, we don't want to try it out. And yeah, most new ideas are going to fail. That's just normal. You expect that to happen. But if you don't leave room for people to try them out, you're never going to make big advances.

I think that's what happened to the culture of biomedical science the last few decades. It's too focused on incremental progress, not enough on enormous. Now, of course, there have been big improvements, big scientific discoveries, right? I don't want to downplay that. That's true. But we spend a lot of money, and per dollar we spend a whole bunch of economists who have looked at this, and the science of science folks have looked at this say that we are getting too few advances per dollar that we spend.

That's because the culture is too conservative. Yeah, it's interesting. It's sort of why many great venture partnerships, you know, ourselves and included, are not consensus-driven. You can't drive, you can't require unanimous consent to fund a big, bold idea because someone's going to say,

hey, no way that's going to work. And someone has to be willing to take that bet. I'm curious, and correct me if this is kind of not how you think about the NIH structurally. But it occurs to me, kind of as an outside observer of the organization, you know, again, for listeners, our countries and the world's largest federally funded, you know, federal funder of biomedical research across 27 different institutes, over 35 billion in funding. You know, there's a massive organization funding essentially across multiple

sub-disease categories, the most important research that we believe will advance our health. as a population. And it seems to me that there are two big categories in which the NIH has to get decision-making right. One is allocation and sort of how you decide, how much should go to immunology versus infectious disease versus maternal health versus autism and behavioral health. And there's kind of this fundamental values-based,

you know, population input-based, you know, citizenship input-based, whatever it might be. There's some risk return-based methods that you have to do to decide how do you allocate funds across these different areas. And then there's an execution challenge. Okay, once you've decided you're going to allocate this quantum of capital in research funding to this area. How do you pick the right investigators? How do you keep them honest?

How do you drive data return? How do you measure productivity on an ongoing basis? How do you incentivize ongoing risk-taking in a multiple-year project? How do you get your agreement straight with an international, you know, funding, you know, research partner? All these are sort of all in the bucket of execution. Is that a reasonable way for people to think about the NIH? Like you got a nail allocation and then nail execution and you're in it to reform both? Okay, first of all, you're like, you're very well trained as an economist.

That's very clear to me because that's exactly the right way how an economist was your class. I'm not, yep. I mean, but no, I mean, that's exactly right, right? So first, there's a decision about where, which diseases should we focus on. It's not only a scientific problem. It's also a political problem. Like the, and it ought to be a political problem for the reasons you just articulate it, right? The things that we focus on to reflect the real needs of the people that fund us,

if we're just doing science for science's sake and we're just wandering around without producing answers, or improvements for people's lives. Well, the question is, why should they fund us? And it's actually Congress that decides this. Congress and the president together and the budget decide, where does the money go? How much to infects diseases? How much to heart disease?

How much to cancer? How much to pediatric conditions? There's a whole allocation that reflects the political will of the people, as well as the scientific opportunities, right? So it's a mix of the two that decides that. And I think it's so completely appropriate that that be the case. So let me push back on that.

Why? Why do people know enough about science and our ability to make progress in important disease areas? They may not even know the names of the diseases. They may not know anything about the true prevalence. We've enabled them to be productive in careers entirely outside biomedical science expressly so that the experts can weigh in on where science is going. going to improve their health on an ongoing basis. And so you may say, oh, that's, you know,

that's an overly paternalistic view. Or you could say, well, that's what people decided they wanted. They didn't want to have to worry about exactly what research needed to be done. They decided to offload that cognitive load to you at the NIH. And they may not want a voice in that. Or at least that's kind of one argument I'd make in response to the idea that allocation should be political.

How would you respond to that? Well, I think, so let me get back to the second half of your characterization, because that's where the scientific sort of expertise comes in, right? So within each area, it is absolutely vital that scientists have their say, right? That they can say, well, this idea for addressing Alzheimer's is promising. This idea for addressing, you know, autism is promising. And then they can, and then scientists can check themselves and say, well, is this actually promising, right? So the NIH's role is to mediate that, take that scientific input and make portfolio decisions

that will actually advance health in those areas, right? That's basically my job. And so that, I think the scientists have their say. But in the question of where should the money go, right? So let me just go back to the HIV epidemic, just to give us some sense of what can go wrong, right? So the early rise in HIV was not met with a sufficient response by the NIH. We're talking very early in the early 80s of money going to research on this vital topic. And it was the political movement of HIV patients coming together saying,

look, it's really important that we address this that led to the NIH actually taking that real public health threat seriously. right if you leave it to scientists themselves or I should say ourselves I'll say two things one is we don't reflect the will of the people like we're not good at mediating between different

population groups I mean and it's it's not right right there's no philosopher king that can decide well this much money should go to HIV this much money should go to cancer this much money should go to pediatric conditions it's the will of the people And so really, I don't see any other way to do it.

You know, like Winston Churchill says, said that democracy is the worst system of government on earth except for all the others. I mean, we don't have a philosopher king. Leaving it to scientists is not an answer. Like, the people really should have some say in where that allocation happens, I think. The other part of it is that, frankly,

I mean, this is something related to what we just talked about before. Scientists, if you ask us, we're not actually good at predicting the few, of the future in terms of like our, will this investment result in productivity? I mean, actually, frankly, neither is Silicon Valley, right? You can't say, you can't promise me that every single project you pick is going to work for your portfolio. You cannot, right? And so scientists play a vital role in deciding what scientific opportunities there are,

letting us know and then we can make decisions. But the portfolio decision, that's not exactly the scientific decision. And that's an economic, microeconomic, small E kind of decision. And then the macroeconomic decision is where there's these areas we should go to. It really shouldn't just be scientists that decide that. Of course, there's an interplay, right? So if there's a scientific opportunity in a particular area, I want to be able to reflect back to Congress and say,

well, this is a great area. You should fund this right now because, you know, there's huge advances in cell-based therapy for sickle cell disease. We definitely need to fund that, right? And then Congress can move based on that scientific opportunity. But that's an exchange between, you know, the people and the scientists, not just a one-way street. I like that. That's insightful. It's awesome.

Yeah. I mean, it seems like a more interdisciplinary approach to allocation and execution. That includes an understanding of how much we're spending, how much it costs on a go-forward basis, what the economic impacts might be of getting the research right. No, thanks for sharing that view. I think it's important for people to understand that you. trying to bring more voices to the allocation question and more rigor to the execution question,

but both are not as straightforward as it may seem. Yeah, this is a weirdly complicated job. I thought being a professor was complicated, but this turns out it's a little more complicated. Are there certain areas you feel were under-allocated or over-allocated if you could just wave a while? Oh, every area is under-allocated, of course.

I mean, I think the thing is about the under-allocation is, I don't know if it's a question of money. But if you look at the trends in public health over the last decade and half, the United States has seen no increase in life expectancy. We have enormous overhang of patients, people with heart disease, actually cancer. We've seen big improvements in life expectancy, or sort of life expectancy. because of the African-in-cancer, but huge increases in the incidence of cancer. Type 1, type 2 diabetes, autism. We've talked about a whole host of other chronic conditions.

I mean, and we've made big advances in other places, right? So the question is like, how can we address the biggest health needs of the country? Right. It seems like we're really good at, like, and we should be good at, some of the, some conditions that have lower prevalence. Like, we've made tremendous advances in HIV. It's a huge cause for celebration, right? We still have some way to go.

40,000 people got HIV last year. We can end the HIV epidemic. We should still invest in that. But at the same time, what about all the people that died of heart attacks? What all the people have type 2 diabetes that are suffering from, you know, blindness because they have, you know, bleeding in their eyes or in their retinas? I mean, like, so you have, what about the people with kidney failure that the prevalence is rising? What about all?

We have to look at the practical health needs of the country that are people where people are suffering and make sure that we address our science to those things. I don't think we've done that as much as we ought to. And just look at the macroeconomics. You don't have any increase in life expectancy in this country over a decade. Science isn't the only reason why.

Like the fact that the NIH, I mean, the NIH contributes to that, but it's not the only answer. Obviously, it's very complicated. But the NIH ought to contribute to that. Things with science we do should translate over to better. health for people. And so really, those areas where people are suffering the most, that's where I want are sort of, I would say, is under-allocated.

I love this idea of comparing or analogizing the NIH to almost like a portfolio manager, right? And similar to what we do as venture capitalist in Silicon Valley. And if I really wanted to abuse your analogy, which I will, if you'll allow me for a second, you know, the people are almost like your limited partners. So the ones that tell you, these are the sort of the the the

thesis and the fund areas we want to be. want you to go after. And you all are the investors, the venture capital investors that have to do the portfolio management, picking and all of that. You said a few minutes ago that a lot of the grants in the NIH are going to older ideas. And there's lots of data that shows they're also going to,

you know, more established, you know, older scientists, you know, at the very high, you know, highly regarded institutions. The equivalent of that would be if we only funded 30-year executives that came out of, you know, large, and ignored, you know, the young up-incomeers, you know, coming right out of the university or dropping out of school or whatever. You've talked a little bit about, you know, that question.

Like, how do you reform the process, the, you know, the execution, to use Veneta's phrasing, on selecting for the innovation that, if you will, bubbles up from the bottom? And it's a hard question, actually. That's something that's the top of my mind. And actually, what you just described is exactly what we've been doing in science.

for a long time. So the data out of the NIH is that in the 1980s, if you were 35, you actually had a chance of getting a large NIH grant. Like that was the median age of the first large NIH grant, you were 35 years old. Now you're in your mid-40s. We tell young investigators, you got to do, which by the way, super young. To be clear. Mid-40s, super young. I just want to be clear about that. I mean, I'm 57, so like, I don't know. I mean, they're all seem like babies to me. But the thing is, you have, just like as in Silicon Valley, the new ideas come from younger investigators, right? So I did a study a few years back where I looked at, it turns out that the age of the ideas in your published work ages by every one year for every year of chronological age. So my ideas get one year older every year that I age.

The very best scientists fight like crazy to stop that. So every two years of chronological age for Nobel Prize winners, their ideas and their papers age by a year. If you want the newest ideas, you have to let the young people have a try. And we're just bad at that. Like young people, we fund them, and then they drop out and they leave for other places. That wasn't true back in the 70s and 80s. The culture of biomedicine says,

you have to have one, two, three postdocs before you have shot at an assistant professor job. And as a result, the ideas that we support are just, they're just older. I mean, not necessarily a bad thing. I mean, of course, you should in the portfolio have some support for older ideas that are still promising. But if you don't also fund some of the newer ideas, the portfolio is going to produce fewer advances as a whole than if you do, right? You have to have a, you have to diversify in that sense. To solve that problem is hard. So the NIH has been trying to solve this now for two decades,

and we made no progress. So first, we have to, I think, I mean, I just give you some sense of where we got it backwards. You know, we used to have a system of peer review where in order to be a peer reviewer, you had to have a large grant. Now think about that. I got a large grant.

I'm in my 50s, and I see an idea that challenge, challenges my 30 years of work. And I'm a reviewer on a panel. It's really hard to open your mind and say, well, I might have been wrong. That system, now that got changed, so that we don't longer have that rule, but like, it's the mindset.

You have to allow, so what I've done is I've asked the Institute directors, I've given them the authority essentially, to expand what they can do in terms of the portfolio. I'm not going to judge them to make, just like within Silicon Valley, I'm not going to judge them to, does every single grant succeed? I'm going to judge them on the portfolio as a whole. Does it translate it a better health for the people that they're, for the disease that they're like trying to address or the diseases that they're trying to address? Does it result in big advances in biological knowledge, right?

I'm going to assess the portfolio as a whole. And then the other thing is that does it match the strategic vision of the institutes. They have these like fantastic strategic plans. Like, you know, you go look at them and say, your eyes will say, you look at them, you go like, your eyes will get big with the science that they're proposing. And yet, what they actually end up funding based on their peer review panels is often they'll get 10 great proposals on one part of the strategic plan and like nothing on another part of the strategic plan. And so, like, I'm going to encourage them to be able to pick the portfolio so that matches the strategic plan. I'm going to reward them for rewarding and empowering early career investigators more. So I'm going to build incentives into the decision making by the institute directors

so that they have incentives to solve these longstanding problems. We have to solve the new investigator problem. And I'm going to start to evaluate long-established investigators because I do believe that play a pretty fundamental role still. But in like how well do they advance the careers of the early career investigators that work with them? Right. So if they're good at that kind of mentorship and career advances, I'm going to reward them in their grants. I'm going to start evaluating the grants for that for that too.

So because the grant portfolio has to be sustainable in the long run of producing new ideas. I mean, just that's we should we need to just. If we don't have the early care investigators sort of getting support they need, we're going to start to stagnate. I love to hear the interest in advancing early career investigators, but we can't have that conversation without talking about the universities from where they tend to come. And so, you know, I was a product of NIH-MSTP funding. I did my MD PhD with the generous support of the NIH,

and my peers and colleagues in my class and, you know, decades behind coming up, get trained on those grants today. How can you work with, you know, with the administration to ensure continuity for the training grants that, you know, NIH does believe are going to fuel the pipeline of early career investigators who, as you say, you know, are perhaps most likely to bring change, big ideas, you know, and take big swings?

Yeah, we, as you know, you are biophysics, right? So we have, we have a range of, a range of like ways that we support early care investigators. So there are these awards for pre-docs, pre-docs meaning undergrads. And that's really important. Like we want to make sure that the undergraduate, the very talented undergraduates who are interested in biomedicine

and research biomedicine have the support to do this. If there's also like support for, for postdocs, right? So for people who are getting their PhD and then postdocs, I want to, it's going to be hard, but we have to structure things so that the range of investments we make actually translate over to people wanting to stay in biomedicine. I mean, we have a lot of people who drop out.

But I think the rain problem isn't that support for the early, I think we have a lot of portfolies pretty good on that. We could do better, but that's pretty good. But the problem is, like, after you've had this career in biomedicine, how do you, like, do you, of this research training, do you have support to, like, make the next leap into an assistant professor job? And too often, it's too hard to do that. You can't get the support you need to do that. There's these K awards that we have that it's really difficult to get them. I think we have to do better at that.

And we have to reward universities that are better at that. There's problems all across the system, but I think that missing link is really the, you know, you finish your MD and your PhD and then can you get that resistant professor job? Or are you going to be asked to do 17 different postdocs where you have a chance? Right now, that system is set up to make it difficult. You mentioned earlier that we're not making advancements in life expectancy. Why are we lagging? Why are some European countries doing better? and what are the highest leverage points you think to get back to improving there?

Well, I think the key thing is we have to, a lot of our science is, you know, this replication question we talked about earlier is very important. We have to solve that. That will help a lot. And then this portfolio thing, I think both of those things actually will address the scientific rigor problem and the sort of conservatism problem. As far as like addressing life expectancy, that, That really needs to be, it's in a sense,

not just a scientific problem. Like, we have to, we have to essentially get a message from the people that we want, that they want scientists to address those problems. Like that's just as we talked about earlier, the political nature of that kind of allocation decision. But you know, that's exactly what the Mahab movement represents. The Mahab movement is a, it's basically a cry for help

from the American people saying, look, all these chronic disease problems, all these problems with our kids and we're sick, we're doing much worse than folks in Europe in terms of our health. And that essentially is a call for the NIH to reform itself to address those problems. And to me, it's a tremendous opportunity. And, you know, this is why I agreed to take this job. I mean, it's perfectly happy being a professor. But it's, you know, once in a lifetime opportunity to make the NIH really work for the American people.

And I think having that political movement behind us is really important for that. Last week you announced some really interesting initiatives around academic freedom. And many folks know your voice kind of reached the national stage, in part because of your ardent desire to see academic freedom respected, protected, across the country. And, you know, it sounds like you're looking for ways to improve publishing. fundamentally so that people feel freedom at all levels, including early career investigators, to share their view on science that they think might be interesting. And we need to figure out, to your point earlier,

how to make the point that anything published is not necessarily fact, but it's one opinion backed by one set of data and one set of analysis and one set of perspectives, and you'd like more of those to flourish in the public arena. Say more about the role that you want NIH to put play in protecting academic freedom. Of course, at the NIH, I found out that a lot of folks, at the internal investigators in the NIH,

in order to publish their work, had to seek permission from their supervisors. I changed that. Like no more permission. If you're an NIH researcher, you have a scientific paper, you don't have to get permission for me. People are going to publish research that I don't agree with. That's wonderful. They should be able to do that.

Also, the places that, like the universities, I think, need to be absolutely committed academic freedom for excellent science to happen. And, you know, like there's been a lot of, like, angst over the administration's actions with the universities over the last few months regarding holding them to high standards regarding, you know, anti-Semitism and so on. But there's also been a message that we really do want academic freedom at the universities. Scientists really able to say what they think and explore where they will or else they're not environments for research. As far as journals, that's a complicated question, but there's, the problem

right now is that the scientific journals, there's essentially a duopoly, a very few number of scientists, companies, for-profit companies control very large number of journals, and they charge tens of thousands, ten thousand dollars per article for science that they didn't do, that the American people paid for. They actually had a sort of a policy where if a regular person wanted to go find a scientific article, they had to go, there was a paywall where they paid like $50, 100. We got rid of that paywall for NIH-funded research. There's still a lot to do in this area. We need more academic freedom. We need more openness in scientific publishing. And I'm working on policies to do that. So, Jay, you know, one of the key questions, you know, for the American public, they're looking for better outcomes, better health.

One of the big avenues that, of course, this country uses and it's really had as a gold standard in the past, is, you know, having this extraordinary public health infrastructure. But I think what's also true is over the course of the last several years, there's a lot of mistrust now in terms of public health. How do you sort of rebuild that trust for the public? because obviously, you know, if there's no trust, the message can only be so effective. And so how do we build those bridges back to the extent that you think they need rebuilding? You know, I think the problem with public health

and the lack of trust in it, you have to point to the pandemic. You have no choice, right? If you look at, you think back to the pandemic, and you remember the plexiglass that was everywhere. There's still, every time there's sea of plexiglass, it fills me with rage, but that's another story. And there was no science mark behind that, right?

There was like the, you wear a mask when you walk into a restaurant and you take it off when you sit down. You know, again, no science behind it. A whole host of like things. And especially, they were really damaging things like closing schools where, again, the science was so weak that it, that. And now kids are like years behind in their education as a result. And they'll be paying the Christ for that for years. And so a lot of American people have lost trust in public health for reasons I can completely understand. And so the question then is, what can we do about it?

And to me, the key thing is there's two things that have to happen, like two very broad things. Like one, I think we have to restore gold standard science. Like that presidential EO on gold standard science is so important. Because what it says is it articulates things that we thought all science already knew or committed to. Like replication is really important. Unbiased peer review, humility and how we talk about the limitations of our science.

scientific findings. There's a whole host of things where you read it and go, wow, this is, I thought science already did that. And so if we actually do that, I think that's a major part of this. The second thing is we have to, just like we talked about earlier, about the role of the people and the politics and deciding what scientific priorities, what like areas of science to fund. And then scientists to decide what priorities within the science areas to fund and in the portfolio analysis. We have to convey to people that, that we are their partners in scientific investigation and in public health. Public health, folks in public health are servants of the people. And too often during the pandemic, it came across like we were sitting above people, right? Telling you what to do, telling you if you don't take this vaccine, you can't go to work, you can't get a job, you know, I mean,

it was it was heartbreaking to watch because if, I believe, very fundamentally, that when science works as partners, with people and has this almost servant attitude toward people, you can do a lot of good. You can do a lot of good. But I think really that kind of humility and the return to sort of gold standard science, that's the way to solve the problem of trust. It's going to take a long time, though. Because I mean, I've talked to so many people around the country and it's not, we're nowhere near solving that public trust problem. Dan, I think it's an especially challenging thing as you look forward. And I'd love to hear your thoughts on, you know, how

How do you convey, you know, recommendations and guidance in the face of uncertainty and incomplete information, right? Because going back to your point, like, in an ideal world, you're always resting on top of gold standard science, you know, but a lot of times science, you know, there's a lot of unknowns in the science. Science is hard going back to what you were saying earlier. And so how do you communicate to, you know, a population,

a nervous populace, you know, a sense of a, of a recommendation or even guidance in a world where you yourself having complete information. I think you should have to be honest, right? So if I asked a question about, I mean, God forbid, there's another pandemic during my watch, and then I'm asked, okay, how should we manage, is it right to wear masks or something, right?

And I don't, there's no good scientific evidence. I'm gonna just say that. I, you know, the knowledge I was a medical student once, I have an MD. So like I can tell you this from firsthand experience. You're at the first two years of med school, you do a bunch of class work. The third year, you finally get to see patients, right?

So you go walk into a patient room and you're wearing a white coat and you know nothing, or very little. You can fill with knowledge about biochemistry. You can write chemical equations so your fingers get tired. But what you can't do is understand what a patient really needs. And so you sit down in front of the patient. They tell you their stories, wonderful,

like they put their trust in you. And you are tempted to tell them things to answer their needs that they're asking you, but you don't know the answer. You just don't because you're a third-year-met student. Of course you don't know the answer. And there's a, because you're wearing the white coat and because of someone looking at you wanting the answer,

putting their trust in you, you feel this urge to like say things you don't know. You start like freelancing. And that's just a terrible mistake. right? As a Thurgy message, you learn, that you should just say, I don't know. I'm going to look it up. I'll look the answer for you. You'll get back to you. I'll consult with people who know more than I do. You have to be humble. And especially in the face of new things, you know, new pandemic or new or genuine scientific uncertainty, we in public health have to be humble and say, look, we're not sure, but here's how we're working to try to get an answer. And we have to convey that uncertainty. And we can't believe. blame the public. I've gone around and talked to lots of folks in public health and science, and they're like, well, what we have to do is we have to teach the public more about science and make sure they understand that science isn't always perfect and science like moves, you know,

you may have eggs are great one day and eggs are terrible another day. That's because we have new science. To me, that's like blaming the public. It's not, the public doesn't understand that science is hard. They understand it fundamentally. Like they just, this is not a complicated thing, in the sense of like, I mean, everyone knows within the public science is hard. The problem is that scientists conveyed certainty about things that they had no business conveying certainty about and then changed people's lives with the worst as a result of it during the pandemic. I acknowledge that the pandemic was a particular challenge

with respect to both communication and certainty in the midst of uncertainty. But how do we acknowledge that challenge that challenge, and not lose trust in some of the bedrocks of public health advancement that we've made over the last several decades, whether that's newborn vaccinations, you know, HHS held a listening tour and an advisory update on Hep B vaccination in babies, and it's great that we're looking at all of the data holistically there. But in some of those cases, you know, some folks would argue there

is substantially less uncertainty than there was in the wake of a new pandemic with a new virus, with no data, with new, completely new infections, you know, than there is in the context of something like a hepby. So how do we, you know, and please don't feel I need to respond to that specific vaccine example, but how do we not make it so that even when you do have relative certainty and you come out and say, hey, this is not perfect, but we're pretty darn sure this is a good idea. How do you then make it so that people don't say, well, you know, last time you said you didn't know, so I don't know. Right. So I think I don't know is a good answer when you don't know.

When you have a little more evidence, a lot more evidence, like just take the MMR vaccine. Like that, I mean, if you want to prevent measles, take the MMR. MMR vaccine. I mean, it's the best way to prevent measles. And measles can be a deadly disease. Like I vaccinated my kids with the MMR. I was really happy I did. Me too. And I think that that, you know, I think.

I think that that kind of certainty, you know, science, right? So nothing is known tomorrow that someone might come along and they overturn, you know, Newtonian physics and all of a sudden you're talking about relativity or something, right? You'll always leave open that possibility. But some things we do know with like much more certainty. I'm not saying that we should all have false humility. I think we should have humility for the things we just should actually have humility about, right? But at the same time, when we have an area of more scientific certainty,

we have to leave open room for academic freedom so that people can have their say that think differently. We don't cancel them. We just, we reason with them. And we say, look, you say X, Y, Z, but look at all this other evidence, MMR is a good example, look at other evidence that shows you differently. And they'll just have a public discussion. It's okay. I mean, it's okay to have that contradiction.

And then I think what will come across is when there is actual excellent science replicated, maybe I'm naive, but I don't think so. I think that wins scientific debates. And you can look, there's evidence for this, right? So the uptake of MMR in this country, the MMR vaccine is like 95% of American parents vaccinate their kids with MMR. The evidence is, and I think it's like 13% of American parents' to vaccinate their kids for the COVID vaccine.

I think that reflects the scientific evidence regarding the relative merits of those vaccines. The American people are not stupid. In fact, they're quite smart. And when we talk to them in ways where we show respect for their intelligence with data, allow people to disagree, but then have the evidence right there in front of people,

I think people will respond with trust where the evidence actually leads. I mean, I just, maybe that's just a matter of faith for me, but I don't see any other way forward. You mentioned that the three priorities of NIH, that you have are nutrition, chronic disease, and integrating AI. Maybe can you flesh out a little bit on the last two,

what you see is most promising in terms of reducing the disease burden and then also in terms of integrating AI? I've seen some like fantastic new ideas regarding Alzheimer's disease, for instance. A colleague of mine at Stanford did, has this like fantastic papers, he's a set of papers. published using an old shingles vaccine called Zostovacs. He found that in excellent observational studies that if you had Zastavax, it reduces the likelihood of developing cognitive decline for

Alzheimer's disease by up to 20%, 30%, I mean, it's pretty substantial for a pretty innocuous, safe vaccine that's no longer used actually because it didn't work for shingles. I mean, imagine if you had a very simple, cheap way to prevent 30% of Alzheimer's cases or delay Alzheimer's for years. There's all these, like, huge advances I've seen that, you know, just need a little bit of scientific love. I think we just need to focus on those, make our portfolios focused on those, be willing to take risks in terms of, like, on things that look like their new ideas. And we're going to make a lot of progress. And AI, by the way, I think is going to play a tremendous role in that. I just, you know, everyone knows about the protein folding and alpha fold.

that has done an amazing job in turbocharging by a drug development. Because now you don't need to sit there and wait and you can just do your computations, figure out how the protein folds, what the target sites will look like, and then ask which of these drug products are more likely to actually work

without having to do very expensive biologic, in lab work. You start to do the lab work, but they focus the lab work in more promising ways. In the way that we deliver medicine, right? So you can have AIs help radiologists do a better job at making sure they catch things, make me catch everything, even simple things. Like, you know, you go to your doctor, the doctor sits there looking at the computer

the entire time rather than you because they're like filling out their electronic health records. Have an AI assistant listen to the conversation, fill out the form for the doctor. So they're just checking out. afterwards for taking them a couple of minutes, and they're spending all their attention on you, right? All of this needs research, by the way. I mean, does this is going to help patients? We have to ask those questions.

But to me, that's a tremendous promise. Like, those simple things can transform biomedical research and how patients are treated. So that's why AI is so important to me as a potential tool. We does need research. I mean, I don't want to, we can't have AI hallucinating on us and then treating patients based on hallucinations. But that's a matter of research

fix those kind of problems. We heard that HHS rolled out across agency-wide, an enterprise-secure version of chat GPT, which seems like a terrific achievement from the perspective of internal HHS and NIH operations even, right, to be able to look up internally how new is an idea. Simple queries and data kind of fluidity of that kind seems important. what's the future? Is an AI going to write the Institute's strategic roadmap and an AI submit a grant and an AI review panel, review the grant? And, you know, where are we going to play a role as scientists?

I mean, I don't. Okay, so just to that question. The answer is no. Yeah, I mean, I think AIs are really good at summarizing existing knowledge. The training data you give it helps it. It's fantastic at that kind of thing. Really developing brand new ideas that challenge existing paradigms, I don't, I mean, your experience with AI's, but they're not quite as good at that. It's really, we have, just to put a new policy in place where I'm limiting the number of new public applications you can have, like to, we can have, you know, six the cycle or something. We have people writing 60 applications and very clearly AI generated.

And then we have, you know, it's, it's, I mean, what it does is the overall system of noise. Yeah. Yeah. So, I mean, I think AI is really important. As I said, I think it's, but it has to, we have to do research to understand how it can be used to help people. And I think people, scientists are still have a tremendously important role. The new AI system, the rollout in age is just exciting. We're actually been working on a new system also, specific to NIH, again, to protect, in a ways that the protect

patient privacy and all that, but it rolled out across the NIH so that people can like interact with it in ways that help on NIH-specific tasks as well. So I mean, I think that's all very exciting, but it's an augmentation of capacity rather than a substitution of capacity. It'll make people way more productive. It'll help us address some of the key problems, but scientists are still going to, I mean, we still have work to do a scientist. We do. If I could just, on one last question. If you had one message for the rising star scientist contemplating a career in science where they can bring the best of their abilities to making science better, smarter, faster, you know, a scientist embarking on a new PhD in a brave new field,

a scientist thinking about starting a new company to advance the work that they're doing, a scientist at the NIH running a lab. What is your one message to the individual scientist who's out there, you know, hoping to make the biggest impact they can? Science is incredible. Like, it has almost limited capacity to advance human well-being. And it's the individual scientists who believes in their idea, it keeps knocking on the door, even when the door is closed over and over again,

until it opens. that's who really makes a big difference in this world. I would say, please stay in science, keep knocking that door and change the world with it, because that's the only way the scientists can do that. I love this story of Max Perot, so I don't know if you've heard of him. He was a University of Cambridge researcher in the, I think, the 50s, and he had this idea that he could figure out the structure of myoglobin.

It sounds like a very geeky kind of thing. It's like, but back then there was no protein folding field, really. I mean, it was like, and he was a, and he was a, student. And all his professors kept telling him, pick an easier problem, Max. This is crazy. Why are you spending all your time? You're never going to finish. And for a decade at the University Cambridge, you wandered around. Everyone knew he was a genius, but he was like, got nowhere. He's not just working at it until finally he figured it out. And it's just transformed like a whole host of things in biomedicine and, you know, eventually won the Nobel Prize. It's, you know,

it's the kind of thing where I ask myself, do we have a scientific sort of infrastructure today that would allow a Max Perutz to do what he did back then. And I would love to make that happen through the sort of the power of the NIH, to allow the Max Perrits of the world, the new ones who were now sitting there with great ideas to be able to try them out and change the world with them. Fantastic. So maybe on that note, just looking to the future,

if we end where we started, where you know, you talked about the NIH's highest ambition is to improve the health of the American people, whether that's measured in life expectancy or the rate of chronic disease that Americans suffer from. If you had to guess where we're going to see the biggest and best gains, is that going to come from, you know, how we manage patients, so the management of disease,

you know, new molecules for treating disease, or modifications in terms of how we all live? Yes. Yes, yes, yes. Yes to all of the above. I mean, you know, I am a big believer in portfolios when I have uncertainty. So I don't know how to answer your question because I see promising advances in all three of those topics. And I think we have to invest in all of the above in order to see where the most promising things go. Like, who would have predicted that the GLP ones, you know, would, actually we saw a reduction in average body weight in this country the first time in

you know, decades last year because of Gila monster molecule that somehow turns out to, you know, when you, if you just do the right biology. There was a scientist knocking on some kind of door to make that happen, right? Yeah, I just, I mean, it's a, that's the only sad thing about science. It's hard, it's hard to predict where the best things are going to happen. So you have to, like, have a portfolio. But all of those areas, to me sound, look like they're very promising. And as I've gone around the country, talk to people, I'm excited about all of it. So I can't wait. wait to see what we produce. Do either of you have a prediction to that question or is it also?

Well, this is the debate we have every week in terms of where we want to invest. Our answer is yes, yes, yes, too. Correct. All of the above. Well, it's a great place to close. Dr. Bottachar, thanks so much for coming on the podcast. Thank you. Thank you so much. Thanks for being here. Have a great day. Thanks for listening to the A16Z podcast. If you enjoy the episode, let us know by leaving a review at rate thispodcast.com slash a 16Z. We've got more great conversations coming your See you next time.

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