Taking Bold Bets: NIH and the Future of Biomedical Science

The American people are not stupid. In fact, they’re quite smart. When we talk to them in ways that show respect for their intelligence with data, allow people to disagree, but then have the evidence right there in front of them, I think people will respond with trust where the evidence actually leads.

We need that Silicon Valley spirit. We should stop punishing scientists who fail. If they fail productively, let them publish in a journal that explains what they learned from it. That Silicon Valley spirit needs to come to science a little bit more.

Well, Dr. Bhattacharya, thank you so much for coming on the podcast. We’re stoked to have you.

I’m delighted to be here. It’s so good to talk with you. I’m a little jealous I’m not in Menlo Park to be there with you on this.

Exactly. We’re talking Monday, September 22. There’s big news coming out today. The Times piece on you just came out, and I want you to reflect on that as well. But maybe you could share with us the big news and why it’s so impactful.

Sure. Roughly 6 months ago, when I first started this job, Secretary Kennedy challenged me to help get answers for families with autistic kids. The prevalence has been rising for decades—1 in 31 kids, I think, was the CDC’s latest number on this. That’s an incredible number, and we don’t have answers.

A lot of times, families 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. I worked really hard to launch this new initiative: $50 million in new funding. Two hundred and fifty teams applied for large research grants, and we’re going to announce today that 13 teams are going to be awarded grants for this Autism Data Science Initiative.

There are 2 other things that are going to be announced today that came out of the process of working with the Centers for Medicare & Medicaid Services, Marty Makary, and Secretary Kennedy. Marty Makary is the FDA commissioner. One is a drug, a very common old drug called leucovorin. It’s basically folinic acid, and it serves almost like a way to deliver folate to the brain.

Some kids have difficulty processing folate. Folate is something you get in vegetables, but some kids have this difficulty processing it. It turns out that a lot of doctors have experience using folinic acid, leucovorin, in treating autistic kids—and kids who have this folate deficiency in their brains—and it actually works. I think 20% of the kids restore speech, and up to 60% of the kids get much better.

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 making that more widely available, I think, is a really good thing.

The other one is a caution on Tylenol, or acetaminophen. That’s an obviously very common pain reliever. It’s the only pain reliever and fever reducer recommended during pregnancy. But new evidence has emerged, highlighted by a new study put out by the dean of the Harvard T.H. Chan School of Public Health just recently, that suggests that use during pregnancy can correlate with subsequent autism diagnoses later on in kids.

I think there’s still a lot of controversy over that in the scientific literature. But it’s enough, I think, to say to moms, “Look, just be careful. Don’t use it all the time. Use it only when you really need it, for high fevers.” Just think prudently about it. I don’t want to panic anybody. That’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 acetaminophen in pregnancy to help moms and parents make a decision, or have a judgment call, on what they should do?

There will be. That’s something that Dr. Makary, the FDA commissioner, is working on. There will also be changes in how CMS, Medicare, and Medicaid pay for leucovorin. It’s a cross-agency collaboration for all of that: both the guidelines for parents as well as payment for the new drug.

Then I get to do the most boring part. I get to launch vast, interesting science projects over the next few years that will hopefully produce answers.

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

The preterm birth issue is really interesting. We have worse outcomes in the United States than Europe does, and we don’t really have great answers for why. There are 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.

We need to get answers to families on all these things that concern us. I’ve heard from so many people around the country asking me for answers to these questions. It’s hard without excellent science, and that’s my job: to make sure that we have rigorous, excellent science to address these questions.

It’s hard because science is difficult. You get an answer you think is right, and then eggs were bad for me when I was 18. Later, it turns out eggs are great for you. I was fearful of eating eggs forever because the science in 1985 told me that eggs were bad for you. Of course, now eggs are good for you.

It’s one of those things where the science is difficult, but we have to hold ourselves to higher standards. We have to be rigorous when we talk to people about science. It has to be rigorous and reproducible.

Something I’ve been focused on sharply during my time as NIH director is making sure that we invest in replication. The standard for truth in science ought to be replication. Don’t just believe me because I say something is true. Other people independently looking at the same thing should arrive at the same answer. Then we know, more likely, that it’s true; we have more confidence that it’s true, rather than just a high authority saying so.

For the layperson listening to this, what’s been the cause for the loss of vigor in science—or the challenges around being able to replicate science? What’s the underlying cause for this trend?

The underlying problem is just that science is hard. That’s really the bottom line. The secondary cause is that there’s just a lot more of it than there was. Once upon a time, if you go back to around 1900, every scientist basically knew almost every other scientist, and everyone was checking each other. That was just the normal course of things.

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.

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. What matters is whether other people looking at it find the same thing. Often, when other people look at it, they don’t find the same thing, but we don’t learn about that.

For the last 2 decades, there’s been a replication crisis in science, with an increasing realization that the standards we hold ourselves to in science for determining truth are too low. Basically, you can get a paper published in a peer-reviewed journal. I’ve had about 180 of them myself, for which I apologize to everyone. But 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. It’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.

It’s really those 2 things. The volume of science means that people are so specialized, and there are no incentives to check each other’s work as much as we ought to. Then the publication standards are too low because science is too hard. Science is so hard, and publication standards are not high enough. 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 any potential reduction in autism, where someone said, “This is a direct attack on Silicon Valley startup productivity.” What will this mean for startups? But, yeah—

Oh my goodness.

Exciting news there. Say more, just in terms of—

Maybe we could zoom out. You mentioned you took over 6 months ago. What are your reflections so far in terms of your activity and achievements to date, and what do you hope to achieve going forward?

Well, we’ve done a lot. One of the first things I did was look at the way we fund foreign collaborations. It turns out that we fund foreign collaborations, but it’s very difficult for the NIH to check that the money is going to the right things. We couldn’t audit the Wuhan lab. The NIH had sent money to the Wuhan lab, but we couldn’t audit it.

So we put in a new system for allowing foreign collaborations. I think foreign collaboration is really important for science, but we need to do it in a way where I can look the American people in the eye and say, “Look, we’re actually tracking the money. We’re checking to make sure things are going to the right place and doing the right thing.”

I put in a new system. The frustrating thing about that is that we put it in, and all of a sudden I’m seeing reports that I want to end all foreign collaborations, which couldn’t be further from the truth. I just want to make sure that we do it in a way that’s auditable. I can go in front of Congress and say, “Yeah, I know where we sent money to a lab, and here are the lab notebooks that they sent and worked on,” which we couldn’t do under the old system.

We’ve changed the way that we evaluate grants. The NIH has a fantastic way of evaluating grants called the Center for Scientific Review. It’s the world’s best peer-review organization. It turns out that a bunch of the institutes—there are 27 institutes—had their own parallel review systems, so we centralized that and made it so that everyone is reviewed the same way.

The other thing—actually, this is related to Silicon Valley—is something we’re working on right now. You guys are going to tell me that I don’t know anything about Silicon Valley, even though I haven’t worked for a16z, but I’ll tell you my view of this. The reason why you all are so successful is that if you, as a16z, have a portfolio of 50 projects and you fund 50 of them, and 49 of them fail and the 50th is Google or something, you view that portfolio as a tremendous success.

The people at those 49 companies are 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? You’re willing—and I think that spirit needs to come to science.

I did publish work before the pandemic asking how willing the NIH is to think big, and too often the answer in recent decades has been no. If you look back at the 1980s and 1990s, the NIH was funding ideas that were 0, 1, or 2 years old. The typical scientific project funded by the NIH in the 2000s and 2010s was 6, 7, or 8 years old. We just became too scared of trying new ideas out.

We need that Silicon Valley spirit, and we should stop punishing scientists who fail. If they fail productively, let them publish in a journal to explain why they failed and what they learned from it. That Silicon Valley spirit needs to come to science a little bit more.

Do you think that the mechanism for reviewing grants at the NIH became overly cautious, or did the scientists themselves become overly cautious?

Well, those are closely linked. It’s a peer-review organization. I sat on those scientific panels for a decade—two decades—and I watched what happens.

Suppose a new idea comes in front of me. I’m really good at methods, especially methods related to the old idea. The new idea isn’t competing with my idea, right? I look at the new idea and go, “There’s no way it can work.” I say that to the peer-review panel, and everyone says, “Yeah, there’s no way it can work.” It’s so easy to do, right?

I’m sure you face the temptation at a16z, too. You get a thing, and you look at it and you’re like, “This guy’s obviously a genius, but he has an idea that couldn’t possibly work.” That temptation is very strong. Too often in science, in scientific funding, we say, “Yeah, we don’t want to give it a try.”

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 over the last few decades: it’s too focused on incremental progress, not enough on enormous advances.

Of course, there have been big improvements and big scientific discoveries. I don’t want to downplay that; that’s true. But we spend a lot of money, and a bunch of economists who have looked at this, as well as the science-of-science folks, say that we are getting fewer advances per dollar that we spend. It’s because the culture is too conservative.

Yeah, it’s interesting. That’s sort of why many great venture partnerships, ourselves included, are not consensus-driven. You can’t require unanimous consent to fund a big, bold idea because someone is going to say, “Hey, no, there’s no way that’s going to work.” Someone has to be willing to take that bet.

I’m curious—and correct me if this isn’t how you think about the NIH structurally—but it occurs to me, as an outside observer of the organization, that the NIH is our country’s—and the world’s—largest federally funded funder of biomedical research, across 27 different institutes and with over $35 billion in funding. It’s a massive organization funding, essentially across multiple disease categories, the most important research that we believe will advance our health as a population.

It seems to me that there are 2 big categories in which the NIH has to get decision-making right. One is allocation: how you decide how much should go to immunology versus infectious disease versus maternal health, versus autism and behavioral health. There’s some fundamental, values-based, population-input-based, citizen-input-based—whatever it might be—risk-return-based method that you have to use to decide how to allocate funds across these different areas.

Then there’s an execution challenge. 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 multiyear project? How do you get your agreements straight with an international research partner? All of these are in the bucket of execution.

Is that a reasonable way for people to think about the NIH? You’ve got to nail allocation and then nail execution, and you’re in it to reform both.

First of all, you’re very well trained as an economist. That’s exactly the right way an economist would think about it.

First, there’s a decision about which diseases we should focus on. That’s not only a scientific problem; it’s also a political problem. It ought to be a political problem for the reasons you just articulated. The things that we focus on should 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, the question is, why should they fund us? It’s actually Congress that decides this. Congress and the president together, in the budget, decide where the money goes: how much to infectious 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 needs and opportunities. It’s a mix of the 2 that decides that, and I think it’s completely appropriate that that be the case because—

So let me push back on that. 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 to improve their health on an ongoing basis.

You may say, “Oh, 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.” At least that’s one argument I’d make in response to the idea that allocation should be political.

How would you respond to that?

Well, let me get back to the second half of your characterization, because that's where the scientific expertise comes in. Within each area, it is absolutely vital that scientists have their say. They can say, “This idea for addressing Alzheimer's is promising; this idea for addressing autism is promising.” Then scientists can check themselves and say, “Is this actually promising?”

The NIH's role is to mediate that, take that scientific input, and make portfolio decisions that will actually advance health in those areas. That's basically my job. The scientists have their say, but in the question of where the money should go, let me just go back to the HIV epidemic to give us some sense of what can go wrong.

The early rise in HIV was not met with a sufficient response by the NIH. We're talking about the very early 1980s, when money was going to research on this vital topic. It was the political movement of HIV patients coming together and saying, “Look, it's really important that we address this,” that led to the NIH actually taking that real public health threat seriously.

If you leave it to scientists themselves—or I should say ourselves—I'll say 2 things. One is, we don't reflect the will of the people. We're not good at mediating between different population groups. There's no philosopher king who can decide, “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 I really don't see any other way to do it.

Wasn't it Winston Churchill who said that democracy is the worst system of government on earth, except for all the others? We don't have a philosopher king. Leaving it to scientists is not an answer. The people really should have some say in where that allocation happens.

The other part of it is that, frankly, scientists, if you ask us, are not actually good at predicting the future in terms of whether our investments will result in productivity. Frankly, neither is Silicon Valley. You can't promise me that every single project you pick is going to work for your portfolio. You cannot.

Scientists play a vital role in deciding what scientific opportunities there are and letting us know, and then we can make decisions. But the portfolio decision is not exactly the scientific decision. That's an economic, small-e, microeconomic kind of decision. Then the macroeconomic decision is which disease areas we should go to. It really shouldn't just be scientists who decide that.

Of course, there's an interplay. If there's a scientific opportunity in a particular area, I want to be able to reflect back to Congress and say, “This is a great area. You should fund this right now because of the huge advances in cell-based therapy for sickle cell disease. We definitely need to fund that.” Then Congress can move based on that scientific opportunity. But that's an exchange between the people and the scientists, not just a one-way street.

I like that. That's insightful.

That's awesome.

Yeah. 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, and what the economic impacts might be of getting the research right.

Thanks for sharing that view. I think it's important for people to understand that you're trying to bring more voices to the allocation question and more rigor to the execution question. But both are not as straightforward as they may seem.

Yeah, this is a weirdly complicated job. I thought being a professor was complicated, but this turns out to be a little more complicated than that.

Are there certain areas you feel were underallocated or overallocated, if you could just wave a wand?

Every area is underallocated, of course. I don't know if it's a question of money. If you look at the trends in public health over the last decade and a half, the United States has seen no increase in life expectancy. We have an enormous overhang of people with heart disease. We've seen big improvements in life expectancy after getting cancer, but huge increases in the incidence of cancer. Type 1 and type 2 diabetes, autism—we've talked about a whole host of other chronic conditions.

We've made big advances in other places, right? The question is: How can we address the biggest health needs of the country? It seems like we're really good at—and we should be good at—some conditions that have lower prevalence. We've made tremendous advances in HIV. It's a huge cause for celebration. We still have some way to go: 40,000 people got HIV last year. We can end the HIV epidemic, and we should still invest in that.

At the same time, what about all the people who died of heart attacks? What about all the people who died from type 2 diabetes or are suffering from blindness because they have bleeding in their eyes or retinas? What about the people with kidney failure, where the prevalence is rising? We have to look at the practical health needs of the country, 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. Just look at the macroeconomics: You don't have any increase in life expectancy in this country in over a decade. Science isn't the only reason why. The fact that the NIH contributes to that doesn't mean it's the only answer. Obviously, it's very complicated, but the science we do should translate into better health for people. Really, those areas where people are suffering the most—that's where I would say we are underallocated.

I love this idea of comparing the NIH to almost a portfolio manager, similar to what we do as venture capitalists in Silicon Valley. If I really wanted to abuse your analogy, which I will, if you'll allow me for a second, the people are almost like your limited partners. They're the ones who tell you, “These are the theses and fund areas we want you to go after.” You all are the venture capital investors who have to do the portfolio management and the picking.

You said a few minutes ago that a lot of the grants at the NIH are going to older ideas. There's lots of data that shows they're also going to more established, older scientists at highly regarded institutions. The equivalent of that would be if we only funded 30-year-old executives who came out of large, established companies and ignored the young up-and-comers coming right out of university, dropping out of school, or whatever.

You've talked a little bit about the question of how you reform the process—the execution, to use Vineeta's phrasing—to select for the innovation that, if you will, bubbles up from the bottom. It's a hard question, actually. It's something that's at the top of my mind. And actually, what you just described is exactly what we've been doing in science for a long time.

The data out of the NIH show that in the 1980s, if you were 35, you actually had a chance of getting a large NIH grant. That was the median age of receiving your first large NIH grant: You were 35 years old. Now you're in your mid-40s. We tell young investigators, “You've got to do stuff.”

To be clear, mid-40s is super young. I just want to be clear about that: super young. I mean, I'm 57, so they all seem like babies to me. But the thing is, just as in Silicon Valley, the new ideas come from younger investigators.

I did a study a few years back where I looked at it, and it turns out that the age of the ideas in your published work ages by 1 year for every year of chronological age. My ideas get 1 year older every year that I age. The very best scientists fight like crazy to stop that. For Nobel Prize winners, their ideas in their papers age by 1 year for every 2 years of chronological age.

If you want the newest ideas, you have to let the young people have a try. We're just bad at that. We fund young people, and then they drop out and leave for other places. That wasn't true back in the '70s and '80s.

The culture of biomedicine says you have to have 1, 2, 3 postdocs before you have a shot at an assistant professor job. As a result, the ideas that we support are just older. That's not necessarily a bad thing. Of course, you should have some support in the portfolio 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. You have to diversify in that sense.

To solve that problem is hard. The NIH has been trying to solve this for 2 decades, and we've made no progress. First, let me give you some sense of where we've gone backwards. 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 challenges my 30 years of work. 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 got changed, so we no longer have that rule, but it's the mindset. 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 on whether every single grant succeeds, just like within Silicon Valley. I'm going to judge them on the portfolio as a whole: Does it translate into better health for the people with the diseases they're trying to address? Does it result in big advances in biological knowledge? I'm going to assess the portfolio as a whole.

And then the other thing is: Does it match the strategic vision of the institutes? They have these fantastic strategic plans. You go look at them, and your eyes will get big with the science that they're proposing, and yet what they actually end up funding based on the peer-review panels is often 10 great proposals on one part of the strategic plan and nothing on another part. I'm going to encourage them to pick the portfolio so that it matches the strategic plan.

I'm going to reward them for rewarding and empowering early-career investigators more. 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 they still play a fundamental role—but in how well they advance the careers of the early-career investigators who work with them. If they're good at that kind of mentorship and career advancement, I'm going to reward them in their grants. I'm going to start evaluating grants for that, too.

The grant portfolio has to be sustainable in the long run and produce new ideas. We need to do that, and if we don't have early investigators getting the 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 which they tend to come. 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—and decades of people behind us coming up—get trained on those grants today.

How can you work with the administration to ensure continuity for the training grants that NIH does believe are going to fuel the pipeline of early-career investigators who, as you say, are perhaps most likely to bring change, big ideas, and take big swings?

Yeah. As you know, you were in biophysics, right? We have a range of ways that we support early investigators. There are awards for predocs, meaning undergrads, and that's really important. We want to make sure that the very talented undergraduates who are interested in biomedicine and biomedical research have the support to do this.

There's also support for postdocs—for people getting their PhD and then doing postdocs. It's going to be hard, but we have to structure things so that the range of investments we make actually translates into people wanting to stay in biomedicine. We have a lot of people who drop out, but I think the main problem isn't support for early investigators. I think our portfolio is pretty good on that. We could do better, but it's pretty good.

The problem is, after you've had this career in biomedicine, how do you use this research training to make the next leap into an assistant professor job? Too often, it's too hard to do that. You can't get the support you need to do that. There are these K awards that we have, and 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 are problems all across the system, but I think that missing link is really this: You finish your MD and your PhD, and then can you get that assistant professor job, or are you going to be asked to do 17 different postdocs before 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 could get us back to improving?

Well, I think the key thing is that a lot of our science is—you know, this replication crisis 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 will address the scientific-rigor problem and the conservatism problem.

As far as addressing life expectancy, that really needs to be—it’s, in a sense, not just a scientific problem. We have to essentially get a message from the people that we want to serve that they want scientists to address those problems. That's just, as we talked about earlier, the political nature of that kind of allocation decision.

But that's exactly what the MAHA movement represents. The MAHA movement is 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.” That essentially is a call for the NIH to reform itself to address those problems.

To me, it's a tremendous opportunity. This is why I agreed to take this job. I was perfectly happy being a professor, but this is a once-in-a-lifetime opportunity to make the NIH really work for the American people. Having that political movement behind me—behind us—is really important for that.

Last week, you announced some really interesting initiatives around academic freedom, and many folks know your voice reached the national stage in part because of your ardent desire to see academic freedom respected and protected across the country. It sounds like you're looking for ways to improve publishing fundamentally so that people feel free at all levels, including early-career investigators, to share their views on science that they think might be interesting.

We need to figure out, to your point earlier, how to make the point that anything published is not necessarily fact, but is one opinion backed by one set of data, one set of analysis, and one set of perspectives. You'd like more of those to flourish in the public arena. Say more about the role that you want the NIH to play in protecting academic freedom.

Of course, at the NIH, I found out that a lot of the internal investigators had to seek permission from their supervisors in order to publish their work. I changed that. No more permission. If you're an NIH researcher and you have a scientific paper, you don't have to get permission from 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 universities need to be absolutely committed to academic freedom for excellent science to happen. There's been a lot of angst over the administration's actions with the universities over the last few months, regarding holding them to high standards regarding antisemitism and so on. But there's also been a mixed message that we really do want academic freedom at the universities. Scientists should be able to say what they think and explore where they will, or else they're not good environments for research.

As far as journals, that is a complicated question. The problem right now is that the scientific journals are essentially a duopoly: A very small number of for-profit companies control a very large number of journals, and they charge $10,000 per article for science that they didn't do, that the American people paid for. They actually had a policy where, if a regular person wanted to go find a scientific article, there was a paywall where they'd pay like $50 or $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, and we need more openness in scientific publishing. I'm working on policies to do that.

So, Jay, one of the key questions for the American public, if they're looking for better outcomes and better health, is that one of the big avenues this country uses—and has really had as a gold standard in the past—is having this extraordinary public-health infrastructure. But I think what's also true is that, over the course of the last several years, there's been a lot of mistrust now in terms of public health.

How do you rebuild that trust for the public? Obviously, if there's no trust, the message can only be so effective. 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? You just look at—you think back to the pandemic and remember the plexiglass that was everywhere. Every time I see plexiglass, it fills me with rage, but that’s another story. There was no science behind that, right? There was the—you wear a mask when you walk into a restaurant and take it off when you sit down; again, no science behind it.

A whole host of things, especially things like closing schools, where again the science was so weak, and yet now kids are years behind in their education as a result. They’ll be paying the price for that for years. A lot of the American people have lost trust in public health for reasons I can completely understand. The question then is, what can we do about it?

To me, the key thing is that there are 2 things that have to happen—2 very broad things. First, I think we have to restore gold-standard science. That presidential EO on gold-standard science is so important because it articulates things that we thought all scientists already knew and were committed to: replication is really important, unbiased peer review, humility in how we talk about the limitations of our scientific findings. There’s a whole host of things where you read it and go, “Wow, I thought science already did that.”

If we actually do that, I think that’s a major part of this. The second thing is, just like we talked about earlier, about the role of the people and politics in deciding what scientific priorities—what areas of science—to fund, and then scientists deciding what priorities within those science areas to fund in the portfolio analysis, we have to convey to people that we are their partners in scientific investigation and in public health.

Public health folks are servants of the people, and too often during the pandemic it came across like we were sitting above people, telling them what to do—telling them, “If you don’t take this vaccine, you can’t go to work. You can’t get a job.” It was heartbreaking to watch because I believe very fundamentally that when science works as a partner with people and has this almost servant attitude toward them, you can do a lot of good. You can do a lot of good.

I think that kind of humility and a return to gold-standard science—that’s the way to solve the problem of trust. It’s going to take a long time, though, because I’ve talked to so many people around the country, and we’re nowhere near solving that public-trust problem.

Yeah. I think it’s an especially challenging thing as you look forward, and I’d love to hear your thoughts on how you convey recommendations and guidance in the face of uncertainty and incomplete information. Going back to your point, in an ideal world you’re always resting on top of gold-standard science, but a lot of times there are a lot of unknowns in the science. Science is hard, going back to what you were saying earlier.

How do you communicate to a nervous populace a sense of a recommendation or even guidance in a world where you yourself have incomplete information?

I think you just have to be honest, right? So, if I were asked a question about—I mean, God forbid there’s another pandemic during my watch—and then I’m asked, “How should we manage this? Is it right to wear masks or something?” If there’s no good scientific evidence, I’m just going to say that.

The analogy I use is that I was a medical student once. I have an MD, so I can tell you this from firsthand experience. The first 2 years of medical school, you do a bunch of classwork. The third year, you finally get to see patients, right? You walk into a patient room wearing a white coat, and you know nothing or very little. You’re filled with knowledge about biochemistry; you can write chemical equations until your fingers get tired. But what you can’t do is understand what a patient really needs.

You sit down in front of the patient, and they tell you their story. It’s wonderful—they put their trust in you. You are tempted to tell them things to answer the questions they’re asking you, but you don’t know the answer. You just don’t, because you’re a third-year medical student. Of course you don’t know the answer.

There’s a temptation because you’re wearing the white coat and because you have someone looking at you, wanting the answer and putting their trust in you. You feel this urge to say things you don’t know. You start freelancing, and that’s just a terrible mistake. As a third-year medical student, you learn that you should just say, “I don’t know. I’m going to look it up. I’ll look up the answer for you. I’ll get back to you. I’ll consult with people who know more than I do.”

You have to be humble, especially in the face of new things—a new pandemic 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.” We have to convey that uncertainty, and we can’t blame the public.

I’ve gone around and talked to lots of folks in public health and science, and they’re like, “What we have to do is teach the public more about science and make sure they understand that science isn’t always perfect and that science moves. You may have eggs that are great one day and eggs that are terrible another day. That’s because we have new science.”

To me, that’s like blaming the public. It’s not that the public doesn’t understand that science is hard. They understand it fundamentally. Everyone knows within the public that 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 for the worse as a result of it during the pandemic.

So, I acknowledge that the pandemic was a particular challenge with respect to both communication and certainty amid uncertainty. But how do we acknowledge that challenge and not lose trust in some of the bedrocks of public-health advancements that we’ve made over the last several decades, whether that’s newborn vaccinations?

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, 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 and completely new infections, than there is in the context of something like Hep B.

Please don’t feel the 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 come out and say, “Hey, this is not perfect, but we’re pretty darn sure this is a good idea,” people don’t say, “Well, last time you said you didn’t know, so I don’t know”?

Right. 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—just take the MMR vaccine. If you want to prevent measles, take the MMR vaccine, and measles can be a deadly disease. I vaccinated my kids with MMR, and I was really happy I did.

I think that kind of certainty—it’s science, right? Nothing is known for certain. Tomorrow, someone might come along and overturn Newtonian physics, and all of a sudden you’re talking about relativity or something, right? You always leave open that possibility. But some things we do know with much more certainty.

I’m not saying that we should all have false humility. I think we should have humility for the things we should actually have humility about. At the same time, when we have an area of more scientific certainty, we have to leave room for academic freedom so that people who think differently can have their say. We don’t cancel them; we reason with them. We say, “Look, you say X, Y, or Z, but look at all this other evidence.” MMR is a good example. Look at the other evidence that shows you differently.

Then we’ll just have a public discussion. It’s okay to have that contradiction. When there is actual excellent, replicated science, maybe I’m naive, but I don’t think so—I think that wins scientific debates.

You can look at the evidence for this. The uptake of the MMR vaccine in this country is like 95%—95% of American parents vaccinate their kids with MMR. I think it’s like 13% of American parents 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, and allow people to disagree but then have the evidence right there in front of them, I think people will respond with trust where the evidence actually leads. Maybe that's just a matter of faith for me, but I don't see any other way forward.

You mentioned that the 3 priorities you have are nutrition, chronic disease, and integrating AI. Can you flesh out a little bit on the last 2—what you see as most promising in terms of reducing the disease burden, and then also in terms of integrating AI?

I've seen some fantastic new ideas regarding Alzheimer's disease. For instance, a colleague of mine at Stanford has a fantastic set of papers he published using an old shingles vaccine called Zostavax. He found, in excellent observational studies, that if you had Zostavax, it reduced the likelihood of developing cognitive decline or Alzheimer's disease by up to 20% or 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. Imagine if you had a very simple, cheap way to prevent 30% of Alzheimer's cases or delay Alzheimer's for years. There are all these huge advances I've seen that 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 on things that look like they're 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.

Everyone knows about protein folding and AlphaFold, which has done an amazing job turbocharging biomedical drug development. Now you don't need to sit there and wait—you can just do your computations, figure out how the protein folds and 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 biological lab work. You still have to do the lab work, but it focuses that lab work in more promising ways.

In the way that we deliver medicine, you can have AI systems help radiologists do a better job making sure they catch everything. Even simple things like this: you go to your doctor, and the doctor sits there looking at the computer the entire time rather than at you because they're filling out the electronic health record. Have an AI assistant listen to the conversation and fill out the form for the doctor, so they're just checking afterward—it takes them a couple of minutes—and they're spending all their attention on you.

All of this needs research, by the way. Does this help patients? We have to ask those questions. But to me, that's a tremendous promise. Those simple things can transform biomedical research and how patients are treated. That's why AI is so important to me as a potential tool.

We do need research. I don't want to have AI hallucinating on us and then treating patients based on hallucinations. But that's a matter of research to fix those kinds of problems.

We heard that HHS rolled out, across the agency, an enterprise-secure version of ChatGPT, which seems like a terrific achievement from the perspective of internal HHS and NIH operations—even being able to look up internally how new an idea is. Simple queries and that kind of data fluidity seem important. What's the future? Is AI going to write the institute's strategic roadmap, submit a grant, and have an AI review panel review the grant? Where are we going to play a role as scientists?

The answer is no. Yeah, I mean, I think AIs are really good at summarizing existing knowledge. The training data you give them helps; they're fantastic at that kind of thing. In terms of really developing brand-new ideas that challenge existing paradigms, I don't know about your experience with AIs, but they're not quite as good at that.

We just put a new policy in place where I'm limiting the number of new grant applications you can have to, like, 6 a year—6 a cycle or something. We have people writing 60 applications, and they're very clearly AI-generated, and it overwhelms the system with noise.

Yeah.

Yeah, so I mean, I think AI is really important. As I said, we have to do research to understand how it can be used to help people. I think scientists are still going to have a tremendously important role.

The new AI system rollout in NIH is exciting. We've actually been working on a new system, also specific to NIH, again to protect patient privacy and all that, but rolled out across the NIH so that people can interact with it in ways that help with NIH-specific tasks as well. 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 as scientists.

We do. If I could just end on 1 last question: if you had 1 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, and faster; 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; or a scientist at the NIH running a lab—what is your 1 message to the individual scientist who's out there hoping to make the biggest impact they can?

Science is incredible. It has almost limitless capacity to advance human well-being. It's the individual scientist who believes in their idea, who 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 on that door and change the world with it, because that's the only way scientists can do that. I love the story of Max Perutz. I don't know if you've heard of him. He was a University of Cambridge researcher in, I think, the 1950s, and he had this idea that he could figure out the structure of myoglobin, which sounds like a very geeky kind of thing.

But back then, there was no protein-folding field, really. 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 on this? You're never going to finish.” For a decade at the University of Cambridge, he wandered around, and everyone knew he was a genius, but he got nowhere. He just kept working at it until finally he figured it out, and it transformed a whole host of things in biomedicine. Eventually, he won the Nobel Prize.

It's the kind of thing where I ask myself: do we have a scientific infrastructure today that would allow a Max Perutz to do what he did back then? I would love to make that happen through the power of the NIH—to allow the Max Perutzes of the world, the new ones who are 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 talked about the NIH's highest ambition—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 how we manage patients, so the management of disease; 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, I'm a big believer in portfolios when I have uncertainty, so I don't know how to answer your question. I see promising advances in all 3 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.

Who would have predicted that the GLP-1s would actually result in a reduction in average body weight in this country—the first time in decades last year—because of a GIP/GLP-1 monster molecule that somehow turns out to, when you just do the right biology—

There was a scientist knocking on some kind of door to make that happen, right?

Yeah, I mean, that's the only thing about science: it's hard to predict where the best things are going to happen, and so you have to have a portfolio. But all of those areas to me look like they're very promising. As I've gone around the country and talked to people, I'm excited about all of it, so I can't wait to see what we produce.

Do either of you have a prediction to that question, or is it also, “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, that’s a great place to close. Dr., thank you so much for coming on the podcast.

Thank you.

Thank you so much for being here. Have a great day.