a16z Podcast - Uncontrolled Spread: Science, Policy, Institutions, Infrastructure

Episode Date: September 20, 2021

There's no question technology played a huge role in the recent/current pandemic, including especially in the plug-and-play engineering and incredibly fast development behind the mRNA vaccines... But is there an even bigger role for the private sector, not just government, to play (and partner) when it comes to key infrastructure for future such emergencies, and even beyond?Especially given how faulty the translation of institutional science to policy and public health measures turned out to be -- for instance, with "6 feet" of social distancing, or with fomite (vs. aerosol) transmission of COVID. And why are we still talking about the same, not specific, vaccine booster for the Delta variant? What can we learn about real-world evidence, other clinical trial approaches, and progressive (vs. binary) EUA approvals when it comes to public health emergencies? Are capabilities like genomic surveillance and mapping strains -- which require layers of technology, real time -- sitting in the right places?In this special book-launch episode of the a16z Podcast, former FDA commissioner Dr. Scott Gottlieb -- author of the upcoming new book, Uncontrolled Spread: Why COVID-19 Crushed Us, and How We Can Defeat the Next Pandemic -- shares insights on the above, and revealing stories from behind the scenes. Do we need a new entity to manage public health through a national security lens, and is the government capable? Gottlieb debates this and other probing questions from a16z co-founder Marc Andreessen (who famously wrote "It's time to build"); a16z bio general partner Vineeta Agarwala MD, Phd (who has spoken about the trials of clinical trials, practiced medicine during the pandemic, and more); and founding a16z bio general partner Vijay Pande PhD (who, among other things, founded the distributed computing project Folding@Home which pivoted to COVID proteins).One thing's for sure -- with this COVID crisis, we're at an inflection point between old and new technology -- whether it's in how we make vaccines, or how we apply the fields of synthetic biology and genetic epidemiology in public health response. So now's the time to look both backward, and forward, to really change things...

Hi, everyone. Welcome to the A6 and Z podcast. I'm Sonal, and I'm so glad for us to be back with the new episode. It's actually one of our special first look book launch episodes for the new book coming out this week by Dr. Scott Gottlieb, physician and former head of the U.S. Food and Drug Administration. He was a 23rd Commissioner. And his book is called Uncontrolled Spread by COVID-19 crushed us and how we can defeat the next pandemic. And that's exactly what we cover in this episode with special guest Mark Andreessen. who wrote the Call to Arms essay, It's Time to Build last spring. You can actually find a read a lot of that in this podcast feed. And we also have A6 and Z Bio-General partner, Dr. Vinita Agarwalah, who's also an adjunct clinical professor in the Division of Primary Care and Population Health at Stanford, as well as a practicing clinician and former operator

at tech-driven biocompanies. And you can find her past podcasts on vaccines, clinical trials, and more. And finally, we have A6 and Z Bio-General Partner, VJ Ponday, PhD, who's a former founder as well as a former professor of chemistry, structural biology, computer science at Stanford, and who founded the distributed computing project folding at home, which focused its resources on COVID protein sequencing. And you can find an episode about all that in this feed. In this episode, however, we touch on a wide range of topics

both about and going well beyond the pandemic, from health care to regulatory policy, to national security, and given our vantage point, we focus mainly on technology and science, as well as the role of the private sector. In the first third, we cover why there aren't boosters for Delta, specifically vaccines, clinical trials, challenged trials, and other debates about applying science in the real world and in an emergency, to discussing the role of genomic surveillance and what we need technologically and operationally, to the role of government institutions in handling the pandemic and the translation between institutional science to policy. So basically going from technology and science to policy

and institutions and infrastructure, both looking back and forward, weaving recommendations throughout, as is the premise of this book. The first voice you'll hear is Vinitas and Scots, followed by VJ's and then Marks. Scott, we're all bullish on the programmability of RNA vaccines, yet more than a year and a half

after our first human doses of the COVID vaccine with multiple new variants. we're still talking about the same vaccine as a booster. Do you have any insight into why even the annual iteration that we had ironed out with the influenza vaccine was not a priority or possible in the context of mRNA vaccines? Well, it certainly is. One of the reasons why you can potentially rely on smaller complements of clinical data in the context of an MRI vaccine as opposed to vaccines developed through traditional methods

is that the manufacturing process can be plug and play. It should be even easier than with the influenza. Right. What you're really just optimizing for is does the new sequence code for a protein that's going to elicit the right immune response? You're not as concerned that there's going to be variability in manufacturing process that can change the vaccine. With a flu vaccine, as you move from vaccine to vaccine, the sequence has to undergo egg

adaptation because the vaccines are manufactured and eggs. And so that can introduce some changes in the protein that then have some clinical consequences. I think to sort of get at the heart of what I think you're called. question is here. Well, so yes, if it's easier, why don't we do it at the beginning of this year? Right. Why don't we have a new variant vaccine? The delta spike mRNA sequence. Right. So I think the answer is that to some respects, you take the bird in the hand. We know that the current vaccine, we know it's effective against Delta. We know with a third booster, it seems to improve the effectiveness substantially against Delta. We also know that

it works well against the Wuhan strain. We know it works well against 117. We understand how well it works against 1351. You know, we know that it doesn't work quite as well against Lambda and Mu. I mean, we have a wealth of data around this vaccine. If you move to a Delta variant vaccine, theoretically, maybe you'd be able to gain a little bit of efficacy against Delta, but what would happen to the efficacy of the vaccine against everything else? We don't know the answer to that question.

And so you don't want to pivot to a new vaccine when you know that with the existing vaccine, you have pretty good efficacy against the full complement of strains that we've seen. and you also have good efficacy against Delta. Now, if you're thinking about the future, about what will the next strain be that threatens humanity, there's a potentially you get a strain that's more transmissible than Delta, although Delta is so transmissible. It's going to be hard for this virus to achieve higher levels of contagion.

If you sort of look at the landscape right now, this virus has raced around the world, and you haven't seen it really figure out a way to dramatically evade our existing immune response. And that may be because the same features that the spike protein uses to attach to our ACE2 receptors in our lung are also the same features that our immune system generates antibodies against. But the bigger concern is that you get a strain that has partial immune escape. We're going to be at really high levels of immunity after this delta wave sweeps through. And the worry is that a variant emerges that can partially evade that immunity that the population is acquired. The thinking is that it's probably going to emerge within the delta lineage.

it's going to be a breakoff and it's going to have some different characteristic. If that's the theoretical possibility, then it would argue in favor of using Delta as the backbone for potential future vaccines. But I don't think we're there yet. I don't think this is a problem for November and December. I think this is a problem for 2022, maybe 2023. Scott, I'm curious to follow up in the future when this is sort of more tested. We could move faster. The fantasy is that let's say the delivery vehicle is well tested, but we want to make a tweak in the sequence, and especially maybe a small one. Maybe that could be a very small trial, but how small a trial? What do you think the expectations are going to be and what are people going to look for?

Yeah, I suspect that Pfizer and Moderna both may well end up developing vaccines to have in their back pocket that are based on the Delta variant. But the licensure of those subsequent vaccines based on new variants isn't going to require 45,000 patient outcome studies. again, FDA is going to move to an approach where you have some clinical data. You want to see the performance of the vaccine in people, but maybe it's a small non-inferiority trial. And then you supplement that with immunogenicity data, where you can basically say the new vaccine stimulates antibodies at a similar level to the old vaccine. And we have all this in vitro data showing that those antibodies neutralize the virus. And so you're now substituting all that different

kind of data in that lets you get to an answer much more quickly, much more efficiently. That's not unlike flu vaccines. Each year, we develop a new flu vaccine against a new strain of circulating flu. We don't do clinical studies with that vaccine. We basically rely on in vitro studies to show that generates an immune response and those antibodies can neutralize the virus. So it's more of a laboratory demonstration of efficacy than a demonstration of efficacy in humans. I think that the questions that you're going to need to answer going forward, are going to be around, does the protein that's being delivered by the MRNA? Does it stimulate a robust immune response?

Are you looking at immunogenicity? Does the protein that you're delivering itself trigger an immune reaction that could cause side effects? So you're going to still want to answer those questions with the next novel pathogen. But answering those questions can be done in the context of much different clinical trial constructs. You can do large simple safety studies and not have a large randomized population. You can use serology data.

antibody response as a correlate as a surrogate for clinical response. If it's a highly novel virus, you're still going to want some complement of outcomes data. So I'll pause here. Are we looking for demonstrating efficacy in the trial for small changes or purely making sure that it doesn't have issues with talks? The question here is what should the sort of thresholds for testing be in terms of efficacy and in terms of toxicity? For example, in a pandemic, if we had confidence that something was not going to be harmful, what type of statistics would we want to see initially to give us confidence that we could use real-world evidence

to be able to decide? Normally, we wouldn't do this for something like a drug because we want to be careful, but in an emergency, when do we turn to world-world move more quickly? The emergence use authorization, which was originally derived in Project Bioshield, it was sort of post-9-11 legislation on how to create a pathway for the rapid regulatory authorization,

rapid access to therapeutics that would be used as countermeasures for a bioterrorist attack. It was eventually evolved to also scope in the risks associated with a pandemic under the Pandemic All Hazards Preparedness Act. The construct gives a lot of flexibility to the FDA to make decisions about enabling early access to therapeutics based on different kinds of evidence, including real world evidence, in the setting of a public health emergency, where we didn't really envision it, perhaps properly or expansively, was that we still looked at the EUA process as a quasi-approval process. It was either authorized or it wasn't. The vaccine's the

best example. Once the vaccine got an emergency use authorization, it was available for everyone from 16 to 100. You could have said, you know what, we're going to do an early interim analysis based on a smaller complement of data. And if it's safe and effective, we're going to authorize it, but just for people who live in congregate settings over the age of 65. Because at the point in the wintertime, we were losing 7,000 people a week in nursing homes. That's where the extreme death and disease was. And if the trials progress and we have more data now from using the vaccine in a real world setting and we don't identify any additional issues, then we'll authorize it for another population.

Yeah. Well, I mean, put in the sort of sense of lessons learned for the next one, that actually could be a huge advantage for the next time where you have to do what's something like this. The authorities there, if you read the statute and how it's been implemented, the FDA has the discretion. I think what doesn't exist is the clear expression from Congress that that's how Congress intended for this to be potentially used. There was a lot of pushback to taking the interim analysis with the vaccine trial. And ultimately, the FDA moved towards a posture where they required the full data set and two months of follow-up on 50% of the patients in the clinical

trial before they would authorize the vaccines. If we didn't think of using that authority to introduce these products in a titrated fashion, we still looked at it as a binary, like we look at a normal approval process. That's one of the lessons from this, that these authorities give us the flexibility to introduce products in a much more progressive fashion based on where the risk is occurring. And that's not how we implemented them. I think that that might have been a shortcoming. I mean, it's interesting to step back.

let's say it's not something like COVID, but it's the next HIV, where it's maybe not as threatening of the full population, but still very serious. It would be interesting to think about how we discern the sort of threat level versus how fast we can move. These, of course, are complicated questions mixing both science and policy. Arguably, HIV, when it emerged, was a public health emergency. It was a global pandemic, and I think it required these kinds of emergency-style interventions. But, you know, you take another disease. From a policy standpoint, the more that we say, this is what we would do in a pandemic, that work well. Let's import that into more routine approvals. The more that it's going to be harder to implement them in the

setting of the emergency, because it's going to make people who are against expedited approvals nervous about implementing it here for fear that it's going to get imported there. So I think the more that we narrowly define the emergency and then we keep the authorities circumscribed to the emergency, the more that we're going to be able to achieve more in that realm. It's a really interesting idea of keeping the EUAs even more narrow and potentially targeted at more narrow populations on the basis of a hyperlocal or subpopulation-specific risk benefit analysis. Does that hypothetically mean that we should have considered an earlier EUA, to VJ's point, let's say targeted at nursing home residents in Missouri? Is something like that

a construct that exists from a regulatory standpoint? Yeah, in the FDA construct, you don't approve a vaccine for people who live in Missouri. You don't approve a vaccine for people who live in multi-generational homes. Yeah, but yet the risk of COVID is fundamentally different. Right, exactly. You approve medical products based on clinical criteria. Those are social constructs, where you live, how you live. But under the emergency use authorization, you could conceive of that.

There's a way to go from the social construct to the clinical construct that would allow regulators to do that kind of an authorization. You could have took some interim analyses. It made an earlier authorization for a subgroup of people who were experiencing the worst COVID outcomes. We tried everything and we still couldn't keep COVID out of the nursing homes. And so the only tool that was going to intervene on that was the vaccine. So you could have defined that population as a population that's being disproportionately and heavily impacted by COVID. Next time, it could be a pandemic strain of flu that disproportionately impacts young children. I mean, typically pandemic influenza's disproportionately impacted very young.

So we need to think about how we make authorizations based on where communities are being very heavily impacted and not just think of an ordinary approval. It's binary. It's just approval light. And who knows, this time around a bunch of studies we're done, you know, to look for germline risk factors and people's genomes and, you know, host factors and biological factors. So maybe a future EUA and a future pandemic, we actually have the opportunity to really granularly identify who's at risk.

Yeah. It is amazing. The technologies that we have, it's breathtaking, you know, the MRI technology and their effectiveness and the speed with which they were developed for people who don't know. At least the Moderna vaccine, the story goes, was actually developed in two days in January, 2020 based on having the genetic sequence for the virus. Without even a last sample of the virus, just the genetic sequence. It took about what another, took 11 or 12 months to kind of start to get put in arms.

But there's this technique for testing vaccines called challenge trials. You know, had we done challenge trials, you know, with volunteer subjects, we potentially could have had the vaccine rolled out six months sooner. And so in theory, we could have had the vaccine out in the summer of 2020. And maybe we could have saved hundreds of thousands of lives. A challenge trial, you know, is a controversial concept because it is a trial in which participants would be intentionally challenged with the infectious pathogen in order to accelerate our knowledge of a vaccine efficacy in the context of an artificial introduction

of the pathogen. In this case, a challenge trial of COVID would mean giving somebody COVID as part of the trial, not waiting for them to get it in the community. So on that next time around, should we do the challenge trials and take on kind of the consequences that that implies? So there's two streams of debate here. One is the ethics of doing challenge trials and then just the other is the practical implications and the benefits of doing the challenge trials. On the ethics, the vigorous debate is around the issue of, is it ethical to expose someone to a virus that is potentially deadly, even in a younger person or inflicts a lot of morbidity that you have no therapeutic for. Remember, we would have been doing these challenge

trials early in the course of the pandemic when we didn't even know that steroids were effective at preventing severe disease. We didn't have any effective therapeutic. So there was the ethical debate around that. Then there was the practicality of it. And what I saw, I'm on the board of Pfizer, so I was watching this process very closely, was that the debate around challenges trials was going on. And before it got settled, we had already advanced so far with the vaccines that it kind of made the challenged trials not relevant anymore because we already had clinical data. And that's in part because the trials enrolled very quickly. The trials read out very quickly because people were motivated to get into them. There was a lot of disease around. So people who

were being vaccinated in the early trials were being exposed to a lot of infection. We did probably some of the largest and maybe the largest outcome studies ever undertaken in the history of modern drug development. Each trial, the Pfizer and the Moderna trial, each trial was about 45,000 patients. The largest vaccine trial I remember from being at FDA was the rotavirus. I think it was around 60,000 patients. If you combine the Pfizer and Moderna trial and look at 90,000 patients that were enrolled collectively across those two trials, it was the largest clinical development enterprise ever taken for developing a drug. There have been some cardiovascular drug studies that enrolled tens of thousands of patients, but oftentimes not all the patients are randomized.

And we got full-blown outcome studies across a broad age continuum, across a diverse population. So I don't think that the challenge studies would have obviated those outcome studies. We still would have wanted to see the performance of the vaccine in a large population. Now, in terms of should we consider challenge studies in the future, I think future drug development in these settings could look very different because we were at a technological inflection point with COVID. But if COVID had happened three years ago, we would have taken the coronavirus, SARS-CoV-2, we would have grown it in cell cultures, we would have figured out a culture that it could grow in, grow it up, we would have inactivated it, we would have cleaved off its proteins,

we would use those proteins to basically formulate a vaccine. If COVID happened three years from now, I think these MRNA fully synthetic approaches where you're developing a vaccine entirely from the genomic sequence of the virus, and you don't even need the live virus, might have been mainstream. In fact, the reason why Pfizer was able to pivot so quickly was that they were trying to use this platform to develop a flu vaccine. They basically pivoted that program. But we were right at the inflection point of that.

Going forward, if the MRNA platform could be applicable across a whole range of viruses, then it just becomes a question of developing a genomic sequence that codes for a protein that's going to give an effective immune response. And so I don't know that we're going to need challenge studies. And I don't know that we're going to need to even go through the same development process we went through here because we're going to have such a deeper understanding of using MRNA as a platform. That really chewed me up.

I'm glad we didn't do challenge trials. As you said, Scott, we did get a lot of natural cases as part of this massive clinical development effort of a novel therapy. The future versus the past is an interesting question here because we did not know the absolute vaccine efficacy would be so high. And so imagine what would have happened in terms of public trust and faith. If that efficacy number had even looked more like an influenza vaccine, gosh, I'm thankful we got to see a high efficacy without taking that kind of risk. But on a go forward basis,

maybe we learn all about the preclinical to clinical correlations. We learn what type of data you have to see in the in vitro setting to make all those correlations and predict with higher fidelity what the in vivo efficacy is going to be. Maybe there's a role for challenge trials in the future once we have a better handle on the modality. It's interesting that our time in history determines a lot about how we respond to a pandemic. Admittedly, we still took a big hit, but we made it through globally with technology and software as well as enterprise companies in every aspect of our lives.

And so it's sort of interesting to think about whether that should explicitly factor in to a future pandemic preparedness plan, recognizing that different people have different access. But nonetheless, it's a dramatic difference that was on display during a pandemic in 2020 that would just not have been possible even 10 years ago. In your book, you mentioned that genomic surveillance helps us for a potential next one. There's just been so much interesting scientific literature on how to do this efficiently. And to some extent, it's happened in pockets all over the country. You know, the group at Fred Hatch contributed greatly to this dialogue. So did a team in our backyard at UCSC doing some great work. We've sort of been doing it in academia versus the

public sector or the private sector even. So I'm curious, what does that genomic surveillance look like in a future pandemic preparedness? Yeah, and I'll just sort of preface my answer by reminding listeners that my other board role in addition to Pfizer's, Illumina, which is one of the companies that makes sequencing machines that's used by a lot of laboratories here and abroad. When I talk about this movement towards synthetic biology, really the bigger inflection point is in the use of genomics to drive a public health response. That's really the inflection point that we've crossed with COVID. And that obviously translates into the ability to derive therapeutics using sequence data. Not just the vaccines, the antibody drugs were also informed and powered by the

ability to look at sequence data, but it's also the use of genomics to drive an augmented the traditional tools of epidemiology. This field of gen epi, of genetic epidemiology, really didn't exist before COVID. I mean, there were people like Trevor Bedford doing this work, but it was never done at scale in response to a public health crisis. Genetic epidemiology has been used by FDA to track outbreaks of foodborne infection, but it's never been used at this kind of a scale. The only place that you saw genetic epidemiology used at any scale to help inform the response to an outbreak or an epidemic was in the context of Ebola in West Africa. So there's two basic opportunities enabled by this.

One is the ability to detect early that B117 is more contagious and is out-competing the Wuhan variant. By collecting phenotypic data and sequencing populations at scale, you can know when a new viral lineage has introduced some new features to the virus that's going to threaten us in some different way. And the other opportunity that it enables, or the big umbrella opportunity, because there's a lot of opportunities it enables, is the ability to track the spread of individual variants or individual introductions of the virus to understand how the virus is

spreading, and that allows you to target your public health interventions much better. Early on, there was, I talk about this in the book, there was an effort by Deborah Burks at the White House to get the CDC to fund a large-scale sequencing effort in a single state. And the thinking was that if you could sequence its scale within a state, you know, a state that has a diversity of geographic apartment, small. communities, rural communities, small cities, bigger cities, you can sort of ascertain, was it going from rural communities into the big cities or is it going from the big cities out into rural communities? And that can then inform where you're going to try to break off change of

transmissions. Those are the kinds of opportunities that being able to sequence a population that scale enables. Yeah. In your book, you give a great example of tracking down the Rose Garden strain and learning that likely it was circulating in parts of the country domestically. It's not like a completely new entrant based on other sequencing data, but that wouldn't have been possible in real time without this type of infrastructure. So it seems like we need a national effort, not even statewide, but that it would have to be at scale a centralized data repository, centralized algorithmic approach.

The data aggregation, I think, should be centralized and open source. And that's essentially what has evolved. We've layered the collection of sequence data onto the system that we originally developed for collecting influenza sequences. Never envisioned to be operated at this scale, but it's been able to be adapted. But I think the actual collection and the sequencing of samples needs to be more of a federated model. It can't be you ship your samples to CDC and they do the sequencing. You need to rely on private and public labs distributed around a country that get contracted to do this work. You're suggesting that testing be done in a federated manner,

orchestrated by local communities. I think it's interesting to think about all the layers required to do genomic surveillance right. The complexity and depth of the genomic surveillance, you know, matters in some sense. As you mentioned, we've been doing genomic surveillance of influenza strains for many years. Food surveillance, you mentioned is a great example, but the readout is fairly simple. Binarily, you know, is the food infected with a pathogen or not? Even influenza, you read out the strain, put it into that year's vaccines, but we're not using it in the context of a rapidly spreading pathogen. If you look at COVID, it's quite another thing to be continuously mapping the evolution of the strains in real time to place trees on a complex origin

and subsequently informed contact tracing efforts, that's hard at a whole new level. It struck me that you actually need a lot of, you know, capability algorithmically from a compute perspective, from a data storage and analysis perspective. And I think we've learned a lot during this pandemic about what those bioinformatic technologies look like. Basically, you argue that genomic surveillance is something we achieve. in the book and that it's something we'll be able to take forward. And what I'm proposing is that maybe we only got to really skim the surface of that. And the real genomic surveillance technology

is actually sitting in the wrong places still. Yeah, look, I think genomic surveillance is something that we operationalize in the context of the response on the fly. I don't think that we've institutionalized it. I don't think that we've built the infrastructure to do this on a routine basis at scale. But we've demonstrated the use case. That's sometimes the most important thing, right? And I think that there's a consensus that this is important. And then the question just becomes how to operationalize it. How much does this fall into sort of parochial fighting that, you know, CDC wants to maintain control of this and academic centers want to have some hand in this in the public health labs? And that's what's going to need to get sorted out. There was a point in time where there was a lot

of sequencing work going on in the U.S. But CDC was only reporting a very small number of sequences being derived each week. And people asked why, and I talk about this. And the answer was because CDC wouldn't recognize the sequences that were being done in a lot of academic and commercial labs because they weren't being done according to CDC's protocol. CDC hadn't done the sequencing. CDC hadn't overseen the sequencing, so they wouldn't recognize it. They were substantially underreporting it. So if you wanted to actually aggregate how many samples of B117 were being unearthed each week, you had to actually go to different sites and add them up. And I was doing this at the time.

You couldn't just go to the CDC webpage and see their reporting. So you're going to need to solve for that, too. How do we develop a sort of federated model where we recognize the work going on in a lot of different labs and resource them to do it and allow then all that information to be pooled in a way that you can read across it? So I'd like to open the door on a topic that I've been thinking about a lot. Scott, we all watch you on TV all year, especially for 2020 with all of these great ideas of all the things that we should do and the quote unquote, we met the country, the government,

states, the cities. And very few of those things actually happened. I have a long list of things that people talked about that didn't happen. I'm sure you have a long list of things that people talked about that didn't happen. Starting out with closing down flights from China, extending through to test trace, isolate, you know, broad-based serological surveys. So the question is, what have you learned about the ability of the American government at its various levels and across parties to actually execute?

And then the second question, which is your recommendations of what we should do if and when we go through this kind of thing again. Look, I think some of the challenges with operationalizing certain aspects of this response was that we just couldn't galvanize collective action. in time. Some of them got scooped up in divisions along political considerations. But I think the challenges that you cite are mostly operational. And there wasn't really a lot of debate over some of those aspects of the response. We just were never able to implement them. So testing and tracing is a perfect example. There was some opposition to the idea of doing wide scale, contact

tracing, a perception that it would sort of morph into what you saw in South Korea, where you saw more intrusive elements where people were tracked electronically and put into what amounted to forced quarantine situations. But we didn't need to go that far with contact tracing here in the U.S. We could have just done contact tracing light, if you will, even if we could have done limited contact tracing. We could have reduced the scope of the epidemic at the outset. And even after we had the national shutdown, the perception always was that you would implement the testing, the tracing, the tracking as a way to control the epidemic once you lift the pandemic. the population-wide mitigation. But once again, we still didn't have the testing in place.

So we implemented these onerous, costly measures to sort of buy ourselves some time. And then we didn't use the time effectively to get the kinds of tools in place that we needed to pivot to a different posture. You've probably seen the movie Contagion. I rewatched it recently to see how realistic it was relative to what we're going through. It actually captured a lot of the challenges pretty accurately. So for people who haven't seen it, this is a movie, Stephen Soderberg movie from about, I think, a decade ago, about a respiratory pandemic, and it's a very chilling movie. But, you know,

there's sort of an assumption in the movie, which basically is that the CDC, sort of on behalf of the United States federal government, is this incredibly competent organization that basically is coiled like a snake, ready to strike at the moment of pandemic and basically take control of the country and, like, you know, implement all kinds of public health measures. It's like an instrument of state power. It's an execution machine. And I think that reflects a general assumption that people have had for a long time, which is this is the function of these federal agencies. Did that movie just have like an unnaturally high expectation for what the government should be able to do? And I bring that up not just because the movie, because I think that's what a

lot of us thought the government was going to be able to do. And then like, are you as shocked as I was at the delta between that and then sort of what happened in reality in terms of ability to execute? Well, look, I'm not surprised that the CDC didn't have the ability to execute a national scale response to a crisis of this magnitude. What I'm surprised at is that we didn't organize the entity capable of doing that. And the entity capable of doing that was always going to be some hybrid organization that got created to deal with this particular crisis. The CDC just isn't capable of doing that. It's a high science organization. It's very retrospective. It does careful analyses to sort of be the final word on a question, not the first word on the question.

And in crisis, you need an organization capable of pumping out information, even if it's only partially accurate that's going to inform decisions that have to get made anyway and will get made in the absence of any information at all if you can't surface it. So you need a more battlefield mindset. What needed to happen with the initial response was to marry the high science capabilities and a regulatory responsibilities of an organization like FDA with an organization like the Defense Department that had the capacity to scale up manufacturing and scale up distribution. You really needed to create a hybrid organization, which is what Operation Warp Speed was. It married a logistics capability with the science and public health capability to inform that.

If you were president at that time, would you have rolled out? the National Guard nationwide to implement, to trace isolate quarantine, so forth and so on. You know, you didn't need sort of a military force or a police force to implement anything to get compliance. What you needed was a capability to actually develop the tools to achieve that purpose. What ended up happening was this highly sequential process. It would have worked that this was a slow-moving infection, but it was no match for a fast-moving pandemic. And I think to your first point, it was in part a reflection of a belief that CDC's got this. There was this perception that CDC would develop a diagnostic test and they would deploy it to the public health

departments. The public health department would start using it for testing. And then eventually in this highly sequential fashion, the clinical laboratories and the academic laboratories would develop their own homebrew tests and they would deploy those. And then eventually the major manufacturers, if there was still need for testing, would develop kits and those would get deployed to the commercial labs. In retrospect, CDC has never developed a diagnostic test and deployed it to anything but the public health labs. The flu tests they develop each year, they sent to the public health labs. Commercial manufacturers supply the commercial market. And the 100 public health labs in this country can each process about 100 samples a day on average. So you're talking about a capacity of 10,000

tests a day that could have been achieved by the public health labs, even if CDC had rolled out their test on time. We needed to be conducting a million tests a day, not 10,000 day. And And so even if CDC was successful, even if everything had worked, you were never going to have the capacity in the market that you needed at the outset to try to control spread and not have to reach for population-wide measures. The reason we had to implement the nationwide mitigation is because we had really no idea where there was spread and where there wasn't. And so we ended up implementing a national stay-at-home order when in actuality, if we had testing in place, we could have said, you know, New York really needs to implement a stay-at-home order. New Orleans does, but Austin doesn't. And that would have preserved the political capital that local officials needed once the spread did arrive in those parts of the country. But what happened was everyone shut down. And then when the spread eventually emerged there, people said,

you know what, we did it when you told us we had to. We didn't have to. We're not going to shut down again. And so you ended up spending the card right up front unnecessarily. So on that exact point, there's a spectrum of different kind of responses from governments. I know we've seen this around the world. On the one hand, you had the sort of extremely draconian responses. You have high-state capacity to be able to do all the stuff that you just said. On the other hand, you've got this equally radical laissez-faire kind of idea, which was just, look, let it rip through the population, rip off the band-aid, as it were, like take the losses. And of course, that's a very brutal thing to say, but, you know, basically get through it.

But my analysis is we could neither do the draconian controls on the one hand. We also couldn't do let it rip on the other hand. And so somehow we therefore ended up in the messy middle and has resulted in, you could argue, the worst of both worlds. the messy middle has still resulted in and controlled spread, and the messy middle has led to all of this disruption, which, by the way, continues, right? Like, we may only be halfway through this today with just enormous societal and political and economic disruption and devastation and people continuing to die. And so, is the messy middle of the right place to end up? Or if we knew we were

going to end up here, I guess, if we knew we couldn't execute the more draconian measures, did that actually have more merit than it appeared at the time? And should we have just considered an approach that just said, let it rip? Yeah, look, I think the one thing that we've learned from is that a respiratory pathogen, a novel respiratory pathogen, poses an asymmetric risk to Western democracies, that we are uniquely vulnerable to this for a whole host of reasons, open societies, inability to really galvanize collective action, get a population to comply with public health measures in a uniform way, a large country with a lot of regional variation, all the things have made us uniquely vulnerable to it. In respect to the genesis of the

tactics that we ultimately adopted here. It was pandemic planning done around each five and one. So we adopted a very flu-based plan in response to COVID. The arguments against the population-wide mitigation at the time, and D.A. Henderson, the famed public health official who helped eradicate smallpox, was one of the most vocal critics of mitigation. And his arguments at the time were that you're basically just going to prolong the agony, that you're going to implement measures, you're going to close schools, you're going to close businesses, it's going to have a devastating economic impact, so you're going to sort of compound the impact of the pandemic, and you're not going to prevent the spread anyway, that eventually everyone's going to get infected.

The arguments for the mitigation was that if you could reduce the peak number of cases at any one point in time, you can preserve the capacity of health care system. And D.A. Henderson's argument against it was that uncontrolled spread was inevitable, and you were just going to inflict more difficulty on society. I think that that is 2005 thinking. I think in 2020 thinking, there is a logic to trying to control the spread, reduce the number of cases, hold back the pandemic as long as possible, and that is because we now have the ability to pivot very quickly at technology. Back in 2005, we never could have envisioned having a vaccine to a novel virus as quickly as we were able to COVID. So I think the fact that we have the

potential to pivot so quickly at technology that could help not just thwart the pandemic, but potentially end it, is a stronger argument for. to try to control the spread. The problem is you can't tell the virus where to go. You're not going to be able to keep a senior citizen or immunocompromised individual who has to go into a pharmacy from catching it in that venue if there's a lot of virus around. So the only way really to protect the vulnerable populations is to reduce the prevalence. And so that's ultimately what we tried to do with obviously mixed results. Yeah. So Scott, from a science standpoint, you look at a lot of the science similar to this role to policy and then be curious, like, what have you learned about the

institutional kind of science that we do in this country and then it's translation through to public health measures? What surprised you, if anything, versus kind of the way that you thought science worked and the way science would contribute to this kind of problem? Yeah, we benefit greatly in this country from a very distributed model of scientific inquiry where individual investigators, private manufacturers are free to conduct studies, generate science, do research, to answer questions that they think are relevant. And that creates a competition of ideas that I think benefits us greatly. You know, it's a diverse environment for the development of scientific information. That doesn't work so well in a national emergency when you need to get to answers

very quickly and speed matters as much as the breadth of the scientific inquiry that's going on. And we saw this with the evaluation of drugs for the treatment of COVID. We probably enrolled over 100 studies to examine hydroxychloroquine. We should have really only had one definitive study enrolled at the outset to examine that. And then we couldn't enroll the studies to evaluate the therapeutic antibodies developed by Regeneron Lilly, which were delayed coming onto the market, because nobody wanted to enroll in a randomized placebo control study when they could enroll in an open label study with hydroxychloricor and some other drug. So you needed to have some organizational structure around this in the setting of a pandemic where you said,

we're going to enroll these studies, because these are the highest priority questions to answer. The British did that with recovery. And in fact, many of the most important answers around what therapies worked and didn't work early on actually came from that single British study. We didn't do that here. We enrolled literally hundreds of studies, most of which were never going to yield definitive answers about the therapeutics they were examining because they weren't designed appropriately. So then let me brush that to kind of this intersection of sort of science and public policy. I'll pick on two things in particular. So social distancing in the form of six foot separation. When that first came out, I was like, oh, that's

interesting. Where did they get the six feet from? And if you dig into that, what you find is the six feet thing was from a droplet spread study done, I think, at MIT on the order of 100 years ago with state-of-air scientific equipment that they had 100 years ago. It shows when you sneeze or cough, droplets go six feet. You know, there are two kind of big issues with that for COVID. One is when MIT re-ran that study last year with modern imaging technologies, they discovered that droplets actually traveled 25 feet. And so if you want effective social distancing with droplets, you need 25 feet, not six feet. And then, of course, there's the other thing, which is we discovered spring of 2020, we knew that COVID was no longer just droplet-based transmission. It was airborne.

And so it spreads through circulating air. And so it doesn't need droplet spread for the virus to spread. But yet, all over the country, there's still the little footprints on the sidewalks everywhere. There's still all the separators. There's still all the stools from bars and restaurants, keep people six feet apart. You know, the other one is a fomite or touch-based transmission. You know, there was early concern that COVID would spread through touch. And then it was relatively quickly kind of realized that that wasn't a real threat.

You know, you need to get a viral load in the nose and throat and you're not to get a bite by, you know, to touch of your face. And yet, I can tell you, we have schools all over the Bay Area still cleaning every week for basically no reason. It seems to me like something is fundamentally broken in the transmission belt between even high quality scientific research and then implementation through public health and into policy. Would you agree with that or is that too dark of a conclusion? Or if you agree with that, what do you take that? No, I don't think it's too dark of a conclusion. I think it's an accurate conclusion. The six foot recommendation is probably a really good touchstone to sort of examine what you're talking about.

That was the single, I think, the single costliest piece of guidance that CDC issued. The six-foot requirement was the reason many school districts couldn't open because they didn't have physical infrastructure to allow six feet of separation in a classroom. Therefore, they had to go to hybrid learning or fully remote learning. And as you said, it wasn't based on any really profound analysis. It was based on some old studies around droplet transmission in the setting of influenza. When CDC issued that guidance, they didn't explain what. the evidentiary base was. So here you have guidance to the entire country that we're following

that is having a tremendous social and economic impact. And the guidance doesn't even fully explain how they drive it so that people can make informed decisions and some people could choose to ignore it. It didn't get re-adjudicated in a timely fashion. It finally got re-adjudicated March of this year when we recognized from a policy standpoint that it was going to force a lot of schools to remain shut in the spring. So CDC went back and reevaluated it. It's science and decided that there was a study that it had done in the fall, so six months earlier, where they looked at spread between two masked individuals and they found that if you have two people with masks on, they can be three feet apart and still you get a 70% reduction in the risk

of transmission, if I remember those numbers correctly. So it begs the question, if this study was the basis of the CDC revising their guidance in the spring, why didn't they revise the guidance in the fall when this study first came out? And then the initial implementation of the six-foot requirement, It actually wasn't six feet. It was 10 feet. And I talk about the book as well. The CDC came to the White House. This is back in the beginning with a recommendation that they wanted to have 10 feet of physical distance as the recommendation. And OMB, the Office of Management and Budget, said that's impossible. Nobody can measure 10 feet. There's no way to achieve it in any practical fashion. But 10 feet was arbitrary and not poorly informed. And so there was this debate between the policy people and the office management and budget, both career and political and CDC and CDC ultimately settled on. six feet. So that is a perfect sort of window into some of the challenges we had. In these settings, you're making imperfect decisions. And so I don't think you can fault the agency for putting out guidance based on what was available to it at the time. But then you need to collect new evidence. You need to test it. You need to assess what impact it's having. Is it having an inordinate

social impact or whatever potential measure of protection you're achieving? Once it got enshrined in guidance, it became doctrine. And then it was impossible. to re-adjudicate it. I'd love for us to collectively learn to Mark's question about what can the government really do in the future well in the vein of what your book recommends. So given all these constraints in our system, do you think there's a more proactive public-private partnership strategy that we should think about implementing in a preparedness plan? It's got to be a model that leverages the private sector and leverages some of the installed base. I think we need to have the blueprint for how we mobilize a response at this scale.

Early on, you needed to turn immediately to the major manufacturers in this country. And this is what South Korea did at the outset. You needed to get all the major manufacturers together at some point in January, starting that process right away of developing the diagnostics, the platforms that were needed.

And we didn't have a lack of capacity of testing around the country. We lacked the ability to bring it all together in a coordinated fashion and properly resource it to withstand the demand of a pandemic. But we had enough Roche machines to run PCR. We didn't have enough swabs to collect the samples, and we didn't have enough sites to run patients through.

So I think the national plan needs to be how do we fully leverage the infrastructure we have? And then part of that's also how do we make sure that we have the right infrastructure? How do we keep a bigger hot base of capacity available in the event that you? you have a crisis. And I talk in the book about the idea that in the future, maybe what we need to do is in the context of just testing, the large commercial labs operate for maximum efficiency. A high complexity lab might have 3,000 machines that are running at 80% capacity. Maybe what we should really have is 5,000 machines running at 50% capacity or 60% capacity. So you have more reserve capacity built in. You have a big lab. It's kept operational. So it's truly a hot base. But you now

pay that laboratory some additional margin to allow it to function for maximal resiliency and not just maximal efficiency. We need to think about that way with respect to drug manufacturing as well. How do we pay for biologics manufacturers to maintain some reserve capacity in their existing facilities so that if we need to scale up the manufacturing of an antibody, we don't have to kick drugs out and move them to European facilities to free up domestic facilities. We have that reserve capacity built into the system. And it can't be just building a plant and mothballing it. We tried that with emergent. And we saw that if you build a plant and you're not operating it continuously, you know, it's not kept up to date. You don't keep the

skilled personnel on hand that you need. It's not really available. We don't think of investing and maintaining those capacities in the same way we think about national security threats, the ability to evacuate an embassy in a foreign country. We can mobilize that in 24 hours and have troops on the ground. And if we want to be prepared for the future pandemic and we want to prevent the future pandemic. That really needs to be our goal and look at it as part of our national security posture. But is that more FEMA or more DOD or is that a new agency? I don't think it's necessarily a new agency because I think it's always hard to create the new agency. There's going to be a turf war among the existing agencies. Originally, when CDC was conceived, it had a very national

security mindset. Security was deliberately used in some of the terminology around how they described the EIS, the epidemiological service, the sort of backbone the heart of that agency. but it's moved away from that into, you know, working on smoking cessation and prevention of heart disease and some of the more policy-oriented public health issues. And I'm not saying those aren't important. They are. But we've got to ask the question of whether or not that focus can coexist with an organization that has to have a national security focus or whether you need to separate the two functions. Do we give the disease prevention aspects of CDC's mission to the NIH and maybe we just focus CDC on disease control, you know, dealing with outbreaks and

epidemics, do we build a new entity in CDC that has a completely different mindset and capacity? You need a disease response organization. And so you need to build a component that's much more of a national security orientation. It has a FEMA-like capability. We've kind of started building that with the new disease targeting center that they created to do the modeling of disease outbreaks, but you're going to have to build that operational capacity. And then you're just going to have to fund it and have it exist even in a peacetime setting. You know, in the 10 intervening years when there's no pandemic or there is no large outbreak, what is that organization doing?

What is its day-to-day obligations? If we took our military and had them engage in, you know, more National Guard-like functions, they wouldn't be the 82nd Airborne anymore. So you're going to need to find that balance. So in what sense should they be the last word to really be definitive or the first word to set the warning for the rest of us? You need an agency that is comfortable surfacing information that is partially accurate and is going to inform real-time decision-making.

The intelligence community does this all the time. They'll say this assessment has a moderate degree of certainty. This assessment has a low degree of certainty. This assessment has a high degree of certainty. And they'll give the reader what the intelligence is behind the assessment. And that's how the president and a military establishment make decisions about geopolitical threats. CDC is presumably going to be this agency, but it needs a different orientation. They're in the business of saying, we're going to do a very exhaustive analysis,

and then we're going to wait, and we're going to publish it in JAMA. That's not a crisis-level response. When I was at FDA, and the information from the 2017-2018 National Youth Tobacco Survey came out showing a dramatic rise in youth use of vaping products that we, at FDA, said, was a public health crisis. Initially, CDC prevented me from putting that data out, because they said, we can't put this data out yet. We plan to publish it. They weren't done scrubbing it. They weren't done baking it.

And we said, we need to get this out immediately. We need to start having a policy response to this. In the 2017-2018 flu season, we at FDA had a view that it was a particularly bad flu season, which it ended up being. We were concerned that the vaccine wasn't covering the flu strain as well as past vaccines had, which was right. It was only 25% protective against the predominant strain

of influenza in that season. And so we crafted a public health advisory at FDA to sort of warn the public about this. And CDC blocked me from putting that out. They actually went to the secretary's office to say, FDA can't talk about the flu season. We talk about the flu season. The flu is our domain. And we're not ready to draw any conclusions about it. And we ultimately, we crafted it as an update to the labeling of the flu vaccines under the

rubric that we regulate the vaccines at FDA. CDC does. And we can amend the labeling anywhere we want. So we effectively put out the public health advisory. just in a different form. It took them another eight months to draw that conclusion. And then when they put out the estimate of how many people died that year from flu, if I remember correctly, it was something like 60,000 was the estimate. But if you actually looked at it, the confidence interval was like 40,000 to 120,000, because it turns out that the CDC doesn't actually

tabulate how many people are hospitalized for flu each year, how many people die from it. They actually derive it from a model that's based off of a very small sample set. And that's actually how they were reporting COVID hospitalizations at the outset of COVID. And then Deborah Berks and other people in the White House said, no, we need to know how many people are hospitalized every day and the hospitals they're being hospitalized. And we can't be shipping drugs to hypothetical patients derived from a model. And then they actually took the task of tabulating how many people are hospitalized for COVID every day away from CDC and recreated a new entity within HHS to aggregate that information. Wow. Wow. And there's a lot of layers on that about how just how

everything works. And as you drill down, you start to see how it can fall apart as well, given the complexities. Yeah. What more could people in the tech sector do to contribute to a pandemic preparedness plan? If you want to have the tech sector and the private sector engaging on this mission, the government's going to need to come up with structures that guarantee over a decade and not just sort of dissipate when our proximate fear of this pandemic starts to dissipate. And that's actually what thwarted some companies from making the initial investments that we needed to make at the outset of this pandemic. A lot of the manufacturers who could develop diagnostic tests said, you know, we've seen this show before. We ended up pivoting into developing test for Zika. And that's what

I was hearing a lot from the manufacturers. You know, the government told us we should be developing test for Zika. Zika turned out to be, you know, less pervasive than what we initially feared. And the government didn't reimburse us for the tests we developed and the work we had undertaken. So we're going to wait and see if this actually turns into something that's really threatening and then we'll pivot. And they ultimately pivoted six weeks too late. This system's hard to penetrate. And there are people who understand the process well, who are professionals at helping companies understand how to penetrate the system, how to get barter funding, how to make a presentation to Operation Warp Speed. And my advice would be to engage.

of those individuals. I mean, you know, sometimes they're lobbyists, sometimes they're consultants, but you wouldn't IPO a company without hiring a skilled investment banker and a good legal team that's done securities transactions before. I don't think you should try to go into developing countermeasures with the expectation that it's going to be something that's going to be purchased by the government without having experts around the table who can inform you on that government procurement process. Scott, to me, you've made a compelling case that nothing you said is going to happen. We're not going to be any more effective. The next time around, we're going to re-learn all the lessons through that this time. Specifically, we're going to have an incredible

private company response. You know, restaurants are going to know what to do. The private sector is going to know exactly what to do, and the government is going to be as just like as it is this time. I don't want to only be the little black rain cloud. Is that just way too cynical or is that like a real possibility? Well, it's fairly cynical, but I think arguing in favor of your grim analysis of the future is that there really hasn't been a collective effort to bring together a disparate group of experts and people across the political spectrum to come to a consensus about how we prepare differently for the future. And you can argue that it's still too early. We're still dealing with the first pandemic, but you run the risk that we move from the pandemic phase to the endemic

phase of COVID. We collectively say we're glad that the worst of this is over. That is a little worrisome. Look, I've said, and I talk a lot in the book about this, that we need to look at public health preparedness at this kind of a scale through a lens of national security and talk a lot about getting our intelligence agencies engaged in the overseas aspects of this, trying to identify emerging outbreaks. So we can't just rely on collective action and multilateral agreements of capacity and hoping that nations are going to tell us when they have an outbreak of an emerging pathogen. You still need some authoritative entity that's able to collect, analyze, and distribute information, something that's sort of like a J-Soc for public health response.

At the very least, you need that to inform the private sector response that you'd fall back on. But if you're looking at this through that mindset of a national crisis of this magnitude where you have basically the potential that a pathogen can shut down society, you can't expect the private sector to self-organize a response organically. People aren't coming into work. I mean, the private sector isn't functioning. You know, we wouldn't expect the private sector to self-organize an overseas contingency operation to deal with some foreign threat. We have a capacity that exists, a U.S. military capable of handling something of that magnitude. And I think you need something similar domestically.

We have it for other kinds of contingencies. We just don't have it for viral contingencies because we've really never looked at a pandemic as having this kind of impact on society, where it would sort of shut down all our other national priorities, where it would effectively change the geopolitical landscape around the world. There are things that happen in the world that are going to have impact. for decades to come that we haven't fully appreciated. I mean, just some of the things going on in the Pacific Rim in terms of China's actions against some of its neighbors. Would that have happened if it wasn't against the backdrop of a pandemic?

So recognizing that, recognizing how profound this hurt us, I think we need to invest differently. Yeah, I mean, the big question on my mind is when I talk to my friends about what COVID is going to mean for us, we're struggling to find the right analogy. and a lot of them have pointed to this being the World War II of our generation, this massive, worldwide, complex mess that have pulled everyone in. And like World War II, there are going to be big changes, new tailwinds, new winners, new losers, new approaches. What gets built out of this? How does it change how we think about health care? How has it changed the way consumers interact with health care? You know, just we have this huge force that's being driven out of this.

Yeah, look, I think COVID had a profound. impact across the full sweep of human history. I mean, it had a profound economic impact, profound geopolitical impact. It's going to have an impact on how we both develop and deploy technology. But I think it also had a profound cultural impact. I think it galvanized attention to protracted social ills that leave certain groups of society excessively vulnerable to public health challenges. And so I think it's going to change the course of sort of how we interact, how we grapple with social challenges, how we work collectively as a society. I mean, this changed the course of human history, this pandemic. So many lessons learned. I hope we learn from them. And I hope

people pay attention to it. Thanks for having me. Thank you, Scott. Can't wait for the world to pour through this book. Thanks a lot. Take care. Hey, Scott. This has been really great. Thank you. Thanks, Mark. Thanks, guys.