Popular Episode - Bob Nelsen on AI, China and the IRA

I think today, you have to give a nod to AI and the potential of AI, with lots of caveats. We live in a world that doesn't have a lot of data and has very, very low success rates and very, very low ability to figure out how everything kind of relates to each other in biology. The promise of AI to kind of decode or even link some of the disparate types of data that we have into some kind of semblance of approximation of what biology is doing is super interesting.

I think in both medicine and discovery, both of those things happen. In some sense, AI creates a set of tools that make the existing ways of doing things more efficient, more effective, more precise. At the same time, the more interesting promise is: can you essentially create a language of biology? Can you link all of these deterministic models that we have of chemistry and what happens with human data and what we propose about mechanism or function or genome together in some rational way to be able to ask harder questions? Like, 'Hey, make me a drug that treats what we call depression today.' Depression is defined on a 50-year-old questionnaire. That's our definition of depression. So is there a better way of looking at the data more precisely? And whether it's Transformer math or the current kind of AI that people are approaching, or some other math that kind of unifies these models, is the big question.

I think all of the major diseases that are not precisely traceable to a point mutation are going to be approachable by these technologies. We haven't figured out how yet, but I think whether it's cardiovascular disease or metabolic disease or anything in the brain, any of the complex, multi-genic or multifactorial type of diseases, clearly depression is not what we define by the questionnaire. Your depression and my depression may be fundamentally different diseases. And you could say the same thing about metabolic disease and cardiovascular disease. And then that's not even thinking about prevention. We only think about pharmaceuticals as a reactive, after-the-thought, 'let's fix it' when really the realm of AI could easily take us into more preventive pharmaceuticals or intervening in pre-disease in a fundamentally different way. And our pharmaceutical industry is not built very well to answer or ask those questions or answer them.

I think it's a start. I think it's better to have things approved and then proven wrong and not paid for than it is to have them not approved at all, if there's a potential benefit. So we need to lean into approving things, but we also need to lean into not paying for things that aren't effective. I actually think the current class of drugs should have been approved and should get approved, and that we should be rigorous about the follow-up studies to make sure that they're actually doing something. I think it's just version 0.1 in the battle against Alzheimer's. Once we have a better mechanistic handle on things, it may be that there are completely orthogonal ways of getting ahead of the neurodegeneration before it happens, even then, or treating things very early. Our pay model doesn't react very well to that. We have a model that wastes an incredible amount of money, trillions of dollars, on chasing disease and usually not curing or preventing it. I think diseases like Alzheimer's eventually will be treated well before you have any phenotype. So we're going to need to figure out how to align the interest of society in a way that gets paid for. Right now, those kind of drugs would be really hard to develop in the current system we have. But I do think there's promise in kind of decoding the brain with AI and decoding these complex networks that lead to diseases like Alzheimer's. Maybe Alzheimer's is kind of a point disease, and clearly you can see in the genetics that in certain cases of Alzheimer's, which is probably many diseases, it can be very, very precisely targeted. We just don't know how to reverse it or when.

I think it does create some perverse incentives to move away from small molecule drugs to biologics. I do think that in general, when you start going after innovation accidentally, whether you intend to or not, it will have unintended consequences. Right now, we're at an innovative environment that's going like this, so some of the impact gets lost in the noise of the innovation. It's super hard to tease out the absolute effect, other than as an investor, you would tend to lean more towards biologics than small molecules, all things equal, which probably isn't good for society. I think they're trying to go after abuse by pharma in the later years and kind of taking a sledgehammer to innovation at the same time. The problem with this is that they start with nine years, and you can already see that they want six years or four years, and then maybe we should do the same thing with biologics. It's a little bit like income tax: once you get it in there, it's not going away and it will be abused. I think there's a reasonable chance that if there's a Democratic House and a Democratic Senate and a Democratic president, they will really screw this up by pushing harder on the number of years and pushing it down, and really majorly impacting the US's competitive advantage in biotech and frankly negatively impacting all of the patients. I always thought that it would be fun to sit down with Senator Sanders and say, 'Hey, Senator Sanders, how are we going to cure Alzheimer's together? How are you going to do that? You said that you can't even talk to companies. Turns out that companies make drugs, governments don't. So how are you going to do that? If you don't talk to the companies and you don't want to engage in the conversation, you're just screwing your constituents who are old. Why can't you engage in a fundamental conversation about how we should go cure Alzheimer's?' Because that will save essentially equivalent to the defense budget in outlays in 2050. I mean, $8 trillion. An Alzheimer's cure would be worth a lot of money. Somebody could get paid a lot of money if they saved a trillion dollars. Senator Sanders, isn't that an okay thing? If you save a trillion, do you get $100 billion? That's net positive $900 billion to the treasury. So maybe we can have a meeting of the minds, but he doesn't actually want to engage in that conversation at all.

I think right now we're playing defense. I think the only way to get people to play offense a little bit is by pointing out that the US is the leader and won't always be the leader if we decimate our innovative ecosystem and that other places will threaten our competitive advantage if you do that. There are some Democrats in Congress that really understand that. So I don't think I'm going to change Senator Sanders' mind, but I do think that it would be interesting to sit down, probably in a closed session, to say, 'How could we cure Alzheimer's?' More of a national interest. Senator Sanders, can you take it upon yourself to spend a weekend off the record trying to figure out how not to bake in the current shitty system that we have that wastes $3.5 trillion a year on reactive healthcare and incentivize a more proactive system? A pill that cures Alzheimer's is worth a trillion dollars. I don't know if that would go anywhere, but I think you have to try those kind of things because you may be able to convince people on the margin that we're in the most innovative time in history, it's accelerating not decelerating, and we actually can move to a system that is more preventive even with drugs and more curative. And that's a cheaper system, a much, much cheaper system than big giant hospitals and a reactive system and a system where essentially people are paid even if the outcome sucks. I think there are some elements of common ground between the innovative industries and the idea that the system is broken. I think baking in the existing system is what I worry about.

We're still investing cautiously. I think we, like everybody else, look at the policy changes and it gives us pause in some areas. But clearly it's a huge market with a lot of unmet healthcare needs. It's also a very important place when it comes to emerging diseases, as we've already seen. You don't need a lesson in the fact that you can't ignore it. So I think putting your head in the sand because there's strategic tension is probably a bad idea. I've always thought that engagement is better than non-engagement. Even Armand Hammer was doing deals with Russia in the height of the Cold War. So we do have common interests. At the same time, there's a lot of reason for concern. So we're kind of watching and thinking more than investing and acting. But I think engagement is better than non-engagement on average. I also think that the US, the reason I helped to create Resilience, was to create our own national manufacturing infrastructure. And I think the US, if there are threats or competition, our response isn't always to play defense. Sometimes it's to play really good offense. And frankly, you almost have to do both. But I don't think we should be worrying as much about China on the defense. I think we should actually lean into playing offense and just winning. Now, winning means retaining your intellectual property. There's a huge concern about making sure that whether it's China or anywhere else, Europe and other places have been known to be interested in our intellectual property. Trying to defend it and maintain it is super important. Maintaining a strong patent system is super important and making sure that you enforce the laws is really important. So when I hear the nationalism, I get nationalistic too and say, 'Hey, yeah, the US should win.' We should win by making sure that we have the best science and making sure that we take advantage of it and making sure that we invest in it and making sure that we don't hurt it. There's much more of a threat from overregulation domestically than from China. We could screw ourselves much worse than China can screw us if we adopt Bernie Sanders' pricing policies and Ron Wyden's taxation policies. China could have written both of them. And frankly, we'll do much more damage to ourselves by bad policy than we do from being afraid. America's never really been afraid and won. We tend to play offense and try to win. So I think we should be cautious and we should play hard and we should win.

I think we need to create our own reimagining of biomanufacturing, not just an onshoring of the old technologies but a reimagining of new technology to make a much more effective system, kind of like the semiconductor industry did and they invested tons and tons of money in manufacturing. So I think you need everybody's help to do that. You need government's help, you need leverage, and you need to essentially have some of the companies rethink and some of the strong American companies rethink what they're doing and make sure that they're willing to use their purchasing power to support US companies that are building it up. Especially when you think about how good we are at manufacturing within some of our pharma companies but how that's not necessarily available to a bunch of biotech companies. So it's not so obvious as just banning Chinese companies from the market. If you think about somebody like WuXi, WuXi is incredibly, it's a different case than BGI. WuXi is incredibly important to little biotech companies in the US and some pharmas in terms of getting stuff done. And I'd like all of that stuff to be done domestically, but we have to be really careful as we're legislating to not have unintended effects on American competitiveness. And that's going to be a really interesting conversation in the next few months.

Yeah, I think the law of unintended consequences could be extreme if it was somebody like WuXi. BGI, probably not. And I think they're very different companies. But I do think that you have to be thoughtful about your approach in those things. We should be encouraging US manufacturing. We should be encouraging the reimagining of manufacturing in biology to make it more efficient, more effective. And there's an opportunity for the US to win in that. We're not always ahead in that. And if you can imagine, you can think of where there would be a transformational difference, for example, if the costs of manufacturing cell therapies and gene therapies were to go down exponentially, like they did for example in monoclonal antibodies a generation ago, that would have an enormous difference on the accessibility of those therapies to patients and on the world.

And I think that will happen, but it may not be as linear as you would like. And there's all kinds of policy impacts that could impact that as well. But you can see the trend, and the trend is those things are getting faster. Cell therapy is a great example. If you look at a CTI therapy or some of these other things, we postulated when we started Juno that maybe someday you could get these things down to a day or two, and people thought we were crazy. And that's already happening. And I remember people thinking that's just absolutely ridiculous, and even the scientists were saying no. So sometimes actually it's good not to listen to scientists because they won't set the goals as high as they might need to be to fundamentally change something.

We do both. So it could be like a Prime or a Beam or a company that we're incubating now in kind of RNA, where it's just an invention. It's a novel way of doing something better, or even just a novel way of doing something nobody could do or even could think of doing. And that's one way, and that's kind of a more linear, in a way, even though they're still platforms. And it might have an A and a B and a C and an IPO, which those companies did. And there are ways to make that go faster probably in the current way we structure things. And then there are the things like Alnylam or Denali or other things that we're working on that are going after large problems, large clinical problems. And some of the things we've been doing in Alnylam in that. And they may have multiple companies within them. Like we may pull two or three companies together. In all of those cases, there were multiple things that were incubating that were pulled into a bigger thing under hopefully a great management team. And then you have the ability of somebody like Ryan Watts to come into Denali and kill the lead project six months later and kill the lead product 18 months later and be just fine, because he had a bunch of money. We did a very, very large Series A, and he could apply a higher bar to some degree than most biotechs, because if you kill your lead product in most biotechs, you're in trouble. So those kind of portfolios, they're not really portfolios in the sense of trying to create a portfolio. They're trying to apply rigorous science, and if there are multiple ways to do it, then you do it multiple ways. Alnylam is very like that, where there's kind of a hypothesis, but it's really to dig into the biology with multiple ideas and pursue all of it at the same time and have enough resources to do it. So if you need to kill something, you just kill it, and there's not the need to hang on to something just because it's your lead asset.

It's something we think about a lot. And actually, Christina Burrell, I think, really led that effort within ARCH to be more systematic about finding the best people. We don't actually hire search firms or anything like that to do it within companies, we do, but as a firm, we've kind of found the self-assembly family model is a good way of doing it. And I think we're in a place right now where people come to us when they have big, crazy ideas or they're ready to do their last company. So I think the human capital aspect of what we do and getting better and better CEOs is probably the biggest thing that's changed over the last decade for us. As we've become more successful, we've been able to skip the two or three years of wasting money with a CEO that's suboptimal and go just straight to the great people. And what we've also found is that people think that actually we try to do big deals, and our biggest deals are usually created by cutting back a lot of people, so leaving a lot of money on the table, even though they're very large. But it's more about getting the best human capital as a CEO or as founding scientist together in one place with shareholders who are aligned with a long-term vision. And those shareholders happen to have a lot of money, so their minimum checks are pretty big. And it turns out the CEOs who have just sold their company for $7 or $11 billion don't really want to hang out with venture capitalists pitching a $20 million Series A deal. They would rather get $250 million to do what they want because they know what they want to do. And so some of these deals, not all, are better when they're capitalized with $250 million in an A round or even more in a seed round. And some of them are not. Some of them are much better with $3 million or $5 million or $25 million in the conventional model to reduce risk. And we have both flavors. But the human capital piece is where we're getting better as a firm and I think making better companies is by applying better people, more experienced people, more rigorous people to these really cool pools of technology to be able to figure out how to make drugs out of them without betting it all on one single molecule.

Yeah, and sometimes it's the same people, sometimes it's new people coming to us even if they've been funded by other venture funds because they want somebody, or at least a lead, to create a company. Because we're creating most of our companies from scratch with others in a way that they're thinking of five or 10 years down the road. And the hardest thing for this industry to understand is sometimes thinking long-term and ignoring the possibility of return or anything else and not modeling stuff is actually the best way to increase short-term optionality. But you can't fake it. You kind of have to go for it. And so you go for it with a lot of money and decide to nucleate a company that's going to go change things. And you get a great founder and suddenly your short-term optionality increases because people want to do business with you, they want to do deals with you, they want to give you money, they want to give you technology, or you can build the company more rapidly. Even though you can't really start out by saying you want to build the company more rapidly because you're going to let your short-term goals get in the way of the long-term goal. And I would say that a big problem with the industry is they tend to, especially in the kind of late-stage VC crossover realm, they kind of let the short-term goal get in the way of the long-term goal. And so you kind of need to ignore the short-term variations and always focus on the long-term. But when you get short-term opportunities, you don't ignore those. So it's, but you can't start by saying I'm going to just focus on the short-term and build a company.

Yeah, thank you. And really enjoyed it. Thanks a lot.