D.A. Wallach 深度解析:生物技术风险投资的独特性与未来 Bloomberg Podcasts 2025-12-12

D.A. Wallach 的跨界之旅:从音乐到生物技术投资

主持人 Tracy Alloway 和 Joe Weisenthal 介绍了本期节目嘉宾 D.A. Wallach,他拥有一个非传统的职业生涯轨迹,从一名职业音乐人转型为风险投资家,尤其专注于生物技术领域。Wallach 分享了他如何从音乐领域“滑入”风险投资界,最初是通过投资 Spotify,并逐渐将兴趣和专业知识拓展到包括生物技术在内的多个行业。他将自己目前的工作比作“为科学家做唱片制作人”,并认为音乐与生物技术投资之间存在一个有趣的共同挑战:如何在商业化过程中平衡艺术与科学,或医学与资本主义。

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And it's all about. It's all about. It's all about Tracy. It's all. About. It's all about. It's all about Joe. How's that? Hello, and welcome to another episode of the Odd Lots podcast. I'm Tracy Alloway and. I'm Joe Weisenthal. Joe, we were doing a Q&A this morning. That's right. It was a lot of fun. Go on a live Q&A and someone asked a question about whether or not we're going to do more health care episodes. And we don't do enough. Do it. No, we don't, and there's a reason for that. I personally am incredibly intimidated by the US health care system. I do not understand it. At all. It is just a complete mystery to me. But I was very happy to say in response to that question that this same day. That's right. We're actually recording a health care episode, with someone that we've wanted to speak to for for a long time. I'm the same way in the sense that, first of all, yes, I'm the same way, in the sense that I really do not know much about how the health care system works. I don't even know where to begin asking the right questions. This is what you do. You have to just start a random episode, and that gives you the germs of the next question, the next episode, the next episode. But there are so it seems so big and sprawling, etc. that what is the first question to ask? So we just have to plunge right in and just pick one, which we're doing now and then maybe that will lead to the string of health care episodes, which we should have done a long time ago. That's exactly right. There's also a lot of new stuff happening in health care at the moment, and we've recorded an episode on Chinese biotechs a little while ago that was incredibly fascinating. Definitely. I'm very curious to see what's going on on the U.S. side of biotech investing. And we do have another episode plan that's sort of tangentially related to that. But clearly there's a lot to talk about. The other very Odd Lots-y thing with this guest is we like people who have interesting career histories, right? That's right. How we, how they got to where they are today is often a very interesting question. You know, I have nothing against people who just took the normal path, people who just sort of, you know, went to college and then they got their MBA. And it's okay. You forgive them. I forgive them. That's really fine. But it's also interesting to hear about the people who maybe walked in through the side door, so to speak. Absolutely. So we do, in fact, have the perfect guest. We have someone who has a lot of thoughts on U.S. health care and who is also a biotech investor, and also formerly the lead singer of, Chester French. So D.A. Wallach, welcome to the show. Thanks so much for coming on. Thanks for having me, guys. I'm, I'm a Odd Lots junkie, so this looks like going to the Grammys. Amazing. Oh, did you ever win a Grammy? No. I'm sorry. Sorry, sorry, I shouldn't have. I shouldn't have asked that. Not. Not yet. Is not. Yet. Not yet, not yet. I love the piano in the background by the way. But I guess my first question should be, can you talk to us about the through line between being a musician and health care, and how you and biotech, and how you got into this space? Because I think, you know, it's not a natural transition, to say the least. Yeah. Well, I'll tell you how I ended up doing this, and then I'll try to connect them theoretically, in some way it might be a little tenuous. I've basically had three careers so far in my limited adult life. I was a professional rock musician with the band that you mentioned for several years, and then I kind of slipped into the venture capital world when I invested in Spotify. That was 13 years ago, and that was pretty much the only company in the private markets I was well-positioned to understand as a musician. And through the success of that, I got turned on to how exciting venture capital was. Started doing other types of investments across different industries was involved in space Acts and Ripple and a bunch of interesting other startups. And then ultimately, a guy I knew started an early stage health care company. It was a telemedicine startup called Doctor On Demand, and telemedicine at the time was not a hot topic because this is pre-COVID, right. So we still primarily went to the doctor in person. And when I made that investment, I started to learn more and more about our health care system and was just blown away by how screwed up and stupid it was. And then that eventually evolved into learning more about biotechnology and the other subsectors of health care that are critical to medicine. And it's ended up being what I do in terms of the connection between music and any of this stuff. There are a couple of ways I can think about it. One is I tell people now my job is like being a record producer for scientists. So there's a little bit of a parallel there, but the other is that I think there's a unique challenge in music to combining art and commerce. Yeah, and in health care, there's a similar parallel challenge, which is how do you combine medicine and capitalism, which don't naturally go together very well. Right. And I imagine yeah. The, the, the producer, analogy makes a ton of sense. And you know, there are a lot of musicians who are really brilliant and really great musicians, but for whatever reason, the lightning doesn't strike where they are or doesn't strike nearby and they don't take off, probably many brilliant scientists, etc.. But the paths from brilliant science to commercial blockbuster can often, I assume, be tricky or dispiriting. In many ways, etc. biotech specifically. Of all the things in investing, biotech, strikes me as this whole different world than the rest of like, investing. You know, when I think of like a software company, it's like, oh, okay, well, they've accumulated these clients and their churn is low, etc.. Yeah. This seems like a company that has traction is going to grow when it comes to biotech. It's like, okay, here's some patent on a sequence. And maybe ten years from now it'll get approved to something that'll be a therapy. It seems so much harder to figure out. Like, what are the heuristics that one would use to establish this is a likely this science is likely going to turn into a business. Oh, that's that's absolutely true. I it's like a completely different paradigm as an investor. I think the typical biotech company is like a bag of options. And each one of the drugs that the company is working on in success could be worth billions of dollars, but that's ten years away, often minimum. And so you're trying to price things based on their ultimate potential scale times, their probability of succeeding. And unfortunately, the base rates in terms of probability of success are very low. So if you take small molecules, which is one major area of drugs, the base case is like a 5% probability of success from the original idea to an FDA approval and a marketed drug. Now you get to a higher sort of prior probability with, antibodies or so-called biologics, other classes of drugs that are intrinsically more likely to work than small molecules. But still, in every case, you're dealing with very low probabilities of success. And the entire challenge is a biotech investors. How do you manage those low probability events and build portfolios that are still likely to make money, despite the fact that each individual project is relatively unlikely to work? I'd say in tech, there's this well-described kind of power law distribution of winners and losers, which is to say, a very small number of companies make all the money and pay for the huge number of losers in biotech. That's still true to a degree, but the magnitudes of the winners are lower. And so a really good biotech investor probably has a lower, sorry, a higher batting average than the typical tech investor. But the winds are not as big. So one thing I'm really curious about is how you source potential investments and how you find, you know, you use the analogy of the record producer, how you find talent in the space or how the talent kind of finds you and whether or not it's different from, again, the sort of soft where or tech space that we usually talk about when it comes to venture capital. You know, when I started doing venture investing, there was, like I said, 12, 13 years ago, it was obviously a well-established part of the capital markets. But, you know, I cold emailed Brian Armstrong from Coinbase and was meeting with them two days later. And it's hard to overstate how much money has rushed in over the past decade. So what went from being an established but still kind of marginal part of the capital markets is now all anyone thinks or talks about. Yeah. And so in biotech, what I found getting into this area was that it was more like that venture market I had encountered. There was a scarcity of capital relative to the capital, the caliber of ideas that were out there. And so I'd say deal sourcing is much easier in a sense, because there's less money chasing. Yeah, huge number of good ideas. And those ideas, by and large, do come out of our university and research infrastructure here in America. The same is also true in other parts of the world, in Europe, China, India and so forth. But it's really the translation of those academic concepts into products that could make money. That is the challenge. That's the so-called valley of death that people sometimes talk about in our industry. Yeah, there are just an immense number of cool ideas if you go into any university in our country, but such a small number of them is ever going to cross that chasm. And part of that is that the expertise and the personnel required to do that translational work is not the same expertise that is required to do the inventing in the first place. And so that is really what the large pharmaceutical companies have a specialized expertise, and they train people in this translational work. How do you go from early science to real products? Right. When I go to like a typical venture capitalist website or I see their Twitter bio or something like that, it'll say like, we met great founders and I'm like, thanks, that's very helpful because that distinguishes you from the venture capitalists who backed crappy founders. So I'm glad I'm going to invest with you instead. What's the biotech equivalent? What's the cliche in your industry that every VC says that ostensibly distinguishes them from all the others? Well, I'm not sure what the VCs say. I mean, they are kind of commoditized in the sense that most of the firms look pretty similar. They employ 30 PhDs and physicians, and the value of those people is that they can make sense of the information that you have to process to invest intelligently in this space. In terms of what distinguishes the founders that they like to look at, I'd say again, it's kind of the inverse of what you find in tech. There's a real premium on, quote, gray hair in the biotech industry, because the only way to learn this stuff is to do it over and over again. And they have had a lot of failures. And if you think about a software company, the tropes you are familiar with, are you know, fail fast, pivot. Right. You know, like you launch something that doesn't work. You tweak the product design, you go into a different market, you can adapt very readily to the market. In biotech, if you choose to embark upon a clinical program, you're in for 30 or 40 million bucks. That's not an easy door to walk back out of. Yeah. And so there's a real premium on people with experience who have done it multiple times. That is a little bit at odds in recent years with a movement that people have, I think, awkwardly dubbed tech bio instead of biotech. And really, these are Silicon Valley tech investors, not totally unlike myself, who have gotten into biotech. And they think that what's about to change is it's going to go the way of the tech industry, and the next big companies are going to be started by really clever 21 year olds coming out of Stanford. And that hypothesis people have been testing now for a few years. I'd say it's a little too early to, issue a verdict is that that's never really been our theory. Is that hypothesis just predicated on AI coming in and making, you know, drug development easier? Is that all it is? There's a lot of that. I'd say there are two parts of it. One of it is maybe more substantive than that. This is a little nuanced. I know of lots of people like nuance. We love it. One of the big transformations that really gave rise to the biotech industry. And when I use that term biotech, I'm distinguishing it from big pharma. So biotech really just means small drug companies. Many of them are public. What really gave rise to that industry was the big pharma is at the behest of Wall Street Deprioritized early stage research, because Wall Street said you're wasting a lot of money on this really risky early stage discovery work. What we would rather you did was just let all these crazy guys like de finance startups, and once they work, just by then, you know you're going to pay a higher price, but you won't be burning all this money on early stuff. What that led to was an exodus of very specialized technical experts from the pharma companies, and it created the so-called CRO, or contract research organization ecosystem. So you now, as a consequence of that, for the past 20 years have had a very proficient, environment, full of, contract organizations that you can hire as a little company to outsource a lot of work that you couldn't in the past. So the best analogy to tat to tech would be sort of like virtual servers or cloud infrastructure, like, you know, to have a startup, you used to have all these servers in your office and then at some point you didn't need that. So the cost of new company formation went way down. So part of the argument for younger, more agile founders has been, look, we got this whole new kind of infrastructure through which they can build companies in a really agile way. The other argument, you know, exactly to your question is around AI. And that theory is basically, look, these old people don't understand AI. Let's get some young Silicon Valley computer science types to do this. And they're going to show them how it's done. I feel like that's probably. A phenomenon that goes beyond biotech, where there's this fantasy and maybe in some cases it's even correct. But there is this fantasy that every industry out there must be dominated by old dinosaurs who don't know how to use tech, and who have been doing something the same way forever. And so steer 2025. It must be out of date by now, and they haven't figured this out. And if we could just cough, cough journalism. Yeah, right. If we could just hire whiz kids, then we could reinvent the industry from first principles and just do a much better job than the legacy things. And I think whether it's health care or whether it's industrial stuff that we see Silicon Valley getting excited about right now, it just feels like the default assumption must be that the veterans are doing something wrong, and with pure brainpower, we can figure out what that thing is. I think that is a reasonable characterization of what people say. Yeah, in a lot of different places. And I don't think it's true in my sector. But as with every conversation about AI, the challenge is balancing two ideas that can be true at the same time, but seem contradictory. And one is that this stuff is amazing. And it is, particularly in life sciences, responsible for some true breakthroughs like the breakthrough that won Demis Hassabis at DeepMind, the Nobel Prize last year with, AlphaFold, which was this amazing discovery they made that use in machine learning models. You could solve a problem that had gone unsolved for decades, which was can you predict from the sequence of a proteins amino acids what three dimensional shape a protein is going to take in a physical environment and I just threw around a bunch of terms of art. But this is fundamental to drug development and drug discovery. So it's like on the one hand, you can't deny these breakthroughs that we're experiencing. You can't deny that when you talk to Gemini, it's staggering what this thing can do. I mean, I'm sitting there all day having it teach me about asset pricing models or whatever else I'm interested in. But at the same time, the religious movement that is powering all of the investment and a lot of the entrepreneurship here across industries is full of hot air and is making claims that are preposterous. Unless you are a zealot. Just real quickly. If we'd been having this conversation in a month ago, would you have said Gemini? Or would you have said ChatGPT? Because I switched from Chegg, we did a Gemini in the last month, and I'm just curious whether you're what you would have said a month ago. A month ago, I was using all of them. Now I'm only using Gemini. It's interesting. All right, good data point. Okay, talk to us about the choke points when it comes to new drug development, because I imagine, okay, maybe AI machine learning can speed up some of the research or discovery process, but even after that, you have to go through these really long clinical trials that in some cases take decades. What what are the major, I guess, like stumbling blocks to getting something to the market? Your question held the answer. So the the process of taking a drug from idea to the market, you can think of as a funnel to just use a visual analogy and into the top of the funnel go all the millions of ideas that people have. And then as you go down the funnel, you are spending progressively more and more and more money to prove two things. The first is that the drug is safe and won't harm or kill people, and the second is that the drug works and it actually modifies the disease that you're trying to treat. And the tragedy of our moment is that the only way to figure out if drugs are safe and effective is to try them in human beings, living, breathing human beings. And that is extraordinarily time consuming and incredibly expensive financially. So I wish for the day when AI is able to fully simulate an accurate human in the computer, and we don't need to do clinical trials on real people. But until that moment, the vast majority of the cost and expense and time that is involved in drug discovery remains with us. So most of the AI technologies that people are excited about really would have the effect of putting more good ideas into the top of the funnel. But unfortunately, that doesn't solve a problem that we have. We already are drowning in good ideas, and the issue is exactly the choke point or bottleneck that you're referring to. This is really I there's actually two questions. First of all, is there low hanging fruit from a regulatory side to accelerate that process? People like to fathom, oh, the FDA must be super. There's another area people will say, well, the FDA must be super slow and do things one way we could speed this up. I don't know, is there somewhere along the process where like from a regulatory standpoint or some other thing that the either the cost of the timelines could shrink or is it mostly still just the reality of we have to test these things on humans, and that's costly and it takes time. Well, we don't need to do anything. We could have no FDA. Sure. And anyone who has a good drug idea just launches it commercially. And if some people die from that and it doesn't do anything, that's fine. By the way, that's kind of like the supplement industry. Yeah. Peptide. Deal with it. Milton Friedman famously thought that the FDA should only assess the safety of drugs. Yeah, and if a drug was proven safe, put it on the market and let the market dictate whether people determine they should pay for it based on their lived experience with whether it works or not. Now, I just personally prefer to live in a world where if I've got something that's going wrong, I can more or less trust that the product my doctor gives me has been proven safe and effective, and that reflects that. We have today a pretty high bar for approving drugs, but we could certainly lower that bar. We could change the type of data that the FDA requires. And that's what's happening in China. By the way, I know you mentioned this other episode you did with my friend Tim. In China, the regulatory environment has been moving pretty rapidly, and they've done that deliberately because they want to be more productive, they want to approve more drugs, and they're trying to strike that balance between being prolific and, holding things to a high standard at the same time. So, you know, we'll see. And I just want to follow up on one other thing you said, because I think it seems important, someone like Sam Altman, when he talks about the promise of AI a lot of it is like, oh, we could find the next drug that cures cancer. In the meantime, we're going to make the sort of slot machine that makes weird videos, etc. but really, we're trying to find these wonder drugs in the long term. But for what? It sounds like you said, candidates are not where the shortage is like. The issue is not that we lack a sufficiently a number of sufficiently promising molecule combinations. The scarcity is not on that at that point. That's my view. I mean, I'll steal, man. The other argument, the other thing, it would be, well, look, DEA, you said ten minutes ago that these drugs have a 5% probability of working from the outset. You know, if we had better predictive models that told us certain candidates were much more likely to work than others, wouldn't that be great? And my rejoinder to that is, yes, but how would we know that we've done that? Meaning, if the three of us tomorrow invented a black box that produce drug candidate concepts, and we were certain that our model doubled the prior probability from 5% to 10%, that would be a truly revolutionary innovation on our part. But how many candidates from that model would we need to take all the way to an approval? Before we had statistically demonstrated that we, in fact increased the rate of of success? Yeah. So people may have already cracked that code. You know, Google may have already cracked the code. Sam Altman may have cracked that code, but someone's going to need to spend $30 billion developing the drug ideas he has before we know whether he's done that. And until that money is spent, it's pure conjecture and salesmanship. How are you actually evaluating opportunities in the US against China competition? Because, you know, if clinical trials are the major choke point and if China seems to be trying to make that process as efficient as possible, it seems like maybe they have an advantage. I mean, they definitely have an advantage. And if I had to make a bet today on our sector, it would be that China is going to be the big story over the next decade or two. I think it's a fundamental structural shift in the global biotechnology market. And there are advantages are multiple. I mean, their advantages are regulatory. They relate to the personnel. We have lost an amazing amount of talent who was educated here in our graduate schools and now has gone back to China. And furthermore, they are, able to develop things in the clinic which is to say, do clinical trials a lot faster and at a much higher volume than our infrastructure can handle. So they've got big advantages. Now, how do I think about investing in the US versus China? I don't that much because I don't speak Mandarin. And I think it would be really difficult for me to invest in China today. But increasingly, companies in the U.S. are starting to outsource certain parts of the research process to Chinese companies. And increasingly, they're going to outsource parts of the clinical development process, the clinical trials to China, that's going to make a huge impact on the industry. Yeah. This was actually my next question. I guess how translatable is a successful clinical trial in China to a market like the US? 3 or 4 years ago, what both investors and regulators in the US would have told you was that it's not that translatable because they're liars and they make up all the data and it's rampant with fraud. And there may have been some truth to that, but I think there was also a good amount of racism. And what sort of woke everyone up in the past couple of years was that some very significant clinical trials were done in China. People were suspicious of the data. Then they replicated those trials in Europe or the United States and got very similar data. And folks thought, whoa, maybe they're not so bad at this. So I think decreasingly people are skeptical. And which said, less awkwardly, people are trusting more and more what's coming out of China. And it's incumbent upon the Chinese, to the extent that they want this to be a major strategy to continue, enhancing people's trust in the quality of their work in their data. If they can do that, I think it's a global industry. A lot of the companies are multinationals. They don't care if the drug comes out of the U.S. or comes out of China. This isn't really a question about private or VC stage investing per se, but about biotech more broadly. You know, there is some sickos out there on the internet who like trade by trade, retail traders who trade up biotech stocks. And again, this is I've never I've talked you know, I've covered the stock market for a long time in various ways. I've never spent any time really getting to know a publicly traded biotech stock. Is are you insane to try to invest in biotech? If you don't have a PhD level understanding of biology, like, can anyone have alpha in this industry if they don't actually know science? I think it's tough. Yeah, it seems very tough to me. Yeah. I mean, here's the thing. What's really interesting about biotech in the public markets is it's abundantly clear that active investors can have alpha in biotech. Whereas as you guys know that is not clear. Right. And the rest of the public equity landscape. And so whereas there is very little if not negative persistence of performance among active equity managers broadly in biotech, you have a small number of firms that have been doing great for sometimes decades. And they all have real science expertise on staff. They do. And, you know, the dynamic between them and the generalists, so to speak, is that they do a lot of very detailed work to make sense of the information you need to process, to value these companies and to assess their probability of success. And then the generalists often follow those specialists into these names and the fortunes of the industry in these cycles, like we're coming out of a four year Great Depression for biotech, I should just mention a lot of those fortunes ride on the sector rotations of the generalists. So the specialists have to stick with biotech because that's what they do. But whether or not companies can IPO, whether or not companies can fund their next clinical trial is largely a function of whether the generalists are in the sector at that moment or not. And we're just in the midst of the early rotation of generalists back into biotech. With the biotech investing downturn, was that just a function of higher interest rates, or was something else going on? It was a confluence of everything that could go wrong. At the same time, it was higher interest rates, which really punished these biotech stocks relative to other companies because, you know, no cash flows for ten years and then a big bowl of some money. So these companies are very sensitive to discount rates. Yeah. Add to that this dynamic where the generalists had gotten out of the sector that ultimately is fatal. And then, consider the fact that we had such a comedown after the sugar high of Covid. So obviously, during Covid, there was this moment of clarity where everyone for a second recognized that this sector is for each of us at some point in our lives, the most important thing that happens in the global economy, like without the biotech industry, you know, we're all in trouble. And we kind of go through life pretending like we're never going to need this industry. And then you get cancer or your dad gets cancer. Yeah, your kid gets some rare disease, and you go, Holy cow, I wish I'd thought about this before. Maybe all these people who are doing this with their lives are not evil bloodsuckers who Bernie Sanders needs to take down. And, you know, that is, I think part of what dawned on people during Covid when we all were vulnerable and we all were yearning for a solution. Talk a little bit more about, I guess, the the financial incentives about actually developing new drugs. So we we all know the story of if you're based in the US, you can go to Mexico or wherever else and buy the same medicine for like five bucks as opposed to $500 or perhaps even more in the US. And the argument for that seems to be that, well, you know, the big pharma companies need to be rewarded for all the research and the effort and the risk that they actually take on. And for some reason, the US seems to be the designated place to do that. But like, why? Why is my question why U.S drug pricing? Well, the the big bounty for a drug development company is the United States market. And that's partly because we as a society have decided that we want all the new most advanced drugs. We want them first and we don't want to deny them to people who could benefit from them. Now the price we pay for those commitments is that our drug prices are higher than the prices in other countries. And the reason their prices are lower is because their governments choose which drugs their people will have access to, and they make those choices and then negotiate the prices with the companies. And they basically will say to Pfizer or AstraZeneca, look, if you want your drug sold here in Japan, you're going to take the price that we give you. And then the pharma company decides whether they want to accept that deal or not. Now, the United States absolutely could choose as a civilization to negotiate. In that same manner, our government could make the choice for us as to exactly what we're willing to pay for every drug there would be two consequences to that. One is that we would go without certain drugs. The second is that a lot of drugs would not even be developed in the first place, because the total pool of profits available to drug companies would be much smaller. And so I don't know that there's any perfect answer to how much pharmaceutical innovation we should have in the world. We get to choose how much innovation we want to occur and the way we choose. That is by determining the size of that bounty that exists. How big is the profit pool? We want to allow for innovative drug development, and a lot of that is driven by our patent law. Remember, a patent in this industry is a legalized monopoly. So we give drug companies a legal monopoly for a limited period of time. And that dictates how much money they're able to make off of a new drug. We could shorten the patent life and that would reduce the profit pool, you'd have less drug development. We could remove the patent life. You could have a permanent monopoly. And believe me, the industry would double or triple overnight. So it's a choice we have to make and it's a civic choice. You mentioned the Bernie Sanders of the world who, they look at the profits of drug companies, they look at the prices of drugs. And, you know, perhaps if they got their way, there would be less investment in drug discovery instead of drug at all, maybe less profit going back to Covid. However, there was also the backlash on the other side, essentially just this deep skepticism towards the premise of pharma and that what are these scientists doing? And why don't they tell you about this route that people have used for thousands of years that cured these diseases that they don't want you to know about, so that they can sell your stuff? Talk to us about like, just the sort of political environment investing in biotech in a political environment or a growing number of people, frankly, seem to distrust the promise of scientific expertise. Look, it's tough, and some of the blame certainly belongs with the scientific community, because, you know, to the extent that, say, in the early days of Covid, communication with the public about, say, the value of masks was not clear and it was maybe even misleading. Yeah, some of the presentation of data regarding the efficacy of the vaccines was not transparent. And that eroded the public's trust in a very understandable way. Now, I'm no apologist for medicine or science because I don't think these are privileged priesthoods. I think every person should be able to be engaged in and understand science and medicine. And unfortunately, the entire history of medicine began with medical science as total witchcraft and sorcery. So if you go back to antiquity, the first people calling themselves doctors objectively understood nothing. Yeah. So this was pure sophistry from the beginning. And we are on this long journey through which medicine is going from total B.S. and witchcraft to slowly turning into a real science, something that deserves to be called science. Medicine is filled with common practices that are not rigorously based on evidence, and that is symptomatic of where we are in that journey that I'm describing. So I'm an advocate for medicine becoming always more and more scientific. I believe that scientific policymakers, scientists and academia need to do a much better job communicating transparently, and that's the only way to engender that kind of trust. You're talking about show, and the trust is critical because it is what gives permission to this industry's existence. We talk more about, I guess, autonomy when it comes to medical decisions, because this is, you know, a big culture shock of non-Americans who come to the US is drug adverts on TV where they, you know, here's this great drug, and then they read off all the risk factors really, really quickly. And one of the risks is always death or severe brain damage or something. Suicidal tendencies. Yeah. And I'm always like, again, I've never asked for a drug that I've seen on TV. I do remember when I, when I first came to the US as an adult, I went to get a prescription. I found a new doctor to do that. And I said I needed this thing. And the doctor was like, oh, well, we have to run all these medical tests before we can give you that. And it ended up in a big argument with my insurance provider. And I remember talking to people about that, and they were like, well, you should have pushed back against the doctor about the testing. And I was like, what do I know? I just do what the doctor tells me, right? How much, say, should people? Actually, it sounds weird, but you know, given the lack of experience and given the way other systems work, around the world, how much safe should people have in their own medical treatment? I think ultimately they should have almost all of the say it's your body. Ultimately, you have to make the best decision you can make, and you should regard physicians, nurses, others in the system as consultants who support you in making wise decisions. The one caveat there, however, is that we do socialize a lot of our medical costs. And in many other countries, they completely socialized medical costs. And to the extent that you want the rest of us to pay for your medical care, I do believe we need to have some standards around what it's appropriate to pay for. Yeah. I mean, at the moment it seems like most of those decisions are left up to the insurers, which again, in other places in the world, it would be left up to, to the governments to make those decisions. Are insurers the sort of another limiting factor here? I believe they are. I believe the private insurance industry adds zero value to the United States health care system, almost, that it may slightly overstate it, but it's close to zero in my book. And I really don't believe insurance companies ought to be the ones making decisions about what medical care is appropriate. I noticed there in the video you have a really nice looking microphone. Is that like a is that a, is that a musical? Is that a microphone for recording music? Yeah, this is this is the one I, this is one I sing on. It's first of all, you sound good, but it also looks a lot cooler than the typical microphone that are, that are guests. Do you, do you are you still are you still playing much music? I do, but but thankfully, now it's just for fun, not for money, which is a much more comfortable place for it to live in my life. Are you, do you think at all about, AI generated music and, the effect that that's going to have on musicians this month? I feel like a lot of musicians, like the ones that I follow on Instagram. I would say there's a lot of anxiety about this. There is anxiety. And look, I mean, it's really hard to make a living as a musician. Yeah. Now it's always been really hard and, you know, I can't imagine what the lifestyle was of a lute player and George the second Royal Court or something. But, you know, it's a tough business and it is scary when new technology comes on the scene. That might change the way you make money as an artist. I lived through that with Spotify. People were terrified of it and, you know, fortunately, what it did over time. They should have all done what you did, would get long Spotify and then hedge their own risk to it, but keep going on the. Spot. Spotify by multiples increased the total revenue of the recorded music business, which was the goal. So mission accomplished. Now look, I is going to make music. And I think like all creative people, like journalists, like investors, everyone is going to think about how they can use it to be more effective, have more leverage, have a cooler output. I mean, I have very little doubt that artists are going to do unbelieve cool and original stuff with AI tools, and it's already happening. And for whatever reason, I have very little trepidation that they're going to be put out of business, because I think ultimately music is communication. Real quickly on that. When you talk about like doing unbelievably cool things with music. So I see in the background you have a piano for example. And one of the things when I think about AI music is and actually I think like, for example, the founder of sumo and some of these other AI, music companies I've talked about, this is like, well, music, learning to play instruments is really hard. And therefore can we separate in some way the craft of music, the hours that someone has to spend just doing scales on the piano before they can compose something? Maybe you could. What? Wouldn't it be nice if we could just have amazing, beautiful piano sonatas without ever having had put in those thousands of hours? You know, Mary had a little lamb and then so forth. But it does raise the question to my mind of whether one can create great art if they never had to learn the craft. I think the nuance with which one can communicate through music is a function of how many options you perceive. Okay? In other words, if you know the piano inside out, you're aware of so many creative choices at your disposal at any moment. And if your ability to express yourself is squeezed down to what you can put into a natural language prompt. Yes. Now those musical ideas are having to pass through the medium of language right to be realized, and that inherently erodes the resolution and the expansiveness with which you can express yourself. Yeah, I feel like there's a danger here that you go off on a big orality tangent and whether ideas can exist without words and things like that. No, but I do think this is this, that answer very insightful. Like, can you actually create great piano music if you don't know the limits of what the piano can do? And if you're only trying to describe in language, make this beautiful sonata. I think that's very tough. And I thought that answer made a lesson. Da. We're going to have to wrap it up soon. I have one last question, and I'm going to kind of I'm going to put you on the spot. Can you can you sing a little Odd Lots song for us? like three bars of an Odd Lots Song? I don't care if you generate it with, you know, I guess Gemini now, but if you think you could. Let's see. I mean. Oh, wow. I'm going to turn this on. Let's see. Here. Oh, this is really cool. Yeah. If you aren't watching the video. So he's moving his microphone. He's moving his microphone to his keyboard okay. Can you see me. Yeah. Yeah. All right. Yeah. Go for it. I'm in through here. Okay. We're going to try. And it's all about. It's all about. It's all about Tracy. It's all about. It's all about. It's all about Joe. How's that. Feel? Pretty good. You have. You have a great voice. Yeah. It is. If you ever want to compose an outro song for us. Yeah, something like that. I would love to. I'm. I am the composer of 2 or 3 podcasts. Theme song. Oh, and, I have to say, I love your guys. Thank you. It gets me excited that I got to end on this for you guys. You know, in high school, the reason I got into investing in high school, I was an economics nerd. Oh, yeah, I. Heard. I heard that you actually wrote, like, some, a paper that won, like, a prize from the fed or something like that. The Federal Reserve had this nerd competition, and they sponsored called Fed Challenge and captain of my high school team one year, and we got to DC and we we saw Greenspan walk out with his wise and face and hands and anyways, if I had had odd lots to listen to in high school, man, I would have been in heaven because you guys touched on so much interesting stuff. And this just has to be the most exciting thing for young people to, experience in order to get turned on to business and economics and finance and recognize these aren't just boring, that's, you know, staid topics. They're fascinating. Now, thank you for saying that. I really appreciate it. And also, thank you for singing for us. I think that was an Odd Lots first that was a first. Yeah. So you're well on the spot. I know we've had, moral hazard. Yeah. Country singing economist on before but that was fantastic. D.A. Wallach, thank you so much for coming on the show. Really appreciate you guys. Thanks for having me. That was really interesting, Jeff. That was super fun. He was great. He's also pretty good at, you know, I know again, he said it was tenuous, but the through line from music to biotech kind of makes sense. I think it makes a lot of sense in the especially the fact that, you know, these are these are all startup investing, as we know. You know, there's there's this power law phenomenon where one of your 20 portfolio companies is going to make all the money. Yeah, the lottery ticket. But, you know, like biotech is like lottery ticket to lottery tickets. There's so much success, uncertainty. Lottery with lower payouts. There's lower payouts. There's so much success, uncertainty. There's so much time that elapses between the initial work and where you have see if there's any signals of traction. It does feel a lot like the uncertainty that exists in the music industry and selecting like, which of these 100 bands that all sound great and they're all really talented, actually has what it takes to be a commercial hit. A lot of parallels. Yeah. I thought the the dinosaur bias point was an interesting one as well because you can imagine, like again, to the timeline point, you kind of have to be old to have any success in the industry historically, just because it can take, you know, a decade to get a particular drug to market. So you don't have that much opportunity to have, you know, those wins unless you get old. And there's no shortage. There's no, you know, there may be regulatory things that can be done. But fundamentally, if you want to know whether something works and if you want to know whether this drug is going to kill people who take it or not and whether it's safe or not, there is no substitute for doing a test and seeing what, what happens. And to to your point or to your observation about the dinosaurs, like, I do think that lots of people have this fantasy that anytime there's a legacy industry of any sort, that if you just got 21 year olds from Stanford in the same room, you gave. Them a garage and workout. Garage, that they would do it a lot better than the veterans. That was the DOGE premise. And, DOGE doesn't exist anymore. So. Yeah. All right. Shall we leave it there? Let's leave it there. This has been another episode of the Odd Lots podcast. I'm Tracy Alloway. You can follow me @tracyalloway. And I'm Joe Weisenthal. You can follow me @thestalwart. Follow our guest, D.A. Wallach. He's @dawallach. Follow our producers, Carmen Rodriguez @carmenarmen, Dashiell Bennett @Dashbot, and Cale Brook @calebrooks. And for more Odd Lots content, you should definitely check out our daily newsletter. You can find that at bloomberg.com/OddLots And you can join fellow listeners in conversation 24 seven in our discord, discord.gg/oddlots And if you enjoyed this conversation, please like the video or leave a comment. Or better yet, subscribe! Thanks for watching.

生物技术投资的独特范式:风险与回报

D.A. Wallach 强调,生物技术(Biotech)投资与软件或科技投资有着本质的区别。科技公司通常可以通过客户积累、低客户流失率等指标来衡量其发展势头。然而,生物技术公司的情况则截然不同。其核心价值往往体现在一项专利或一项潜在的治疗方法上,而这些可能需要十年或更长时间才能获得美国食品药品监督管理局(FDA)的批准并成为上市药物。因此,生物技术投资的评估模型更像是对一系列“期权”(options)进行定价,即评估每种药物的潜在市场规模乘以其成功的概率。不幸的是,这些成功的概率通常非常低。例如,对于小分子药物(small molecules),从最初的想法到最终获得 FDA 批准并上市,成功率可能只有 5%。虽然像抗体或生物制剂(biologics)这类药物的成功率会稍高,但整体而言,生物技术投资始终伴随着极低的成功概率。

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But I guess my first question should be, can you talk to us about the through line between being a musician and health care, and how you and biotech, and how you got into this space? Because I think, you know, it's not a natural transition, to say the least. Yeah. Well, I'll tell you how I ended up doing this, and then I'll try to connect them theoretically, in some way it might be a little tenuous. I've basically had three careers so far in my limited adult life. I was a professional rock musician with the band that you mentioned for several years, and then I kind of slipped into the venture capital world when I invested in Spotify. That was 13 years ago, and that was pretty much the only company in the private markets I was well-positioned to understand as a musician. And through the success of that, I got turned on to how exciting venture capital was. Started doing other types of investments across different industries was involved in space Acts and Ripple and a bunch of interesting other startups. And then ultimately, a guy I knew started an early stage health care company. It was a telemedicine startup called Doctor On Demand, and telemedicine at the time was not a hot topic because this is pre-COVID, right. So we still primarily went to the doctor in person. And when I made that investment, I started to learn more and more about our health care system and was just blown away by how screwed up and stupid it was. And then that eventually evolved into learning more about biotechnology and the other subsectors of health care that are critical to medicine. And it's ended up being what I do in terms of the connection between music and any of this stuff. There are a couple of ways I can think about it. One is I tell people now my job is like being a record producer for scientists. So there's a little bit of a parallel there, but the other is that I think there's a unique challenge in music to combining art and commerce. Yeah, and in health care, there's a similar parallel challenge, which is how do you combine medicine and capitalism, which don't naturally go together very well. Right. And I imagine yeah. The, the, the producer, analogy makes a ton of sense. And you know, there are a lot of musicians who are really brilliant and really great musicians, but for whatever reason, the lightning doesn't strike where they are or doesn't strike nearby and they don't take off, probably many brilliant scientists, etc.. But the paths from brilliant science to commercial blockbuster can often, I assume, be tricky or dispiriting. In many ways, etc. biotech specifically. Of all the things in investing, biotech, strikes me as this whole different world than the rest of like, investing. You know, when I think of like a software company, it's like, oh, okay, well, they've accumulated these clients and their churn is low, etc.. Yeah. This seems like a company that has traction is going to grow when it comes to biotech. It's like, okay, here's some patent on a sequence. And maybe ten years from now it'll get approved to something that'll be a therapy. It seems so much harder to figure out. Like, what are the heuristics that one would use to establish this is a likely this science is likely going to turn into a business. Oh, that's that's absolutely true. I it's like a completely different paradigm as an investor. I think the typical biotech company is like a bag of options. And each one of the drugs that the company is working on in success could be worth billions of dollars, but that's ten years away, often minimum. And so you're trying to price things based on their ultimate potential scale times, their probability of succeeding. And unfortunately, the base rates in terms of probability of success are very low. So if you take small molecules, which is one major area of drugs, the base case is like a 5% probability of success from the original idea to an FDA approval and a marketed drug. Now you get to a higher sort of prior probability with, antibodies or so-called biologics, other classes of drugs that are intrinsically more likely to work than small molecules. But still, in every case, you're dealing with very low probabilities of success. And the entire challenge is a biotech investors. How do you manage those low probability events and build portfolios that are still likely to make money, despite the fact that each individual project is relatively unlikely to work? I'd say in tech, there's this well-described kind of power law distribution of winners and losers, which is to say, a very small number of companies make all the money and pay for the huge number of losers in biotech. That's still true to a degree, but the magnitudes of the winners are lower. And so a really good biotech investor probably has a lower, sorry, a higher batting average than the typical tech investor. But the winds are not as big.

交易来源与“死亡之谷”

与科技领域相比,生物技术领域的交易来源(deal sourcing)相对容易。Wallach 指出,尽管存在大量优秀的科学理念,但相对于这些理念的数量,可获得的资本却显得稀缺。这些理念大多源自美国大学和研究机构。然而,将这些学术概念转化为能够盈利的实际产品,是生物技术行业面临的核心挑战,即所谓的“死亡之谷”(valley of death)。只有极少数的大学研究项目能够成功跨越这一鸿沟。这不仅需要科学家的发明能力,还需要具备将早期科学转化为成熟产品的专业知识和人才,而这正是大型制药公司和合同研究组织(CROs - Contract Research Organizations)所擅长的领域。

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So one thing I'm really curious about is how you source potential investments and how you find, you know, you use the analogy of the record producer, how you find talent in the space or how the talent kind of finds you and whether or not it's different from, again, the sort of soft where or tech space that we usually talk about when it comes to venture capital. You know, when I started doing venture investing, there was, like I said, 12, 13 years ago, it was obviously a well-established part of the capital markets. But, you know, I cold emailed Brian Armstrong from Coinbase and was meeting with them two days later. And it's hard to overstate how much money has rushed in over the past decade. So what went from being an established but still kind of marginal part of the capital markets is now all anyone thinks or talks about. Yeah. And so in biotech, what I found getting into this area was that it was more like that venture market I had encountered. There was a scarcity of capital relative to the capital, the caliber of ideas that were out there. And so I'd say deal sourcing is much easier in a sense, because there's less money chasing. Yeah, huge number of good ideas. And those ideas, by and large, do come out of our university and research infrastructure here in America. The same is also true in other parts of the world, in Europe, China, India and so forth. But it's really the translation of those academic concepts into products that could make money. That is the challenge. That's the so-called valley of death that people sometimes talk about in our industry. Yeah, there are just an immense number of cool ideas if you go into any university in our country, but such a small number of them is ever going to cross that chasm. And part of that is that the expertise and the personnel required to do that translational work is not the same expertise that is required to do the inventing in the first place. And so that is really what the large pharmaceutical companies have a specialized expertise, and they train people in this translational work. How do you go from early science to real products? Right.

“科技生物”运动与人工智能的崛起

近年来,一种被称为“科技生物”(Tech Bio)的趋势兴起,吸引了许多硅谷的科技投资者进入生物技术领域。他们认为,生物技术行业即将迎来变革,并可能像科技行业一样,由年轻、聪明的创业者(例如来自斯坦福大学的 21 岁学生)引领。这种观点认为,人工智能(AI)的进步将极大地简化药物研发过程。然而,Wallach 对这种“恐龙偏见”(dinosaur bias)——即认为老牌行业由不懂技术的老古董主导的假设——持谨慎态度。他承认 AI 在生命科学领域取得了突破性进展,例如 DeepMind 的 AlphaFold(一种利用机器学习预测蛋白质三维结构的 AI 模型),这对药物研发至关重要。但他同时指出,许多关于 AI 的投资和创业热潮中充斥着夸大的宣传。他提到,自己现在更倾向于使用 Gemini 而非 ChatGPT,并认为 AI 的真正价值在于解决实际问题,而非仅仅制造“噱头”。

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When I go to like a typical venture capitalist website or I see their Twitter bio or something like that, it'll say like, we met great founders and I'm like, thanks, that's very helpful because that distinguishes you from the venture capitalists who backed crappy founders. So I'm glad I'm going to invest with you instead. What's the biotech equivalent? What's the cliche in your industry that every VC says that ostensibly distinguishes them from all the others? Well, I'm not sure what the VCs say. I mean, they are kind of commoditized in the sense that most of the firms look pretty similar. They employ 30 PhDs and physicians, and the value of those people is that they can make sense of the information that you have to process to invest intelligently in this space. In terms of what distinguishes the founders that they like to look at, I'd say again, it's kind of the inverse of what you find in tech. There's a real premium on, quote, gray hair in the biotech industry, because the only way to learn this stuff is to do it over and over again. And they have had a lot of failures. And if you think about a software company, the tropes you are familiar with, are you know, fail fast, pivot. Right. You know, like you launch something that doesn't work. You tweak the product design, you go into a different market, you can adapt very readily to the market. In biotech, if you choose to embark upon a clinical program, you're in for 30 or 40 million bucks. That's not an easy door to walk back out of. Yeah. And so there's a real premium on people with experience who have done it multiple times. That is a little bit at odds in recent years with a movement that people have, I think, awkwardly dubbed tech bio instead of biotech. And really, these are Silicon Valley tech investors, not totally unlike myself, who have gotten into biotech. And they think that what's about to change is it's going to go the way of the tech industry, and the next big companies are going to be started by really clever 21 year olds coming out of Stanford. And that hypothesis people have been testing now for a few years. I'd say it's a little too early to, issue a verdict is that that's never really been our theory. Is that hypothesis just predicated on AI coming in and making, you know, drug development easier? Is that all it is? There's a lot of that. I'd say there are two parts of it. One of it is maybe more substantive than that. This is a little nuanced. I know of lots of people like nuance. We love it. One of the big transformations that really gave rise to the biotech industry. And when I use that term biotech, I'm distinguishing it from big pharma. So biotech really just means small drug companies. Many of them are public. What really gave rise to that industry was the big pharma is at the behest of Wall Street Deprioritized early stage research, because Wall Street said you're wasting a lot of money on this really risky early stage discovery work. What we would rather you did was just let all these crazy guys like de finance startups, and once they work, just by then, you know you're going to pay a higher price, but you won't be burning all this money on early stuff. What that led to was an exodus of very specialized technical experts from the pharma companies, and it created the so-called CRO, or contract research organization ecosystem. So you now, as a consequence of that, for the past 20 years have had a very proficient, environment, full of, contract organizations that you can hire as a little company to outsource a lot of work that you couldn't in the past. So the best analogy to tat to tech would be sort of like virtual servers or cloud infrastructure, like, you know, to have a startup, you used to have all these servers in your office and then at some point you didn't need that. So the cost of new company formation went way down. So part of the argument for younger, more agile founders has been, look, we got this whole new kind of infrastructure through which they can build companies in a really agile way. The other argument, you know, exactly to your question is around AI. And that theory is basically, look, these old people don't understand AI. Let's get some young Silicon Valley computer science types to do this. And they're going to show them how it's done. I feel like that's probably. A phenomenon that goes beyond biotech, where there's this fantasy and maybe in some cases it's even correct. But there is this fantasy that every industry out there must be dominated by old dinosaurs who don't know how to use tech, and who have been doing something the same way forever. And so steer 2025. It must be out of date by now, and they haven't figured this out. And if we could just cough, cough journalism. Yeah, right. If we could just hire whiz kids, then we could reinvent the industry from first principles and just do a much better job than the legacy things. And I think whether it's health care or whether it's industrial stuff that we see Silicon Valley getting excited about right now, it just feels like the default assumption must be that the veterans are doing something wrong, and with pure brainpower, we can figure out what that thing is. I think that is a reasonable characterization of what people say. Yeah, in a lot of different places. And I don't think it's true in my sector. But as with every conversation about AI, the challenge is balancing two ideas that can be true at the same time, but seem contradictory. And one is that this stuff is amazing. And it is, particularly in life sciences, responsible for some true breakthroughs like the breakthrough that won Demis Hassabis at DeepMind, the Nobel Prize last year with, AlphaFold, which was this amazing discovery they made that use in machine learning models. You could solve a problem that had gone unsolved for decades, which was can you predict from the sequence of a proteins amino acids what three dimensional shape a protein is going to take in a physical environment and I just threw around a bunch of terms of art. But this is fundamental to drug development and drug discovery. So it's like on the one hand, you can't deny these breakthroughs that we're experiencing. You can't deny that when you talk to Gemini, it's staggering what this thing can do. I mean, I'm sitting there all day having it teach me about asset pricing models or whatever else I'm interested in. But at the same time, the religious movement that is powering all of the investment and a lot of the entrepreneurship here across industries is full of hot air and is making claims that are preposterous. Unless you are a zealot. Just real quickly. If we'd been having this conversation in a month ago, would you have said Gemini? Or would you have said ChatGPT? Because I switched from Chegg, we did a Gemini in the last month, and I'm just curious whether you're what you would have said a month ago. A month ago, I was using all of them. Now I'm only using Gemini. It's interesting. All right, good data point.

药物研发的瓶颈与监管考量

药物从概念到上市的过程,可以被视为一个漏斗。最初涌入的是数百万个想法,随着流程的深入,需要投入越来越多的资金来证明两点:一是药物的安全性(不会对人体造成伤害或死亡),二是药物的有效性(能实际改善所治疗的疾病)。然而,目前验证这些安全性和有效性的唯一方法是在活生生的人体上进行临床试验(clinical trials),这是一个极其耗时且成本高昂的过程。尽管 AI 技术可以帮助产生更多好的想法,但它并不能解决药物研发的核心瓶颈——即临床试验的漫长周期和高昂费用。

关于监管,Wallach 提到,虽然有人认为美国食品药品监督管理局(FDA)的审批流程过于缓慢,但也有观点认为,如果完全取消 FDA,允许任何药物直接上市,可能会导致更多人因无效或有害的药物而死亡,这类似于当前的补充剂行业。他引用了米尔顿·弗里德曼(Milton Friedman)的观点,即 FDA 应仅评估药物的安全性,而市场应根据用户体验来决定其有效性和价值。Wallach 个人更倾向于一个有严格安全性和有效性标准的体系。他指出,中国在监管环境方面正快速变化,旨在提高审批效率和数量,并在效率与高标准之间寻求平衡。

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talk to us about the choke points when it comes to new drug development, because I imagine, okay, maybe AI machine learning can speed up some of the research or discovery process, but even after that, you have to go through these really long clinical trials that in some cases take decades. What what are the major, I guess, like stumbling blocks to getting something to the market? Your question held the answer. So the the process of taking a drug from idea to the market, you can think of as a funnel to just use a visual analogy and into the top of the funnel go all the millions of ideas that people have. And then as you go down the funnel, you are spending progressively more and more and more money to prove two things. The first is that the drug is safe and won't harm or kill people, and the second is that the drug works and it actually modifies the disease that you're trying to treat. And the tragedy of our moment is that the only way to figure out if drugs are safe and effective is to try them in human beings, living, breathing human beings. And that is extraordinarily time consuming and incredibly expensive financially. So I wish for the day when AI is able to fully simulate an accurate human in the computer, and we don't need to do clinical trials on real people. But until that moment, the vast majority of the cost and expense and time that is involved in drug discovery remains with us. So most of the AI technologies that people are excited about really would have the effect of putting more good ideas into the top of the funnel. But unfortunately, that doesn't solve a problem that we have. We already are drowning in good ideas, and the issue is exactly the choke point or bottleneck that you're referring to. This is really I there's actually two questions. First of all, is there low hanging fruit from a regulatory side to accelerate that process? People like to fathom, oh, the FDA must be super. There's another area people will say, well, the FDA must be super slow and do things one way we could speed this up. I don't know, is there somewhere along the process where like from a regulatory standpoint or some other thing that the either the cost of the timelines could shrink or is it mostly still just the reality of we have to test these things on humans, and that's costly and it takes time. Well, we don't need to do anything. We could have no FDA. Sure. And anyone who has a good drug idea just launches it commercially. And if some people die from that and it doesn't do anything, that's fine. By the way, that's kind of like the supplement industry. Yeah. Peptide. Deal with it. Milton Friedman famously thought that the FDA should only assess the safety of drugs. Yeah, and if a drug was proven safe, put it on the market and let the market dictate whether people determine they should pay for it based on their lived experience with whether it works or not. Now, I just personally prefer to live in a world where if I've got something that's going wrong, I can more or less trust that the product my doctor gives me has been proven safe and effective, and that reflects that. We have today a pretty high bar for approving drugs, but we could certainly lower that bar. We could change the type of data that the FDA requires. And that's what's happening in China. By the way, I know you mentioned this other episode you did with my friend Tim. In China, the regulatory environment has been moving pretty rapidly, and they've done that deliberately because they want to be more productive, they want to approve more drugs, and they're trying to strike that balance between being prolific and, holding things to a high standard at the same time. So, you know, we'll see. And I just want to follow up on one other thing you said, because I think it seems important, someone like Sam Altman, when he talks about the promise of AI a lot of it is like, oh, we could find the next drug that cures cancer. In the meantime, we're going to make the sort of slot machine that makes weird videos, etc. but really, we're trying to find these wonder drugs in the long term. But for what? It sounds like you said, candidates are not where the shortage is like. The issue is not that we lack a sufficiently a number of sufficiently promising molecule combinations. The scarcity is not on that at that point. That's my view. I mean, I'll steal, man. The other argument, the other thing, it would be, well, look, DEA, you said ten minutes ago that these drugs have a 5% probability of working from the outset. You know, if we had better predictive models that told us certain candidates were much more likely to work than others, wouldn't that be great? And my rejoinder to that is, yes, but how would we know that we've done that? Meaning, if the three of us tomorrow invented a black box that produce drug candidate concepts, and we were certain that our model doubled the prior probability from 5% to 10%, that would be a truly revolutionary innovation on our part. But how many candidates from that model would we need to take all the way to an approval? Before we had statistically demonstrated that we, in fact increased the rate of of success? Yeah. So people may have already cracked that code. You know, Google may have already cracked the code. Sam Altman may have cracked that code, but someone's going to need to spend $30 billion developing the drug ideas he has before we know whether he's done that. And until that money is spent, it's pure conjecture and salesmanship.

中美生物技术竞争与临床试验的可信度

Wallach 认为,未来十年,中国在全球生物技术市场将扮演重要角色,并可能成为“大故事”。中国在监管、人才吸引(许多在美国接受教育的顶尖人才已回归中国)以及临床试验的执行速度和规模方面都拥有显著优势。美国虽然在生物技术领域仍是领导者,但其基础设施处理临床试验的能力已显不足。尽管如此,Wallach 表示自己因语言障碍(不懂中文)而难以直接投资中国市场,但他注意到美国公司正日益将部分研发和临床试验外包给中国。

关于中国临床试验数据的可信度,Wallach 指出,过去几年,美国投资者和监管机构曾对中国数据的真实性表示怀疑,甚至带有种族偏见。然而,随着一些重要的中国临床试验在欧洲和美国得到成功复制,人们的看法正在转变,对中国数据的信任度逐渐提高。他强调,中国需要持续提升其工作和数据的质量,以增强全球信任。

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How are you actually evaluating opportunities in the US against China competition? Because, you know, if clinical trials are the major choke point and if China seems to be trying to make that process as efficient as possible, it seems like maybe they have an advantage. I mean, they definitely have an advantage. And if I had to make a bet today on our sector, it would be that China is going to be the big story over the next decade or two. I think it's a fundamental structural shift in the global biotechnology market. And there are advantages are multiple. I mean, their advantages are regulatory. They relate to the personnel. We have lost an amazing amount of talent who was educated here in our graduate schools and now has gone back to China. And furthermore, they are, able to develop things in the clinic which is to say, do clinical trials a lot faster and at a much higher volume than our infrastructure can handle. So they've got big advantages. Now, how do I think about investing in the US versus China? I don't that much because I don't speak Mandarin. And I think it would be really difficult for me to invest in China today. But increasingly, companies in the U.S. are starting to outsource certain parts of the research process to Chinese companies. And increasingly, they're going to outsource parts of the clinical development process, the clinical trials to China, that's going to make a huge impact on the industry. Yeah. This was actually my next question. I guess how translatable is a successful clinical trial in China to a market like the US? 3 or 4 years ago, what both investors and regulators in the US would have told you was that it's not that translatable because they're liars and they make up all the data and it's rampant with fraud. And there may have been some truth to that, but I think there was also a good amount of racism. And what sort of woke everyone up in the past couple of years was that some very significant clinical trials were done in China. People were suspicious of the data. Then they replicated those trials in Europe or the United States and got very similar data. And folks thought, whoa, maybe they're not so bad at this. So I think decreasingly people are skeptical. And which said, less awkwardly, people are trusting more and more what's coming out of China. And it's incumbent upon the Chinese, to the extent that they want this to be a major strategy to continue, enhancing people's trust in the quality of their work in their data. If they can do that, I think it's a global industry. A lot of the companies are multinationals. They don't care if the drug comes out of the U.S. or comes out of China. This isn't really a question about private or VC stage investing per se, but about biotech more broadly. You know, there is some sickos out there on the internet who like trade by trade, retail traders who trade up biotech stocks. And again, this is I've never I've talked you know, I've covered the stock market for a long time in various ways. I've never spent any time really getting to know a publicly traded biotech stock. Is are you insane to try to invest in biotech? If you don't have a PhD level understanding of biology, like, can anyone have alpha in this industry if they don't actually know science? I think it's tough. Yeah, it seems very tough to me. Yeah. I mean, here's the thing. What's really interesting about biotech in the public markets is it's abundantly clear that active investors can have alpha in biotech. Whereas as you guys know that is not clear. Right. And the rest of the public equity landscape. And so whereas there is very little if not negative persistence of performance among active equity managers broadly in biotech, you have a small number of firms that have been doing great for sometimes decades. And they all have real science expertise on staff. They do. And, you know, the dynamic between them and the generalists, so to speak, is that they do a lot of very detailed work to make sense of the information you need to process, to value these companies and to assess their probability of success. And then the generalists often follow those specialists into these names and the fortunes of the industry in these cycles, like we're coming out of a four year Great Depression for biotech, I should just mention a lot of those fortunes ride on the sector rotations of the generalists. So the specialists have to stick with biotech because that's what they do. But whether or not companies can IPO, whether or not companies can fund their next clinical trial is largely a function of whether the generalists are in the sector at that moment or not. And we're just in the midst of the early rotation of generalists back into biotech.

生物技术投资的金融激励与定价逻辑

美国市场是全球药物开发公司最大的“奖赏池”。这是因为美国社会普遍希望优先获得最先进的药物,并且不愿剥夺患者受益的机会。然而,这种承诺的代价是美国国内的药物价格远高于其他国家。其他国家政府通过选择性地批准药物并进行价格谈判来控制成本。

Wallach 解释说,药物定价与创新激励密切相关。专利法赋予了制药公司在一定时期内的合法垄断权,这决定了它们能从新药中获利多少。如果缩短专利期,利润池会缩小,从而减少药物研发;反之,如果延长专利期,研发投入会大幅增加。他认为,我们选择允许多少创新发生,是通过决定这个“奖赏池”的大小来体现的。对于像伯尼·桑德斯(Bernie Sanders)等批评者提出的高利润问题,Wallach 回应说,减少利润可能会导致更少的药物研发投入。

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With the biotech investing downturn, was that just a function of higher interest rates, or was something else going on? It was a confluence of everything that could go wrong. At the same time, it was higher interest rates, which really punished these biotech stocks relative to other companies because, you know, no cash flows for ten years and then a big bowl of some money. So these companies are very sensitive to discount rates. Yeah. Add to that this dynamic where the generalists had gotten out of the sector that ultimately is fatal. And then, consider the fact that we had such a comedown after the sugar high of Covid. So obviously, during Covid, there was this moment of clarity where everyone for a second recognized that this sector is for each of us at some point in our lives, the most important thing that happens in the global economy, like without the biotech industry, you know, we're all in trouble. And we kind of go through life pretending like we're never going to need this industry. And then you get cancer or your dad gets cancer. Yeah, your kid gets some rare disease, and you go, Holy cow, I wish I'd thought about this before. Maybe all these people who are doing this with their lives are not evil bloodsuckers who Bernie Sanders needs to take down. And, you know, that is, I think part of what dawned on people during Covid when we all were vulnerable and we all were yearning for a solution. Talk a little bit more about, I guess, the the financial incentives about actually developing new drugs. So we we all know the story of if you're based in the US, you can go to Mexico or wherever else and buy the same medicine for like five bucks as opposed to $500 or perhaps even more in the US. And the argument for that seems to be that, well, you know, the big pharma companies need to be rewarded for all the research and the effort and the risk that they actually take on. And for some reason, the US seems to be the designated place to do that. But like, why? Why is my question why U.S drug pricing? Well, the the big bounty for a drug development company is the United States market. And that's partly because we as a society have decided that we want all the new most advanced drugs. We want them first and we don't want to deny them to people who could benefit from them. Now the price we pay for those commitments is that our drug prices are higher than the prices in other countries. And the reason their prices are lower is because their governments choose which drugs their people will have access to, and they make those choices and then negotiate the prices with the companies. And they basically will say to Pfizer or AstraZeneca, look, if you want your drug sold here in Japan, you're going to take the price that we give you. And then the pharma company decides whether they want to accept that deal or not. Now, the United States absolutely could choose as a civilization to negotiate. In that same manner, our government could make the choice for us as to exactly what we're willing to pay for every drug there would be two consequences to that. One is that we would go without certain drugs. The second is that a lot of drugs would not even be developed in the first place, because the total pool of profits available to drug companies would be much smaller. And so I don't know that there's any perfect answer to how much pharmaceutical innovation we should have in the world. We get to choose how much innovation we want to occur and the way we choose. That is by determining the size of that bounty that exists. How big is the profit pool? We want to allow for innovative drug development, and a lot of that is driven by our patent law. Remember, a patent in this industry is a legalized monopoly. So we give drug companies a legal monopoly for a limited period of time. And that dictates how much money they're able to make off of a new drug. We could shorten the patent life and that would reduce the profit pool, and you'd have less drug development. We could remove the patent life. You could have a permanent monopoly. And believe me, the industry would double or triple overnight. So it's a choice we have to make and it's a civic choice. You mentioned the Bernie Sanders of the world who, they look at the profits of drug companies, they look at the prices of drugs. And, you know, perhaps if they got their way, there would be less investment in drug discovery instead of drug at all, maybe less profit going back to Covid. However, there was also the backlash on the other side, essentially just this deep skepticism towards the premise of pharma and that what are these scientists doing? And why don't they tell you about this route that people have used for thousands of years that cured these diseases that they don't want you to know about, so that they can sell your stuff? Talk to us about like, just the sort of political environment investing in biotech in a political environment or a growing number of people, frankly, seem to distrust the promise of scientific expertise.

对科学专业知识的信任与医疗决策自主权

公众对科学专业知识的信任度下降是一个复杂的问题。Wallach 认为,科学界自身也应承担部分责任,尤其是在早期 COVID-19 疫情期间,关于口罩的价值以及疫苗有效性的沟通不够清晰,甚至存在误导,这侵蚀了公众的信任。他强调,医学正经历一个从“巫术和魔法”向真正科学的漫长演变过程,其中仍存在许多未经严格证据支持的常见做法。因此,他倡导医学界应更加透明地沟通,以重建信任。

在医疗决策自主权方面,Wallach 认为个人最终应拥有对自己身体的决定权,并将医生视为提供建议的顾问。然而,他也指出,由于医疗成本的社会化(即由集体承担),在一定程度上需要设定标准来决定哪些治疗是“适宜支付”的。他认为,私人保险行业在美国医疗体系中几乎没有增值作用,并且不应由保险公司来决定何种医疗是恰当的。

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Look, it's tough, and some of the blame certainly belongs with the scientific community, because, you know, to the extent that, say, in the early days of Covid, communication with the public about, say, the value of masks was not clear and it was maybe even misleading. Yeah, some of the presentation of data regarding the efficacy of the vaccines was not transparent. And that eroded the public's trust in a very understandable way. Now, I'm no apologist for medicine or science because I don't think these are privileged priesthoods. I think every person should be able to be engaged in and understand science and medicine. And unfortunately, the entire history of medicine began with medical science as total witchcraft and sorcery. So if you go back to antiquity, the first people calling themselves doctors objectively understood nothing. Yeah. So this was pure sophistry from the beginning. And we are on this long journey through which medicine is going from total B.S. and witchcraft to slowly turning into a real science, something that deserves to be called science. Medicine is filled with common practices that are not rigorously based on evidence, and that is symptomatic of where we are in that journey that I'm describing. So I'm an advocate for medicine becoming always more and more scientific. I believe that scientific policymakers, scientists and academia need to do a much better job communicating transparently, and that's the only way to engender that kind of trust. You're talking about show, and the trust is critical because it is what gives permission to this industry's existence. We talk more about, I guess, autonomy when it comes to medical decisions, because this is, you know, a big culture shock of non-Americans who come to the US is drug adverts on TV where they, you know, here's this great drug, and then they read off all the risk factors really, really quickly. And one of the risks is always death or severe brain damage or something. Suicidal tendencies. Yeah. And I'm always like, again, I've never asked for a drug that I've seen on TV. I do remember when I, when I first came to the US as an adult, I went to get a prescription. I found a new doctor to do that. And I said I needed this thing. And the doctor was like, oh, well, we have to run all these medical tests before we can give you that. And it ended up in a big argument with my insurance provider. And I remember talking to people about that, and they were like, well, you should have pushed back against the doctor about the testing. And I was like, what do I know? I just do what the doctor tells me, right? How much, say, should people? Actually, it sounds weird, but you know, given the lack of experience and given the way other systems work, around the world, how much safe should people have in their own medical treatment? I think ultimately they should have almost all of the say it's your body. Ultimately, you have to make the best decision you can make, and you should regard physicians, nurses, others in the system as consultants who support you in making wise decisions. The one caveat there, however, is that we do socialize a lot of our medical costs. And in many other countries, they completely socialized medical costs. And to the extent that you want the rest of us to pay for your medical care, I do believe we need to have some standards around what it's appropriate to pay for. Yeah. I mean, at the moment it seems like most of those decisions are left up to the insurers, which again, in other places in the world, it would be left up to, to the governments to make those decisions. Are insurers the sort of another limiting factor here? I believe they are. I believe the private insurance industry adds zero value to the United States health care system, almost, that it may slightly overstate it, but it's close to zero in my book. And I really don't believe insurance companies ought to be the ones making decisions about what medical care is appropriate.

AI 与音乐创作的未来

在节目接近尾声时,Wallach 谈到了 AI 对音乐产业的影响。他承认许多音乐人对 AI 生成音乐感到焦虑,因为这可能改变他们的收入模式。他以自己经历 Spotify 带来的变革为例,指出技术进步最初可能引发恐惧,但最终往往能增加整个行业的总收入。Wallach 相信,艺术家(包括音乐家、记者和投资者)将学会利用 AI 工具来提高效率、增强创作能力,并产生更酷的作品。他认为,音乐本质上是沟通,AI 不会取代艺术家,反而可能激发新的、原创的艺术形式。

关于学习音乐技艺的必要性,Wallach 认为,对乐器(如钢琴)的深入理解能带来更丰富的创作选择。如果创作过程仅限于通过自然语言提示来生成音乐,可能会削弱表达的精细度和广度。他认为,伟大的艺术创作往往源于对技艺的深刻掌握,而不仅仅是语言描述。

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I noticed there in the video you have a really nice looking microphone. Is that like a is that a, is that a musical? Is that a microphone for recording music? Yeah, this is this is the one I, this is one I sing on. It's first of all, you sound good, but it also looks a lot cooler than the typical microphone that are, that are guests. Do you, do you are you still are you still playing much music? I do, but but thankfully, now it's just for fun, not for money, which is a much more comfortable place for it to live in my life. Are you, do you think at all about, AI generated music and, the effect that that's going to have on musicians this month? I feel like a lot of musicians, like the ones that I follow on Instagram. I would say there's a lot of anxiety about this. There is anxiety. And look, I mean, it's really hard to make a living as a musician. Yeah. Now it's always been really hard and, you know, I can't imagine what the lifestyle was of a lute player and George the second Royal Court or something. But, you know, it's a tough business and it is scary when new technology comes on the scene. That might change the way you make money as an artist. I lived through that with Spotify. People were terrified of it and, you know, fortunately, what it did over time. They should have all done what you did, would get long Spotify and then hedge their own risk to it, but keep going on the. Spot. Spotify by multiples increased the total revenue of the recorded music business, which was the goal. So mission accomplished. Now look, I is going to make music. And I think like all creative people, like journalists, like investors, everyone is going to think about how they can use it to be more effective, have more leverage, have a cooler output. I mean, I have very little doubt that artists are going to do unbelieve cool and original stuff with AI tools, and it's already happening. And for whatever reason, I have very little trepidation that they're going to be put out of business, because I think ultimately music is communication. Real quickly on that. When you talk about like doing unbelievably cool things with music. So I see in the background you have a piano for example. And one of the things when I think about AI music is and actually I think like, for example, the founder of sumo and some of these other AI, music companies I've talked about, this is like, well, music, learning to play instruments is really hard. And therefore can we separate in some way the craft of music, the hours that someone has to spend just doing scales on the piano before they can compose something? Maybe you could. What? Wouldn't it be nice if we could just have amazing, beautiful piano sonatas without ever having had put in those thousands of hours? You know, Mary had a little lamb and then so forth. But it does raise the question to my mind of whether one can create great art if they never had to learn the craft. I think the nuance with which one can communicate through music is a function of how many options you perceive. Okay? In other words, if you know the piano inside out, you're aware of so many creative choices at your disposal at any moment. And if your ability to express yourself is squeezed down to what you can put into a natural language prompt. Yes. Now those musical ideas are having to pass through the medium of language right to be realized, and that inherently erodes the resolution and the expansiveness with which you can express yourself. Yeah, I feel like there's a danger here that you go off on a big orality tangent and whether ideas can exist without words and things like that. No, but I do think this is this, that answer very insightful. Like, can you actually create great piano music if you don't know the limits of what the piano can do? And if you're only trying to describe in language, make this beautiful sonata. I think that's very tough. And I thought that answer made a lesson.

结语:音乐与播客的奇妙融合

节目最后,D.A. Wallach 现场演唱了《Odd Lots》播客的标志性开场白,展示了他出色的音乐才华,并分享了他高中时期赢得联邦储备委员会经济学竞赛的经历,表达了对《Odd Lots》播客的喜爱。他认为,像《Odd Lots》这样的节目能让年轻人对商业、经济和金融产生兴趣,认识到这些领域并非枯燥乏味,而是充满吸引力。主持人也感谢了 Wallach 的精彩分享和即兴演唱,并表示这是《Odd Lots》播客的首次现场演唱表演。

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Da. We're going to have to wrap it up soon. I have one last question, and I'm going to kind of I'm going to put you on the spot. Can you can you sing a little Odd Lots song for us? like three bars of an Odd Lots Song? I don't care if you generate it with, you know, I guess Gemini now, but if you think you could. Let's see. I mean. Oh, wow. I'm going to turn this on. Let's see. Here. Oh, this is really cool. Yeah. If you aren't watching the video. So he's moving his microphone. He's moving his microphone to his keyboard okay. Can you see me. Yeah. Yeah. All right. Yeah. Go for it. I'm in through here. Okay. We're going to try. And it's all about. It's all about. It's all about Tracy. It's all about. It's all about. It's all about Joe. How's that. Feel? Pretty good. You have. You have a great voice. Yeah. It is. If you ever want to compose an outro song for us. Yeah, something like that. I would love to. I'm. I am the composer of 2 or 3 podcasts. Theme song. Oh, and, I have to say, I love your guys. Thank you. It gets me excited that I got to end on this for you guys. You know, in high school, the reason I got into investing in high school, I was an economics nerd. Oh, yeah, I. Heard. I heard that you actually wrote, like, some, a paper that won, like, a prize from the fed or something like that. The Federal Reserve had this nerd competition, and they sponsored called Fed Challenge and captain of my high school team one year, and we got to DC and we we saw Greenspan walk out with his wise and face and hands and anyways, if I had had odd lots to listen to in high school, man, I would have been in heaven because you guys touched on so much interesting stuff. And this just has to be the most exciting thing for young people to, experience in order to get turned on to business and economics and finance and recognize these aren't just boring, that's, you know, staid topics. They're fascinating. Now, thank you for saying that. I really appreciate it. And also, thank you for singing for us. I think that was an Odd Lots first that was a first. Yeah. So you're well on the spot. I know we've had, moral hazard. Yeah. Country singing economist on before but that was fantastic. D.A. Wallach, thank you so much for coming on the show. Really appreciate you guys. Thanks for having me. That was really interesting, Jeff. That was super fun. He was great. He's also pretty good at, you know, I know again, he said it was tenuous, but the through line from music to biotech kind of makes sense. I think it makes a lot of sense in the especially the fact that, you know, these are these are all startup investing, as we know. You know, there's there's this power law phenomenon where one of your 20 portfolio companies is going to make all the money. Yeah, the lottery ticket. But, you know, like biotech is like lottery ticket to lottery tickets. There's so much success, uncertainty. Lottery with lower payouts. There's lower payouts. There's so much success, uncertainty. There's so much time that elapses between the initial work and where you have see if there's any signals of traction. It does feel a lot like the uncertainty that exists in the music industry and selecting like, which of these 100 bands that all sound great and they're all really talented, actually has what it takes to be a commercial hit. A lot of parallels. Yeah. I thought the the dinosaur bias point was an interesting one as well because you can imagine, like again, to the timeline point, you kind of have to be old to have any success in the industry historically, just because it can take, you know, a decade to get a particular drug to market. So you don't have that much opportunity to have, you know, those wins unless you get old. And there's no shortage. There's no, you know, there may be regulatory things that can be done. But fundamentally, if you want to know whether something works and if you want to know whether this drug is going to kill people who take it or not and whether it's safe or not, there is no substitute for doing a test and seeing what, what happens. And to to your point or to your observation about the dinosaurs, like, I do think that lots of people have this fantasy that anytime there's a legacy industry of any sort, that if you just got 21 year olds from Stanford in the same room, you gave. Them a garage and workout. Garage, that they would do it a lot better than the veterans. That was the DOGE premise. And, DOGE doesn't exist anymore. So. Yeah. All right. Shall we leave it there? Let's leave it there. This has been another episode of the Odd Lots podcast. I'm Tracy Alloway. You can follow me @tracyalloway. And I'm Joe Weisenthal. You can follow me @thestalwart. Follow our guest, D.A. Wallach. He's @dawallach. Follow our producers, Carmen Rodriguez @carmenarmen, Dashiell Bennett @Dashbot, and Cale Brook @calebrooks. And for more Odd Lots content, you should definitely check out our daily newsletter. You can find that at bloomberg.com/OddLots And you can join fellow listeners in conversation 24 seven in our discord, discord.gg/oddlots And if you enjoyed this conversation, please like the video or leave a comment. Or better yet, subscribe! Thanks for watching.

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