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Speaker 1: Hello and welcome to another episode of the Odd Lots podcast.
Speaker 3: I'm Tracy Alloway.
Speaker 2: And I'm Joe Why isn't they Joe.
Speaker 3: We were doing a Q and A this morning.
Speaker 2: That's right.
Speaker 3: It's a lot of fun go on a live Q
Speaker 3: and A.
Speaker 1: And someone asked a question about whether or not we're
Speaker 1: going to do more healthcare episodes, and no, we don't,
Speaker 1: and there's a reason for that. I personally am incredibly
Speaker 1: intimidated by the US healthcare system. I do not understand
Speaker 1: it at all. It is just a complete mystery to me.
Speaker 1: But I was very happy to say in response to
Speaker 1: that question that this same day, that's right, we're actually
Speaker 1: recording a healthcare episode with someone that we've wanted to
Speaker 1: speak to for a long time.
Speaker 2: I'm the same way in the sense that, first of all, yes,
Speaker 2: I'm the same way in the sense that I really
Speaker 2: do not know much about how the healthcare system works.
Speaker 2: I don't even know where to begin asking the right questions.
Speaker 2: There is athing you do. You have to just start
Speaker 2: a random episode, and that gives you the germs of
Speaker 2: the next question, the next episode, the next episode. But
Speaker 2: they're so it seems so big and sprawling, etc. That
Speaker 2: what is the first question to ask? So we just
Speaker 2: have to plunge right in and just pick one which
Speaker 2: we're doing now, and then maybe that will lead to
Speaker 2: the string of healthcare episodes, which we should have done
Speaker 2: a long time.
Speaker 1: Again, that's exactly right. There's also a lot of new
Speaker 1: stuff happening in healthcare at the moment, and we recorded
Speaker 1: an episode on Chinese biotechs a little while ago that
Speaker 1: was incredibly fascinating. Definitely, I'm very curious to see what's
Speaker 1: going on on the US side of biotech and nesting,
Speaker 1: and we do have another episode plan that's sort of
Speaker 1: tangentially related to that. But clearly there's a lot to
Speaker 1: talk about. The other very odd lotsy thing with this
Speaker 1: guest is we like people who have interest in career histories, right.
Speaker 2: That's right. How how they got to where they are
Speaker 2: today is often a very interesting question. You know, I
Speaker 2: have nothing against people who just took the normal path,
Speaker 2: people who just sort of, you know, went to college
Speaker 2: and they got their NBA.
Speaker 3: And okay, you forgive them, I forgive them.
Speaker 2: That's totally fine. But it's also interesting to hear about
Speaker 2: the people who maybe walked in through the side door,
Speaker 2: so to speak.
Speaker 1: Absolutely so, we do, in fact have the perfect guest.
Speaker 1: We have someone who has a lot of thoughts on
Speaker 1: US healthcare and who is also a biotech investor and
Speaker 1: also formerly the lead singer of Chester French. So Da Wallack,
Speaker 1: Welcome to the show. Thanks so much for coming on.
Speaker 5: Thanks for having me, guys. I'm I'm a odd lots junkie.
Speaker 5: So this is like going to the Grammys.
Speaker 2: Amazing, Thank you ever Grammy. No, don't sorry, sorry, sorry,
Speaker 2: I shouldn't have I shouldn't have it.
Speaker 5: Not yet is the right answer.
Speaker 3: Not yet, not yet, not yet.
Speaker 1: I guess my first question should be, can you talk
Speaker 1: to us about the through line between being musician and
Speaker 1: healthcare and how and biotech and how you got into
Speaker 1: the space, because I think you know, it's not a
Speaker 1: natural transition, to say the least.
Speaker 5: Yeah, well, I'll tell you how I ended up doing this,
Speaker 5: and then I'll try to connect them theoretically in some way.
Speaker 5: It might be a little tenuous. I've basically had three
Speaker 5: careers so far in my limited adult life. I was
Speaker 5: a professional rock musician with the band that you mentioned
Speaker 5: for several years, and then I kind of slipped into
Speaker 5: the venture capital world when I invested in Spotify about
Speaker 5: thirteen years ago, and that was pretty much the only
Speaker 5: company in the private markets I was well positioned to
Speaker 5: understand as a musician, and through the success of that,
Speaker 5: I got turned on to how exciting venture capital was.
Speaker 5: Started doing other types of investments across different industries. Was
Speaker 5: involved in SpaceX and Ripple and a bunch of interesting
Speaker 5: other startups, and then ultimately a guy I knew started
Speaker 5: an early stage a healthcare company. It was a telemedicine
Speaker 5: startup called doctor on Demand, and telemedicine at the time
Speaker 5: was not a hot topic because this is pre COVID,
Speaker 5: so we still primarily went to the doctor in person.
Speaker 5: And when I made that investment, I started to learn
Speaker 5: more and more about our healthcare system and was just
Speaker 5: blown away by how screwed up and stupid it was.
Speaker 5: And then that eventually evolved into learning more about biotechnology
Speaker 5: and the other sub sectors of healthcare that are critical
Speaker 5: to medicine, and it's ended up being what I do.
Speaker 5: In terms of the connection between music and any of
Speaker 5: this stuff, there are a couple of ways I can
Speaker 5: think about it. One is, I tell people, now my
Speaker 5: job is like being a record producer for scientists, so
Speaker 5: there's a little bit of a parallel there. But the
Speaker 5: other is that I think there's a unique challenge in
Speaker 5: music to combining art and commerce, And in healthcare there's
Speaker 5: a similar parallel challenge, which is how do you combine
Speaker 5: medicine and capitalism, which don't naturally go together very well?
Speaker 2: Producer, analogy makes a ton of sense. And you know,
Speaker 2: there are probably a lot of musicians who are really brilliant,
Speaker 2: they're really great musicians, but for whatever reason, the lightning
Speaker 2: doesn't strike where they are or doesn't strike nearby, and
Speaker 2: they don't take off. Probably many brilliant scientists, et cetera,
Speaker 2: but the path from brilliant science to commercial blockbuster can often,
Speaker 2: I assume, be tricky or dispiriting in many ways, et cetera.
Speaker 2: Biotech specifically, of all the things in investing, biotech strikes
Speaker 2: me is this whole different world than the rest of
Speaker 2: like investing. You know, when I think of like a
Speaker 2: software company, it's like, oh, okay, well they've accumulated these
Speaker 2: clients and their churn is low, et cetera. Yeah, this
Speaker 2: seems like a company that has traction is going to grow.
Speaker 2: When it comes to biotech, it's like, okay, here's some
Speaker 2: patent on a sequence and maybe ten years from now
Speaker 2: it'll get approved to something that'll be a therapy. It
Speaker 2: seems so much harder to figure out, like what are
Speaker 2: the heuristics that one would use to establish this is
Speaker 2: a likely this science is likely going to turn into
Speaker 2: a business.
Speaker 5: Oh, that's absolutely true. It's like a completely different paradigm.
Speaker 5: As an investor, I think the typical biotech company is
Speaker 5: like a bag of options, and each one of the
Speaker 5: drugs that the company is working on in success could
Speaker 5: be worth billions of dollars, but that's ten years away
Speaker 5: often minimum, and so you're trying to price things based
Speaker 5: on their ultimate potential scale times their probability of succeeding,
Speaker 5: and unfortunately, the base rates in terms of probability of
Speaker 5: success are very low. So if you take small molecules,
Speaker 5: which is one major area of drugs, the base case
Speaker 5: is like a five percent probability of success from the
Speaker 5: original idea to an FDA approval and a marketed drug.
Speaker 5: Now you get to a higher sort of prior probability
Speaker 5: with antibodies or so called biologics other classes of drugs
Speaker 5: that are intrinsically more likely to work than small molecules,
Speaker 5: but still in every case you're dealing with very low
Speaker 5: probabilities of success, and the entire challenge as a biotech
Speaker 5: investor is how do you manage those low probability events
Speaker 5: and build portfolios that are still likely to make money
Speaker 5: despite the fact that each individual project is relatively unlikely
Speaker 5: to work. I'd say, in tech, there's this well described
Speaker 5: kind of power law distribution of winners and losers, which
Speaker 5: is to say, a very small number of companies make
Speaker 5: all the money and pay for the huge number of losers.
Speaker 5: In biotech, that's still true to a degree, but the
Speaker 5: magnitudes of the winners are lower, and so a really
Speaker 5: good biotech investor probably has a lower, sorry a higher
Speaker 5: batting average than the typical tech investor, but the wins
Speaker 5: are not as big.
Speaker 1: So one thing I'm really curious about is how you
Speaker 1: source potential investments and how you find you use the
Speaker 1: analogy of the record, how you find talent in the space,
Speaker 1: or how the talent kind of finds you, and whether
Speaker 1: or not it's different from again, the sort of software
Speaker 1: or tech space that we usually talk about when it
Speaker 1: comes to venture capital.
Speaker 5: You know, when I started doing venture investing, it was,
Speaker 5: like I said, twelve thirteen years ago, it was obviously
Speaker 5: a well established part of the capital markets. But you know,
Speaker 5: I cold emailed Brian Armstrong from coinbase and was meeting
Speaker 5: with them two days later. And it's hard to overstate
Speaker 5: how much money has rushed in over the past decades.
Speaker 5: So what went from being an established but still kind
Speaker 5: of marginal part of the capital markets is now all
Speaker 5: anyone thinks or talks about. And so in biotech, what
Speaker 5: I found getting into this area was that it was
Speaker 5: more like that venture market I had encountered. There was
Speaker 5: a scarcity of capital relative to the to the caliber
Speaker 5: of ideas that were out there, and so I'd say
Speaker 5: deal sourcing is much easier in a sense because there's
Speaker 5: less money chasing a huge number of good ideas, and
Speaker 5: those ideas, by and large do come out of our
Speaker 5: university and research infrastructure here in America. The same is
Speaker 5: also true in other parts of the world in Europe, China, India,
Speaker 5: and so forth. But it's really the translation of those
Speaker 5: academic concepts into products that could make money that is
Speaker 5: the challenge. That's the so called valley of death that
Speaker 5: people sometimes talk about in our industry. There are just
Speaker 5: an immense number of cool ideas. If you go into
Speaker 5: any university in our country, but such a small number
Speaker 5: of them is ever going to cross that chasm. And
Speaker 5: part of that is that the expertise and the personnel
Speaker 5: required to do that translational work is not the same
Speaker 5: expertise that is required to do the inventing in the
Speaker 5: first place. So that is really what the large pharmaceutical
Speaker 5: companies have a specialized expertise and they train people in
Speaker 5: this translational work. How do you go from early science
Speaker 5: to real products?
Speaker 2: When I go to a typical venture capitalist website or
Speaker 2: I see their Twitter bio or something like that, it'll
Speaker 2: say like, we bet great founders, and I'm like, thanks,
Speaker 2: that's very helpful because that distinguishes you from the venture
Speaker 2: capitalists who back crappy founders. So I'm glad I'm gonna
Speaker 2: invest with you. And said, what's the biotech equivalent? What's
Speaker 2: the cliche in your industry that every VC says that
Speaker 2: ostensibly distinguishes them from all the others.
Speaker 5: Well, I'm not sure what the vcs say. I mean,
Speaker 5: they are kind of commoditized in the sense that most
Speaker 5: of the firms look pretty similar. They employ thirty PhDs
Speaker 5: and physicians, and the value of those people is that
Speaker 5: they can make sense of the information that you have
Speaker 5: to process to invest intelligently in this space. In terms
Speaker 5: of what distinguishes the founders that they like to look at,
Speaker 5: I'd say again, it's kind of the inverse of what
Speaker 5: you find in tech. There's a real premium on quote
Speaker 5: gray hair in the biotech industry because the only way
Speaker 5: to learn this stuff is to do it over and
Speaker 5: over again and to have had a lot of failures.
Speaker 5: And if you think about a software company, the tropes
Speaker 5: you are familiar with are you know, fail fast, pivot right.
Speaker 5: You know, like, you launch something, it doesn't work, you
Speaker 5: tweak the product design, you go into a different market.
Speaker 5: You can adapt very readily to the market. In biotech,
Speaker 5: if you choose to embark upon a clinical program, you're
Speaker 5: in for thirty or forty million bucks, an easy door
Speaker 5: to walk back out of. And so there's a real
Speaker 5: premium on people with experience who have done it multiple times.
Speaker 5: That is a little bit at odds in recent years
Speaker 5: with a movement that people have I think awkwardly dubbed
Speaker 5: tech bio instead of biotech. And really these are Silicon
Speaker 5: Valley tech investors, not totally unlike myself, who have gotten
Speaker 5: into biotech, and they think that what's about to change
Speaker 5: is it's going to go the way of the tech
Speaker 5: industry and the next big companies are going to be
Speaker 5: started by really clever twenty one year olds coming out
Speaker 5: of Stanford and that hypothesis people have been testing now
Speaker 5: for a few years. I'd say it's a little too
Speaker 5: early to issue a verdict, but that's never really been
Speaker 5: our theory.
Speaker 1: Is that hypothesis just predicated on AI coming in and
Speaker 1: making you know, drug development easier.
Speaker 3: Is that all it is.
Speaker 5: There's a lot of that. I'd say there are two
Speaker 5: parts of it. One of it is maybe more substantive
Speaker 5: than that, and this is a little nuanced, but I
Speaker 5: know odd lots of people like Nuance one of the
Speaker 5: big transformations that really gave rise to the biotech industry.
Speaker 5: And when I use that term biotech, I'm distinguishing it
Speaker 5: from big pharma. So biotech really just means small drug companies,
Speaker 5: many of them are public. What really gave rise to
Speaker 5: that industry was the big pharmas at the behest of
Speaker 5: Wall Street deprioritized early stage research because Wall Street said,
Speaker 5: you're wasting a lot of money on this really risky
Speaker 5: early stage discovery work. What we would rather you did
Speaker 5: was just let all these crazy guys like da finance
Speaker 5: startups and once they work, just buy them. You know,
Speaker 5: you're going to pay a higher price, but you won't
Speaker 5: be burning all this money on early stuff. What that
Speaker 5: led to was an exodus a very specialized technical experts
Speaker 5: from the pharma companies, and it created the so called
Speaker 5: cro or contract research organization ecosystem. So you now, as
Speaker 5: a consequence of that, for the past twenty years, have
Speaker 5: had a very proficient environment full of contract organizations that
Speaker 5: you can hire as a little company to outsource a
Speaker 5: lot of work that you couldn't in the past. So
Speaker 5: the best analogy to to tech would be sort of
Speaker 5: like virtual servers or cloud infrastructure, Like you know, to
Speaker 5: have a startup, you used to have all these servers
Speaker 5: in your office, and then at some point you didn't
Speaker 5: need that, so the cost of new company formation went
Speaker 5: way down. So part of the argument for younger, more
Speaker 5: agile founders has been, look, we got this whole new
Speaker 5: kind of infrastructure through which they can build companies in
Speaker 5: a really agile way. The other argument, you know exactly
Speaker 5: your question, is around AI, and that is basically, look
Speaker 5: these old people don't understand AI. Let's get some young
Speaker 5: Silicon Valley computer science he types to do this, and
Speaker 5: they're gonna show them how it's done.
Speaker 2: I feel like that's probably a phenomenon that goes beyond biotech,
Speaker 2: where there's this fantasy, and maybe in some cases it's
Speaker 2: even correct, but there is this fantasy that every industry
Speaker 2: out there must be dominated by old dinosaurs who don't
Speaker 2: know how to use tech and who have been doing
Speaker 2: something the same way forever. And so you're twenty twenty five,
Speaker 2: it must be out of date by now and they
Speaker 2: haven't figured this out.
Speaker 3: And if we could just cough cough, journalism.
Speaker 2: Yeah right, if we could just hire wiz kids, then
Speaker 2: we could reinvent the industry from first principles and just
Speaker 2: do a much better job than the legacy of things.
Speaker 2: And I think, whether it's healthcare or whether it's industrial
Speaker 2: stuff that we see Silicon Valley getting excited about right now,
Speaker 2: it just feels like the default assumption must be that
Speaker 2: the veterans are doing something wrong, and with pure brain power,
Speaker 2: we could figure out what that thing is.
Speaker 5: I think that is a reasonable characterization or what people
Speaker 5: say today in a lot of different places, and I
Speaker 5: don't think it's true in my sector. But as with
Speaker 5: every conversation about AI, the challenge is balancing two ideas
Speaker 5: that can be true at the same time but seem contradictory.
Speaker 5: And one is that this stuff is amazing, and it is,
Speaker 5: particularly in life sciences, responsible for some true breakthroughs, like
Speaker 5: the breakthrough that won Demisisabus at deep Mind the Nobel
Speaker 5: Prize last year with alpha fold, which was this amazing
Speaker 5: discovery they made that using machine learning models you could
Speaker 5: solve a problem that had gone unsolved for decades, which
Speaker 5: was can you predict from the sequence of a protein's
Speaker 5: amino acids what three dimensional shape a protein is going
Speaker 5: to take in a physical environment. And I just threw
Speaker 5: around a bunch of terms of art. But this is
Speaker 5: fundamental to drug development and drug discovery. So it's like,
Speaker 5: on the one hand, you can't deny these breakthroughs that
Speaker 5: we're experiencing. You can't deny that when you talk to Gemini,
Speaker 5: it's staggering what this thing can do. I mean, I'm
Speaker 5: sitting there all day having it teach me about asset
Speaker 5: pricing models or whatever else I'm interested in. But at
Speaker 5: the same time, the religious movement that is powering all
Speaker 5: of the investment and a lot of the entrepreneurship here
Speaker 5: across industries is full of hot air and is making
Speaker 5: claims that are preposterous unless you are a zealot.
Speaker 2: Just real quickly, if we had been having this conversation
Speaker 2: in a month ago, would you have said Gemini or
Speaker 2: would you have said CHADJPT Because I switched from chad
Speaker 2: JPT to Gemini in the last month, and I'm just
Speaker 2: curious whether you're what you would have said a month ago.
Speaker 5: A month ago, I was using all of them. Now
Speaker 5: I'm only using Gemen.
Speaker 2: It's interesting, all right, good data plant.
Speaker 1: Okay, talk to us about the choke points when it
Speaker 1: comes to new drug development, because I imagine, okay, maybe
Speaker 1: AI machine learning can speed up some of the research
Speaker 1: or discovery process, but even after that, you have to
Speaker 1: go through these really long clinical trials that in some
Speaker 1: cases take decades. What are the major I guess, like
Speaker 1: stumbling blocks to getting something to the market.
Speaker 5: Your question held the answer. The process of taking a
Speaker 5: drug from idea to the market. You can think of
Speaker 5: as a funnel. To just use a visual analogy and
Speaker 5: into the top of the funnel, go all the millions
Speaker 5: of ideas that people have, and then as you go
Speaker 5: down the funnel, you are spending progressively more and more
Speaker 5: and more money to prove two things. The first is
Speaker 5: that the drug is safe and won't harm or kill people,
Speaker 5: and the second is that the drug works and actually
Speaker 5: modifies the disease that you're trying to treat. And the
Speaker 5: tragedy of our moment is that the only way to
Speaker 5: figure out if drugs are safe and effective is to
Speaker 5: try them in human beings, living, breathing human beings, and
Speaker 5: that is extraordinarily time consuming and incredibly expensive financially. So
Speaker 5: I wish for the day when AI is able to
Speaker 5: fully simulate an accurate human in the computer and we
Speaker 5: don't need to do clinical trials on real people. But
Speaker 5: until that moment, the vast majority of the cost and
Speaker 5: expense and time that is involved in drug discovery remains
Speaker 5: with us. So most of the AI technologies that people
Speaker 5: are excited about really would have the effect of putting
Speaker 5: more good ideas into the top of the funnel, But
Speaker 5: unfortunately that doesn't solve a problem that we have. We
Speaker 5: already are drowning in good ideas, and the issue is
Speaker 5: exactly the choke point or bottleneck that you're referring to.
Speaker 2: This is really there's actually two questions. First of all,
Speaker 2: is there low hanging fruit from a regulatory side to
Speaker 2: accelerate that process. People like to fathom, oh, the FDA
Speaker 2: must be super There's another area people will say, oh,
Speaker 2: the FDA must be super slow and do things one
Speaker 2: way we could expede this up. I don't know. Is
Speaker 2: there somewhere along the process where like from a regulatory
Speaker 2: standpoint or some other thing, that the either the cost
Speaker 2: of the timelines could shrink or is it mostly still
Speaker 2: just the reality of we have to test these things
Speaker 2: on humans and that's costly going, it takes time.
Speaker 5: Well, we don't need to do anything. We could have
Speaker 5: no FDA and anyone who has a good drug idea
Speaker 5: just launches it commercially and if some people die from
Speaker 5: that and it doesn't do anything, that's fine. By the way.
Speaker 5: That's kind of like the supplement yeah, time and the
Speaker 5: way we deal with it. Milton Friedman famously thought that
Speaker 5: the FDA should only assess the safety of drugs, and
Speaker 5: if a drug was proven safe, put it on the
Speaker 5: market and let the market dictate whether people determine they
Speaker 5: should pay for it based on their lived experience with
Speaker 5: whether it works or not. Now, I just personally prefer
Speaker 5: to live in a world where if I've got something
Speaker 5: that's going wrong, I can more or less trust that
Speaker 5: the product my doctor gives me has been proven safe
Speaker 5: and effective. And that reflects that we have today a
Speaker 5: pretty high bar for approving drugs. But we could certainly
Speaker 5: lower that bar. We could change the type of data
Speaker 5: that the FDA requires, And that's what's happening in China.
Speaker 5: By the way, I know you mentioned this other episode
Speaker 5: you did with my friend Tim. In China, the regulatory
Speaker 5: environment has been moving pretty rapidly, and they've done that
Speaker 5: deliberately because they want to be more productive. They want
Speaker 5: to approve more drugs, and they're trying to strike that
Speaker 5: balance between being prolific and holding things to a high
Speaker 5: standard at the same time. So you know, we'll see.
Speaker 2: And I just want to up and one other thing
Speaker 2: you said, because I think it seems important someone like
Speaker 2: Sam Altman, when he talks about the promise of AI,
Speaker 2: a lot of it is like, Oh, we could find
Speaker 2: the next drug that cures cancer. In the meantime, we're
Speaker 2: going to make this sort of slot machine that makes
Speaker 2: weird videos, et cetera. But really we're trying to find
Speaker 2: these wonder drugs in long term. But for what it
Speaker 2: sounds like you said, candidates are not where the shortages like.
Speaker 2: The issue is not that we lack sufficiently a number
Speaker 2: of sufficiently promising molecule combinations. The scarcity is not on
Speaker 2: that at that point.
Speaker 5: That's my view. I mean, I'll steal me in the
Speaker 5: other argument. The other argument would be, well, look, Dea,
Speaker 5: you said ten minutes ago that these drugs have a
Speaker 5: five percent probability of working from the outset. You know,
Speaker 5: if we had better predictive models that told us certain
Speaker 5: candidates were much more likely to work than others, wouldn't
Speaker 5: that be great? And my rejoinder to that is yes,
Speaker 5: but how would we know that we've done that? Meaning
Speaker 5: if the three of us tomorrow invented a black box
Speaker 5: that produced drug candidate concepts, and we were certain that
Speaker 5: our model doubled the prior probability from five percent to
Speaker 5: ten percent, that would be a truly revolutionary innovation on
Speaker 5: our part. But how many candidates from that model would
Speaker 5: we need to take all the way to an approval
Speaker 5: before we had statistically demonstrated that we in fact increased
Speaker 5: the rate of success. So people may have already cracked
Speaker 5: that code. You know, Google may have already cracked that code.
Speaker 5: Sam Waltman may have cracked that code. But someone's going
Speaker 5: to need to spend thirty billion dollars developing the drug
Speaker 5: ideas he has before we know whether he's done that,
Speaker 5: And until that money is spent, it's pure conjecture and salesmanship.
Speaker 1: How are you actually evaluating opportunities in the US against
Speaker 1: China competition, Because you know, if clinical trials are the
Speaker 1: major choke point, and if China seems to be trying
Speaker 1: to make that process as efficient as possible, it seems
Speaker 1: like maybe they have an advantage.
Speaker 5: I mean, they definitely have an advantage. And if I
Speaker 5: had to make a bet today on our sector, it
Speaker 5: would be that China is going to be the big
Speaker 5: story over the next decade or two. I think it's
Speaker 5: a fundamental structural shift in the global biotechnology market. And
Speaker 5: their advantages are multiple. I mean, their advantages are regulatory,
Speaker 5: they relate to the personnel. We have lost an amazing
Speaker 5: amount of talent who was educated here in our graduate
Speaker 5: schools and now has gone back to China. And furthermore,
Speaker 5: they are able to develop things in the clinic, which
Speaker 5: is to say, do clinical trials a lot faster and
Speaker 5: at a much higher volume than our infrastructure can handle.
Speaker 5: So they've got big advantages. Now, how do I think
Speaker 5: about investing in the US versus China. I don't that
Speaker 5: much because I don't speak Mandarin, and I think it
Speaker 5: would be really difficult for me to invest in China today.
Speaker 5: But increasingly companies in the US are starting to outsource
Speaker 5: certain parts of the research process to Chinese companies, and
Speaker 5: increasingly they're going to outsource parts of the clinical development process,
Speaker 5: the clinical trials to China. That's going to make a
Speaker 5: huge impact on the AUA.
Speaker 1: Yeah, this was actually my next question. I guess how
Speaker 1: translatable is a successful clinical trial in China to a
Speaker 1: market like the US.
Speaker 5: Three or four years ago, what both investors and regulators
Speaker 5: in the US would have told you was that it's
Speaker 5: not that translatable because they're liars and they make up
Speaker 5: all the data, and it's rampant with fraud. And there
Speaker 5: may have been some truth to that, but I think
Speaker 5: there was also a good amount of racism and what
Speaker 5: sort of woke everyone up in the past couple of
Speaker 5: years was that some very significant clinical trials were done
Speaker 5: in China. People were suspicious of the data. Then they
Speaker 5: replicated those trials in Europe or the United States and
Speaker 5: got very similar data, and folks thought, WHOA, maybe they're
Speaker 5: not so bad at this. So I think decreasingly people
Speaker 5: are skeptical, and which said less awkwardly, people are trusting
Speaker 5: more and more what's coming out of China. And it's
Speaker 5: incumbent upon the Chinese to the extent that they want
Speaker 5: this to be a major strategy to continue enhancing people's
Speaker 5: trust in the quality of their work and their data.
Speaker 5: If they can do that. I think it's a global industry.
Speaker 5: A lot of the companies are multinationals. They don't care
Speaker 5: if the drug comes out of the US or comes
Speaker 5: out of China.
Speaker 2: This is a really good question about private or VC
Speaker 2: stage investing per se, but about biotech more broadly. You know,
Speaker 2: I've covered the stock market for a long time in
Speaker 2: various ways. I've never spent any time really getting to
Speaker 2: know a publicly traded biotech doc is, are you insane
Speaker 2: to try to invest in biotech if you don't have PhD?
Speaker 2: Level understanding of biology, Like, can anyone have alpha in
Speaker 2: this industry if they don't actually know science.
Speaker 5: I think it's tough.
Speaker 2: Yeah, it seems very tough to you me.
Speaker 5: Look, yeah, I mean, here's the thing. What's really interesting
Speaker 5: about biotech in the public markets is it's abundantly clear
Speaker 5: that active investors can have alpha in biotech, whereas as
Speaker 5: you guys know, that is not clear in the rest
Speaker 5: of the public equity landscape. And so whereas there is
Speaker 5: very little, if not negative persistence of performance among active
Speaker 5: equity managers broadly, in biotech, you have a small number
Speaker 5: of firms that have been doing great for sometimes decades,
Speaker 5: and it.
Speaker 2: Is and they all have real science expertise on Stowe
Speaker 2: they do.
Speaker 5: And you know, the dynamic between them and the generalists,
Speaker 5: so to speak, is that they do a lot of
Speaker 5: very detailed work to make sense of the information you
Speaker 5: need to process to value these companies and to assess
Speaker 5: their probability of success. And then the generalists often follow
Speaker 5: those specialists into these names and the fortunes of the
Speaker 5: industry in these cycles, like we're coming out of a
Speaker 5: four year great depression for biotech, I should just mention
Speaker 5: a lot of those fortunes ride on the sector rotations
Speaker 5: of the generalists. So the specialists have to stick with
Speaker 5: biotech because that's what they do. But whether or not
Speaker 5: companies can IPO, whether or not companies can fund their
Speaker 5: next clinical trial, is largely a function of whether the
Speaker 5: generalists are in the sector at that moment or not.
Speaker 5: And we're just in the midst of the early rotation
Speaker 5: of generalists.
Speaker 1: Back into wait, the biotech investing downturn, was that just
Speaker 1: a function of higher interest rates or was something else
Speaker 1: going on?
Speaker 5: It was a confluence of everything that could go wrong
Speaker 5: at the same time. It was higher interest rates, which
Speaker 5: really punished these biotech stocks relative to other companies because
Speaker 5: you know, no cash flows for ten years and then
Speaker 5: a big bowl of some money. So these companies are
Speaker 5: very sensitive to discount rates. Add to that this dynamic
Speaker 5: where the generalists had gotten out of the sector, that
Speaker 5: ultimately is fatal. And then consider the fact that we
Speaker 5: had such a come down after the sugar high of COVID.
Speaker 5: So obviously during COVID there was this moment of clarity
Speaker 5: where everyone for a second recognized that this sector is
Speaker 5: for each of us at some point in our lives.
Speaker 5: The most important thing that happens in the global economy.
Speaker 5: Like without the biotech industry, you know, we're all in trouble.
Speaker 5: And we kind of go through life pretending like we're
Speaker 5: never going to need this industry, and then you get cancer,
Speaker 5: your dad gets cancer, your kid gets some rare disease,
Speaker 5: and you go, holy cow. I wish I had thought
Speaker 5: about this before. Maybe all these people who are doing
Speaker 5: this with their lives are not evil bloodsuckers who Bernie
Speaker 5: Sanders needs to take down. And that is I think
Speaker 5: part of what dawned on people during COVID, when we
Speaker 5: all were vulnerable and we all were yearning for a solution.
Speaker 1: Talk a little bit more about, I guess, the financial
Speaker 1: incentives about actually developing new drugs. So we all know
Speaker 1: the story of if you're based in the US, you
Speaker 1: can go to Mexico or wherever else and buy the
Speaker 1: same medicine for like five bucks as opposed to five
Speaker 1: hundred dollars or perhaps even more in the US. And
Speaker 1: the argument for that seems to be that, well, you know,
Speaker 1: the big pharma companies need to be rewarded for all
Speaker 1: the research and the effort, the risk that they actually
Speaker 1: take on and for some reason, the US seems to
Speaker 1: be the designated place to do that.
Speaker 3: But like, why why? Is my question? Why US drugs?
Speaker 5: Well, the big bounty for a drug development company is
Speaker 5: the United States market, and that's partly because we as
Speaker 5: a society have decided that we want all the new,
Speaker 5: most advanced drugs. We want them first, and we don't
Speaker 5: want to deny them to people who could benefit from them. Now,
Speaker 5: the price we pay for those commitments is that our
Speaker 5: drug prices are higher than the prices in other countries.
Speaker 5: And the reason their prices are lower is because their
Speaker 5: governments choose which drugs their people will have access to,
Speaker 5: and they make those choices and then negotiate the prices
Speaker 5: with the companies, and they basically will say to Pfizer
Speaker 5: or Astro Zeneca, look, if you want your drugs sold
Speaker 5: here in Japan, you're going to take the price that
Speaker 5: we give you, and then the pharma company decides whether
Speaker 5: they want to accept that deal or not. Now, the
Speaker 5: United States absolutely could choose as a civilization to negotiate
Speaker 5: in that same manner. Our government could make the choice
Speaker 5: for US as to exactly what we're willing to pay
Speaker 5: for every drug. There would be two consequences to that.
Speaker 5: One is that we would go without certain drugs. The
Speaker 5: second is that a lot of drugs would not even
Speaker 5: be developed in the first place, because the total pool
Speaker 5: of profits available to drug companies would be much smaller.
Speaker 5: And so I don't know that there is any perfect
Speaker 5: answer to how much pharmaceutical innovation we should have in
Speaker 5: the world. We get to choose how much innovation we
Speaker 5: want to occur, and the way we choose that is
Speaker 5: by determining the size of that bounty that exists. How
Speaker 5: big is the profit pool we want to allow for
Speaker 5: innovative drug development, and a lot of that is driven
Speaker 5: by our patent law. Remember, a patent in this industry
Speaker 5: is a legalized monopoly. So we give drug companies a
Speaker 5: legal monopoly for a limited period of time, and that
Speaker 5: dictates how much money they're able to make off of
Speaker 5: a new drug. We could shorten the patent life, and
Speaker 5: that would reduce the profit pool and you'd have less
Speaker 5: drug development. We could remove the patent life, you could
Speaker 5: have a permanent monopoly, and believe me, the industry would
Speaker 5: double or triple overnight. So it's a choice we have
Speaker 5: to make, and it's a civic choice.
Speaker 2: You mentioned the Bernie Sanders of the world, who they
Speaker 2: look at the profits of drug companies, or they look
Speaker 2: at the prices of drugs, and you know if perhaps
Speaker 2: if they got their way, there would be less investment
Speaker 2: in drug discovery, etc. At all, maybe less profits. Going
Speaker 2: back to COVID. However, there was also the backlash on
Speaker 2: the other side, essentially just this deep skepticism towards the
Speaker 2: premise of pharma and that what are these scientists doing
Speaker 2: and why don't they tell you about this root the
Speaker 2: people have used for thousands of years that cured these
Speaker 2: diseases that they don't want you to know about so
Speaker 2: that they can sell your stuff, talk to us about
Speaker 2: like just this sort of political environment investing in biotech
Speaker 2: in a political environment, or a growing number of people
Speaker 2: frankly seem to distrust the premise of scientific expertise.
Speaker 5: Look, it's tough, and some of the blame certainly belongs
Speaker 5: with the scientific community, because you know, to the extent that, say,
Speaker 5: in the early days of COVID, communication with the public
Speaker 5: about say, the value of masks was not clear and
Speaker 5: it was maybe even misleading. Some of the presentation of
Speaker 5: data regarding the efficacy of the vaccines was not transparent,
Speaker 5: and that eroded the public's trust in a very understandable way. Now,
Speaker 5: I'm no apologist for medicine or science, because I don't
Speaker 5: think these are privileged priesthoods. I think every person should
Speaker 5: be able to be engaged in and understand science and medicine.
Speaker 5: And unfortunately, the entire history of medicine began with medical
Speaker 5: science as total witchcraft and sorcery. So if you go
Speaker 5: back to antiquity, the first people calling themselves doctors objectively
Speaker 5: understood nothing. So this was pure sophistry from the beginning.
Speaker 5: And we are on this long journey through which medicine
Speaker 5: is going from total bs and witchcraft to slowly turning
Speaker 5: into a real science, something that deserves to be called science.
Speaker 5: Medicine is filled with common practices that are not rigorously
Speaker 5: based on evidence, and that is symptomatic of where we
Speaker 5: are in that journey that I'm describing. So I'm an
Speaker 5: advocate for medicine becoming always more and more scientific. I
Speaker 5: believe that scientific policymakers, scientists, and academia need to do
Speaker 5: a much better job communicating transparently, and that's the only
Speaker 5: way to engender that kind of trust you're talking about, Joe,
Speaker 5: and the trust is critical because it is what gives
Speaker 5: permission to this industry's existence.
Speaker 1: Wait, talk more about I guess autonomy when it comes
Speaker 1: to medical decisions, because this is, you know, a big
Speaker 1: culture shock of non Americans who come to the US
Speaker 1: is drug adverts on TV where they you know, here's
Speaker 1: this great drug, and then they read off all the
Speaker 1: risk factors really really quickly, and one of the risks
Speaker 1: is always death or so your brain damage. You're something yeah,
Speaker 1: and I'm always like, again, I've never asked for a
Speaker 1: drug that I've seen on TV. I do remember when
Speaker 1: I when I first came to the US as an adult,
Speaker 1: I went to get a prescription. I found a new
Speaker 1: doctor to do that, and I said I needed this
Speaker 1: thing and the doctor was like, oh, well, we have
Speaker 1: to run all these medical tests before we can give
Speaker 1: you that, and it ended up in a big argument
Speaker 1: with my insurance provider. And I remember talking to people
Speaker 1: about that and they were like, well, you should have
Speaker 1: pushed back against the doctor about the testing, and I
Speaker 1: was like, what do I know? I just do what
Speaker 1: the doctor tells me, right, how much say should people?
Speaker 5: Actually?
Speaker 1: It sounds weird but you know, given the lack of experience,
Speaker 1: and given the way other systems work around the world,
Speaker 1: how much, say, should people have in their own medical treatment.
Speaker 5: I think ultimately they should have almost all of the say,
Speaker 5: it's your body. Ultimately, you have to make the best
Speaker 5: decision you can make, and you should regard physicians, nurses,
Speaker 5: others in the system as consultants who support you in
Speaker 5: making wise decisions. The one caveat there, however, is that
Speaker 5: we do socialize a lot of our medical costs, and
Speaker 5: in many other countries they completely socialize medical costs to
Speaker 5: the extent that you want the rest of us to
Speaker 5: pay for your medical care. I do believe we need
Speaker 5: to have some standards around what it's appropriate to pay for.
Speaker 1: Yeah, I mean, at the moment, it seems like most
Speaker 1: of those decisions are left up to the insurers, which again,
Speaker 1: in other places in the world, it would be left
Speaker 1: up to the governments to make those decisions. Are insurers
Speaker 1: the sort of another limiting factor here?
Speaker 5: I believe they are. I believe the private insurance industry
Speaker 5: adds zero value to the United States healthcare system almost that.
Speaker 5: I mean that may slightly overstate it, but it's close
Speaker 5: to zero in my book, and I really don't believe
Speaker 5: insurance companies ought to be the ones making decisions about
Speaker 5: what medical care is appropriate.
Speaker 2: I notice they're in the video. You have a really
Speaker 2: nice looking microphone? Is that a musical? Is that a
Speaker 2: microphone for recording music?
Speaker 5: Yeah? This is the one I uh, this is the
Speaker 5: one I sing on.
Speaker 2: It's it's first of all, you sound good, but it
Speaker 2: also looks a lot cooler than the typical microphone that
Speaker 2: are that our guests to is do you do you?
Speaker 2: Are you still? Are you still playing much music?
Speaker 5: I do, but but thankfully now it's just for fun
Speaker 5: not for money, which is a much more comfortable place
Speaker 5: for it to live in my life.
Speaker 2: Are you do you think it all about AI generated music?
Speaker 2: And uh, the effect that that's going to have on musicians.
Speaker 2: I feel like a lot of musicians, like the ones
Speaker 2: that I follow on Instagram, is there have a lot
Speaker 2: of anxiety about this.
Speaker 5: There is anxiety, And look, I mean it's really hard
Speaker 5: to make a living as a musician now It's always
Speaker 5: been really hard, and you know, I can't imagine what
Speaker 5: the lifestyle was of a loot player in George the
Speaker 5: Second Royal Court or something but you know, it's a
Speaker 5: tough business and it is scary when new technology comes
Speaker 5: on the scene that might change the way you make
Speaker 5: money as an artist. I live through that with Spotify,
Speaker 5: people were terrified of it, and you know, fortunately what
Speaker 5: it did.
Speaker 2: Over done what you did at long Spotify and then
Speaker 2: hedge their own risk to it. But keep going.
Speaker 5: No, but looks spot Spotify by multiples increased the total
Speaker 5: revenue of the recorded music business, which was the goal.
Speaker 5: So mission accomplished. Now, look, AI is going to make music,
Speaker 5: and I think like all creative people, like journalists, like investors,
Speaker 5: everyone's going to think about how they can use it
Speaker 5: to be more effective, have more leverage, have a cooler output.
Speaker 5: I mean, I have very little doubt that artists are
Speaker 5: going to do unbelievably cool and original stuff with AI tools,
Speaker 5: and it's already happening, and for whatever reason, I have
Speaker 5: very little trepidation that they're going to be put out
Speaker 5: of business because I think ultimately music is communication and.
Speaker 2: Real quickly on that when you talk about like doing
Speaker 2: unbelievably cool things with music. So I see in the
Speaker 2: background you have a piano, for example, and one of
Speaker 2: the things when I think about AI music is and
Speaker 2: actually I think, like for example, the founder of Suno
Speaker 2: and some of these other AI music companies have talked
Speaker 2: about this is like, well, music, learning to play instruments
Speaker 2: is really hard, and therefore, can we separate in some
Speaker 2: way the craft of music, the hours that someone has
Speaker 2: to spend just doing scales on the piano before they
Speaker 2: can compose something. Maybe you could what wouldn't it be
Speaker 2: nice if we could just have amazing, beautiful piano sonatas
Speaker 2: without ever having had both put in those thousands of hours.
Speaker 2: You know, Mary had a little lamb and then so forth.
Speaker 2: But it does raise the question to my mind of
Speaker 2: whether one can create great art if they never had
Speaker 2: to learn the craft.
Speaker 5: I think the nuance with which one can communicate through
Speaker 5: music is a function of how many options you perceive.
Speaker 5: In other words, if you know the piano inside out,
Speaker 5: you're aware of so many creative choices that are at
Speaker 5: your disposal at any given moment. And if your ability
Speaker 5: to express yourself is squeezed down to what you can
Speaker 5: put into a natural language prompt, now those musical ideas
Speaker 5: are having to pass through the medium of language to
Speaker 5: be realized, and that inherently erodes the resolution and the
Speaker 5: expansiveness with which you can express yourself.
Speaker 1: I feel like there's a danger here that you go
Speaker 1: off on a big orality tangent and whether ideas can
Speaker 1: exist without words and things like that.
Speaker 2: No, but I do think this that answered very deciightful, Like,
Speaker 2: can you actually create great piano music if you don't
Speaker 2: know the limits of what the piano can do and
Speaker 2: if you're only trying to describe in language, make this
Speaker 2: beautiful sonata? I think that's very tough. But I thought
Speaker 2: that answer made last time.
Speaker 3: DA.
Speaker 1: We're gonna have to wrap it up soon. I have
Speaker 1: one last question, and I'm gonna kind of I'm gonna
Speaker 1: put you on the spot. Can you can you sing
Speaker 1: a little odd lot song for us? Like three bars
Speaker 1: of an odd lot song? I don't care if you
Speaker 1: generate it with you know, I guess Gemini now, but.
Speaker 5: Do you think you could Let's see? I mean, oh wow,
Speaker 5: I'm gonna turn this. Let's see here.
Speaker 2: This is really cool. Yeah, if you came, you are
Speaker 2: watching the video. So he's moving his microphone, he's moving
Speaker 2: his microphone to his keyboard.
Speaker 5: Okay, can you see great?
Speaker 2: Yeah? Go for it?
Speaker 5: Okay, We're gonna try.
Speaker 6: And it's all about it's all about It's all about Tracy,
Speaker 6: It's all about it's all about it's all about Joe.
Speaker 5: How's that pretty good?
Speaker 2: You have a great voice.
Speaker 3: Yeah it is.
Speaker 2: Do you ever want to compose an outro song for uh? Yeah,
Speaker 2: something like that?
Speaker 5: Oh, I would love to. I'm I'm. I am the
Speaker 5: composer of two or three podcast theme songs. And I
Speaker 5: have to say, I love your guys theme music. It
Speaker 5: gets me excited. And I got to end on this
Speaker 5: for you guys. You know, in high school the reason
Speaker 5: I got into investing. In high school, I was an
Speaker 5: economics nerd. Oh yeah, I heard and my.
Speaker 1: Hobby, we heard that you actually wrote like some a
Speaker 1: paper that won like a prize from the FED or
Speaker 1: something like that.
Speaker 5: So the Federal Reserve had this nerd competition they sponsored
Speaker 5: called FED Challenge. And I was the captain of my
Speaker 5: high school team one year and we got to DC
Speaker 5: and we we saw Green Span walk out with his
Speaker 5: wizened face and hands. And anyways, if I had had
Speaker 5: odd lots to listen to in high school, man, I
Speaker 5: would have been in heaven because you guys touch on
Speaker 5: so much interesting stuff, and this just has to be
Speaker 5: the most exciting thing for young people to experience in
Speaker 5: order to get turned onto business and economics and finance
Speaker 5: and recognize these aren't just boring, you know, staid topics.
Speaker 5: They're fascinating.
Speaker 1: Thank you for saying that. I really appreciate it, and
Speaker 1: also thank you for singing for us. I think that
Speaker 1: was an all thoughts first. Yeah, yeah, well on the spot.
Speaker 1: I know we've had merl Hazard the country Singing Economist
Speaker 1: on before, but that was fantastic day.
Speaker 3: Wallack, thank you so much for coming on the show.
Speaker 3: Really appreciate it. Thanks you, guys, than for that was great.
Speaker 3: That was really interesting.
Speaker 2: Joe, that was super fun. He was great.
Speaker 1: He's also pretty good at you know. I know again
Speaker 1: he said it was tenuous, but the through line from
Speaker 1: music to biotech kind of makes sense.
Speaker 2: I think it makes a lot of sense. And the
Speaker 2: especially the fact that you know these are extreme. These
Speaker 2: are all startup investing. We know, you know, there's this
Speaker 2: power law phenomenon where one of your twenty portfolio company
Speaker 2: is going to make all the money.
Speaker 3: Yeah, the lottery ticket, but you.
Speaker 2: Know, like biotech is like lottery tickets upon lottery tickets
Speaker 2: there's so much success uncertainty.
Speaker 1: There's so much with lower payouts as.
Speaker 2: Lower payouts, there's so much success uncertainty. There's so much
Speaker 2: time that elapses between the initial work and where you
Speaker 2: see if there's any signals of traction. It does feel
Speaker 2: a lot like the uncertainty that exists in the music
Speaker 2: industry and selecting which of these hundred bands that all
Speaker 2: sound great and they're all really talented, actually has what
Speaker 2: it takes to be a commercial hit. A lot of parallels.
Speaker 1: Yeah, I thought that the dinosaur bias point was an
Speaker 1: interesting one as well, because you can imagine, like again
Speaker 1: to the timeline point, you kind of have to be
Speaker 1: old to have any success in the industry historically, just
Speaker 1: because it can take you know, a decade to get
Speaker 1: a particular drug to market, so you don't have that
Speaker 1: much opportunity to have you know, those wins unless you
Speaker 1: get old and.
Speaker 2: There's no shortage. There's no you know, there may be
Speaker 2: regulatory things that can be done, but fundamentally, if you
Speaker 2: want to know whether something works, and if you want
Speaker 2: to know whether this drug is going to kill people
Speaker 2: who take it or not, and whether it's safe or not,
Speaker 2: there is no substitute for doing a test and seeing
Speaker 2: what happens. And to your point or to your observation
Speaker 2: about the dinosaurs, like I do think that lots of
Speaker 2: people have this fantasy that anytime there is a legacy
Speaker 2: industry of any sort, that if you just got twenty
Speaker 2: one year olds from Stanford in the same room.
Speaker 3: They gave them a garage to work out.
Speaker 2: Garage, that they would do it a lot better than
Speaker 2: the veterans. That was the Doge premise, and Doge doesn't
Speaker 2: exist anymore.
Speaker 3: So yeah, shall we leave it there.
Speaker 2: Let's leave it there.
Speaker 1: This has been another episode of the All Thoughts podcast.
Speaker 1: I'm Tracy Alloway. You can follow me at Tracy Alloway.
Speaker 2: And I'm Joe wasn't Thal. You can follow me at
Speaker 2: the Stalwart, follow our guesst d A Wallack He's at
Speaker 2: d A Wallack. Follow our producers Carmen Rodriguez at Carmen
Speaker 2: armand Dashel Bennett a Dashboy, and kill Brooks at Kilbrooks.
Speaker 2: From our Oddlots content, go to Bloomberg dot com slash
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Speaker 3: Thanks for listening, oh