December 12, 2025 • 50 mins
Most people think of venture capital as funding software startups or, these days, some new AI tool. But VC also plays a major role in developing new medicines and treatments. That’s the world of D.A. Wallach — though he didn’t start there. Before becoming a biotech investor, Wallach was the lead singer of the indie rock band Chester French. So how did he make the leap from music to venture capital? How does he spot promising biotech opportunities? What does it actually take to bring a new drug to market? And how does biotech investing differ from traditional VC? We talk to the co-founder of Time BioVentures about all of this — plus we get his thoughts on AI’s impact on music and a special performance.
Have a question for Joe and Tracy? Now's your chance to be the perfect guest - record a voice memo with your name, age, location and question and email to oddlots@bloomberg.net for a chance to be included in the holiday AMA episode.
Read More:
Big Pharma’s Patent Cliff Puts China Front and Center
Novartis Strikes Deal With UK Biotech for Up To $1.7 Billion
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
Hey, they're aud Loots listeners. It is that time of
the year again. We are going to be doing a
call in show on the podcast. You can ask us
any of your burning questions.
Speaker 2 (00:12):
That's right. You want to ask us about finance, markets
and economics, go for it. You want to ask us
about the year in podcasting, go for it. You want
to ask about where Tracy is with growing chicken or
raising chicken, growing chickens, raising chickens on her versioning firm
in Connecticut, go for it. This is your chance to
(00:33):
ask us anything.
Speaker 3 (00:34):
Joe's favorite cut of steak.
Speaker 2 (00:36):
Right, my favorite cut of steak, my favorite Chinese restaurant
in the East Village. It's all fair game, all right.
Speaker 1 (00:41):
All you have to do is send a voice memo
with your question, your name, your age, and your location
to od Loots at Bloomberg dot net.
Speaker 2 (00:51):
Deadline to submit is December seventeenth, So get the men,
assume as you can.
Speaker 1 (00:55):
We're looking forward to hearing what you have to ask
and yeah, that's coming up.
Speaker 4 (01:02):
Bloomberg Audio Studios, Podcasts, Radio News.
Speaker 1 (01:18):
Hello and welcome to another episode of the Odd Lots podcast.
Speaker 3 (01:21):
I'm Tracy Alloway.
Speaker 2 (01:22):
And I'm Joe Why isn't they Joe.
Speaker 3 (01:23):
We were doing a Q and A this morning.
Speaker 2 (01:25):
That's right.
Speaker 3 (01:26):
It's a lot of fun go on a live Q
and A.
Speaker 1 (01:29):
And someone asked a question about whether or not we're
going to do more healthcare episodes, and no, we don't,
and there's a reason for that. I personally am incredibly
intimidated by the US healthcare 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
(01:51):
that question that this same day, that's right, we're actually
recording a healthcare episode with someone that we've wanted to
speak to for a long time.
Speaker 2 (02:01):
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 healthcare system works.
I don't even know where to begin asking the right questions.
There is athing 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
they're so it seems so big and sprawling, etc. That
(02:21):
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 healthcare episodes, which we should have done
a long time.
Speaker 1 (02:32):
Again, that's exactly right. There's also a lot of new
stuff happening in healthcare at the moment, and we 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 US side of biotech and nesting,
and we do have another episode plan that's sort of
tangentially related to that. But clearly there's a lot to
(02:53):
talk about. The other very odd lotsy thing with this
guest is we like people who have interest in career histories, right.
Speaker 2 (03:01):
That's right. How 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 they got their NBA.
Speaker 3 (03:14):
And okay, you forgive them, I forgive them.
Speaker 2 (03:16):
That's totally fine. But it's also interesting to hear about
the people who maybe walked in through the side door,
so to speak.
Speaker 1 (03:22):
Absolutely so, we do, in fact have the perfect guest.
We have someone who has a lot of thoughts on
US healthcare and who is also a biotech investor and
also formerly the lead singer of Chester French. So Da Wallack,
Welcome to the show. Thanks so much for coming on.
Speaker 5 (03:39):
Thanks for having me, guys. I'm I'm a odd lots junkie.
So this is like going to the Grammys.
Speaker 2 (03:45):
Amazing, Thank you ever Grammy. No, don't sorry, sorry, sorry,
I shouldn't have I shouldn't have it.
Speaker 5 (03:52):
Not yet is the right answer.
Speaker 3 (03:53):
Not yet, not yet, not yet.
Speaker 1 (03:55):
I guess my first question should be, can you talk
to us about the through line between being musician and
healthcare and how and biotech and how you got into
the space, because I think you know, it's not a
natural transition, to say the least.
Speaker 5 (04:10):
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 about
(04:32):
thirteen 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 SpaceX and Ripple and a bunch of interesting
other startups, and then ultimately a guy I knew started
(04:56):
an early stage a healthcare 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,
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 healthcare system and was just
blown away by how screwed up and stupid it was.
(05:18):
And then that eventually evolved into learning more about biotechnology
and the other sub sectors of healthcare 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
(05:40):
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, And in healthcare there's
a similar parallel challenge, which is how do you combine
medicine and capitalism, which don't naturally go together very well?
Speaker 2 (06:00):
Producer, analogy makes a ton of sense. And you know,
there are probably a lot of musicians who are really brilliant,
they're 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, et cetera,
but the path from brilliant science to commercial blockbuster can often,
I assume, be tricky or dispiriting in many ways, et cetera.
(06:23):
Biotech specifically, of all the things in investing, biotech strikes
me is 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, et cetera. 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
(06:46):
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.
Speaker 5 (07:02):
Oh, that's absolutely true. 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
(07:23):
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 five percent probability of success from the
(07:44):
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
(08:04):
probabilities of success, and the entire challenge as a biotech
investor is 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
(08:26):
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 wins
(08:48):
are not as big.
Speaker 1 (08:50):
So one thing I'm really curious about is how you
source potential investments and how you find you use the
analogy of the record, 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 software
or tech space that we usually talk about when it
(09:12):
comes to venture capital.
Speaker 5 (09:14):
You know, when I started doing venture investing, it was,
like I said, twelve thirteen 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 decades.
(09:37):
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. 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 to the caliber
(09:57):
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 a 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,
(10:20):
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. There are just
an immense number of cool ideas. If you go into
(10:41):
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. So that is really what the large pharmaceutical
(11:03):
companies have a specialized expertise and they train people in
this translational work. How do you go from early science
to real products?
Speaker 2 (11:29):
When I go to a typical venture capitalist website or
I see their Twitter bio or something like that, it'll
say like, we bet great founders, and I'm like, thanks,
that's very helpful because that distinguishes you from the venture
capitalists who back crappy founders. So I'm glad I'm gonna
invest with you. And said, what's the biotech equivalent? What's
the cliche in your industry that every VC says that
(11:51):
ostensibly distinguishes them from all the others.
Speaker 5 (11:55):
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 thirty 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
(12:16):
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 to have had a lot of failures.
(12:36):
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, it 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
(12:57):
in for thirty or forty million bucks, an easy door
to walk back out of. 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
(13:20):
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 twenty one year olds coming out
of Stanford and that hypothesis people have been testing now
(13:42):
for a few years. I'd say it's a little too
early to issue a verdict, but that's never really been
our theory.
Speaker 1 (13:50):
Is that hypothesis just predicated on AI coming in and
making you know, drug development easier.
Speaker 3 (13:56):
Is that all it is.
Speaker 5 (13:58):
There's a lot of that. I'd say there are two
parts of it. One of it is maybe more substantive
than that, and this is a little nuanced, but I
know odd lots of people like Nuance 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,
(14:21):
many of them are public. What really gave rise to
that industry was the big pharmas 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
(14:43):
was just let all these crazy guys like da finance
startups and once they work, just buy them. 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 a very specialized technical experts
from the pharma companies, and it created the so called
(15:04):
cro or contract research organization ecosystem. So you now, as
a consequence of that, for the past twenty 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
(15:25):
the best analogy to 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
(15:48):
kind of infrastructure through which they can build companies in
a really agile way. The other argument, you know exactly
your question, is around AI, and that is basically, look
these old people don't understand AI. Let's get some young
Silicon Valley computer science he types to do this, and
they're gonna show them how it's done.
Speaker 2 (16:10):
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 you're twenty twenty five,
(16:32):
it must be out of date by now and they
haven't figured this out.
Speaker 3 (16:35):
And if we could just cough cough, journalism.
Speaker 2 (16:38):
Yeah right, if we could just hire wiz kids, then
we could reinvent the industry from first principles and just
do a much better job than the legacy of things.
And I think, whether it's healthcare 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 brain power,
(17:01):
we could figure out what that thing is.
Speaker 5 (17:04):
I think that is a reasonable characterization or what people
say today 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.
(17:25):
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 Demisisabus at deep Mind the Nobel
Prize last year with alpha fold, which was this amazing
discovery they made that using machine learning models you could
(17:47):
solve a problem that had gone unsolved for decades, which
was can you predict from the sequence of a protein's
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
(18:08):
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
(18:28):
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.
Speaker 2 (18:44):
Just real quickly, if we had been having this conversation
in a month ago, would you have said Gemini or
would you have said CHADJPT Because I switched from chad
JPT to Gemini in the last month, and I'm just
curious whether you're what you would have said a month ago.
Speaker 5 (18:57):
A month ago, I was using all of them. Now
I'm only using Gemen.
Speaker 2 (19:01):
It's interesting, all right, good data plant.
Speaker 1 (19:03):
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 are the major I guess, like
(19:24):
stumbling blocks to getting something to the market.
Speaker 5 (19:29):
Your question held the answer. 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
(19:49):
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 actually
modifies the disease that you're trying to treat. And the
tragedy of our moment is that the only way to
(20:10):
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
(20:33):
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
(20:54):
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.
Speaker 2 (21:08):
This is really 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, oh,
the FDA must be super slow and do things one
way we could expede 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
(21:31):
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 going, it takes time.
Speaker 5 (21:39):
Well, we don't need to do anything. We could have
no FDA 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 yeah, time and the
way we deal with it. Milton Friedman famously thought that
the FDA should only assess the safety of drugs, and
(22:00):
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
(22:22):
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
(22:45):
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.
Speaker 2 (22:59):
And I just want to up and 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 this sort of slot machine that makes
weird videos, et cetera. But really we're trying to find
these wonder drugs in long term. But for what it
(23:19):
sounds like you said, candidates are not where the shortages like.
The issue is not that we lack sufficiently a number
of sufficiently promising molecule combinations. The scarcity is not on
that at that point.
Speaker 5 (23:33):
That's my view. I mean, I'll steal me in the
other argument. The other argument would be, well, look, Dea,
you said ten minutes ago that these drugs have a
five percent 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,
(23:56):
but how would we know that we've done that? Meaning
if the three of us tomorrow invented a black box
that produced drug candidate concepts, and we were certain that
our model doubled the prior probability from five percent to
ten percent, that would be a truly revolutionary innovation on
our part. But how many candidates from that model would
(24:20):
we need to take all the way to an approval
before we had statistically demonstrated that we in fact increased
the rate of success. So people may have already cracked
that code. You know, Google may have already cracked that code.
Sam Waltman may have cracked that code. But someone's going
to need to spend thirty billion dollars developing the drug
(24:43):
ideas he has before we know whether he's done that,
And until that money is spent, it's pure conjecture and salesmanship.
Speaker 1 (25:06):
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.
Speaker 5 (25:23):
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
their advantages are multiple. I mean, their advantages are regulatory,
they relate to the personnel. We have lost an amazing
(25:47):
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.
(26:08):
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 US 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,
(26:32):
the clinical trials to China. That's going to make a
huge impact on the AUA.
Speaker 1 (26:35):
Yeah, this was actually my next question. I guess how
translatable is a successful clinical trial in China to a
market like the US.
Speaker 5 (26:44):
Three or four 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
(27:05):
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
(27:26):
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 and their data.
If they can do that. I think it's a global industry.
(27:48):
A lot of the companies are multinationals. They don't care
if the drug comes out of the US or comes
out of China.
Speaker 2 (27:54):
This is a really good question about private or VC
stage investing per se, but about biotech more broadly. 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 doc is, are you insane
to try to invest in biotech if you don't have PhD?
Level understanding of biology, Like, can anyone have alpha in
(28:17):
this industry if they don't actually know science.
Speaker 5 (28:21):
I think it's tough.
Speaker 2 (28:23):
Yeah, it seems very tough to you me.
Speaker 5 (28:25):
Look, 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 in the rest
of the public equity landscape. And so whereas there is
(28:46):
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 it.
Speaker 2 (29:01):
Is and they all have real science expertise on Stowe
they do.
Speaker 5 (29:04):
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
(29:25):
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
(29:47):
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.
Speaker 1 (29:59):
Back into wait, the biotech investing downturn, was that just
a function of higher interest rates or was something else
going on?
Speaker 5 (30:06):
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. Add to that this dynamic
where the generalists had gotten out of the sector, that
(30:30):
ultimately is fatal. And then consider the fact that we
had such a come down 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.
(30:51):
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,
your dad gets cancer, your kid gets some rare disease,
and you go, holy cow. I wish I had thought
about this before. Maybe all these people who are doing
(31:11):
this with their lives are not evil bloodsuckers who Bernie
Sanders needs to take down. And 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.
Speaker 1 (31:30):
Talk a little bit more about, I guess, the financial
incentives about actually developing new drugs. So 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 five
hundred dollars or perhaps even more in the US. And
(31:51):
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, the risk that they actually
take on and for some reason, the US seems to
be the designated place to do that.
Speaker 3 (32:07):
But like, why why? Is my question? Why US drugs?
Speaker 5 (32:12):
Well, 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,
(32:34):
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
(32:56):
or Astro Zeneca, look, if you want your drugs 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
(33:16):
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.
(33:38):
And so I don't know that there is 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
(34:01):
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
(34:21):
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.
Speaker 2 (34:32):
You mentioned the Bernie Sanders of the world, who they
look at the profits of drug companies, or they look
at the prices of drugs, and you know if perhaps
if they got their way, there would be less investment
in drug discovery, etc. At all, maybe less profits. Going
back to COVID. However, there was also the backlash on
the other side, essentially just this deep skepticism towards the
(34:54):
premise of pharma and that what are these scientists doing
and why don't they tell you about this root the
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 this sort of political environment investing in biotech
in a political environment, or a growing number of people
(35:15):
frankly seem to distrust the premise of scientific expertise.
Speaker 5 (35:22):
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. Some of the presentation of
data regarding the efficacy of the vaccines was not transparent,
(35:47):
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
(36:13):
science as total witchcraft and sorcery. So if you go
back to antiquity, the first people calling themselves doctors objectively
understood nothing. So this was pure sophistry from the beginning.
And we are on this long journey through which medicine
is going from total bs and witchcraft to slowly turning
(36:38):
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
(37:01):
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, Joe,
and the trust is critical because it is what gives
permission to this industry's existence.
Speaker 1 (37:17):
Wait, 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
(37:38):
is always death or so your brain damage. You're something 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
(37:59):
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?
Speaker 5 (38:21):
Actually?
Speaker 1 (38:22):
It sounds weird but you know, given the lack of experience,
and given the way other systems work around the world,
how much, say, should people have in their own medical treatment.
Speaker 5 (38:33):
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
(38:56):
in many other countries they completely socialize medical costs 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.
Speaker 1 (39:10):
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 the governments to make those decisions. Are insurers
the sort of another limiting factor here?
Speaker 5 (39:30):
I believe they are. I believe the private insurance industry
adds zero value to the United States healthcare system almost that.
I mean that 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.
Speaker 2 (39:48):
I notice they're in the video. You have a really
nice looking microphone? Is that a musical? Is that a
microphone for recording music?
Speaker 5 (39:55):
Yeah? This is the one I uh, this is the
one I sing on.
Speaker 2 (39:58):
It's it's first of all, you sound good, but it
also looks a lot cooler than the typical microphone that
are that our guests to is do you do you?
Are you still? Are you still playing much music?
Speaker 5 (40:09):
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.
Speaker 2 (40:16):
Are you do you think it all about AI generated music?
And uh, the effect that that's going to have on musicians.
I feel like a lot of musicians, like the ones
that I follow on Instagram, is there have a lot
of anxiety about this.
Speaker 5 (40:32):
There is anxiety, And look, I mean it's really hard
to make a living as a musician now It's always
been really hard, and you know, I can't imagine what
the lifestyle was of a loot player in George the
Second Royal Court or something but you know, it's a
tough business and it is scary when new technology comes
(40:53):
on the scene that might change the way you make
money as an artist. I live through that with Spotify,
people were terrified of it, and you know, fortunately what
it did.
Speaker 2 (41:02):
Over done what you did at long Spotify and then
hedge their own risk to it. But keep going.
Speaker 5 (41:08):
No, but looks spot Spotify by multiples increased the total
revenue of the recorded music business, which was the goal.
So mission accomplished. Now, look, AI is going to make music,
and I think like all creative people, like journalists, like investors,
everyone's going to think about how they can use it
(41:30):
to be more effective, have more leverage, have a cooler output.
I mean, I have very little doubt that artists are
going to do unbelievably 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 and.
Speaker 2 (41:55):
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 Suno
and some of these other AI music companies have talked
about this is like, well, music, learning to play instruments
is really hard, and therefore, can we separate in some
(42:18):
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 both 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
(42:40):
whether one can create great art if they never had
to learn the craft.
Speaker 5 (42:48):
I think the nuance with which one can communicate through
music is a function of how many options you perceive.
In other words, if you know the piano inside out,
you're aware of so many creative choices that are at
(43:11):
your disposal at any given moment. And if your ability
to express yourself is squeezed down to what you can
put into a natural language prompt, now those musical ideas
are having to pass through the medium of language to
be realized, and that inherently erodes the resolution and the
(43:35):
expansiveness with which you can express yourself.
Speaker 1 (43:38):
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.
Speaker 2 (43:46):
No, but I do think this that answered very deciightful, 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. But I thought
that answer made last time.
Speaker 3 (44:02):
DA.
Speaker 1 (44:02):
We're gonna have to wrap it up soon. I have
one last question, and I'm gonna kind of I'm gonna
put you on the spot. Can you can you sing
a little odd lot song for us? Like three bars
of an odd lot song? I don't care if you
generate it with you know, I guess Gemini now, but.
Speaker 5 (44:18):
Do you think you could Let's see? I mean, oh wow,
I'm gonna turn this. Let's see here.
Speaker 2 (44:27):
This is really cool. Yeah, if you came, you are
watching the video. So he's moving his microphone, he's moving
his microphone to his keyboard.
Speaker 5 (44:35):
Okay, can you see great?
Speaker 2 (44:37):
Yeah? Go for it?
Speaker 5 (44:39):
Okay, We're gonna try.
Speaker 6 (44:44):
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.
Speaker 5 (44:58):
How's that pretty good?
Speaker 2 (45:00):
You have a great voice.
Speaker 3 (45:01):
Yeah it is.
Speaker 2 (45:02):
Do you ever want to compose an outro song for uh? Yeah,
something like that?
Speaker 5 (45:06):
Oh, I would love to. I'm I'm. I am the
composer of two or three podcast theme songs. And I
have to say, I love your guys theme music. It
gets me excited. And 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 and my.
Speaker 1 (45:25):
Hobby, we heard that you actually wrote like some a
paper that won like a prize from the FED or
something like that.
Speaker 5 (45:32):
So the Federal Reserve had this nerd competition they sponsored
called FED Challenge. And I was the captain of my
high school team one year and we got to DC
and we we saw Green Span walk out with his
wizened 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 touch on
(45:53):
so much interesting stuff, and this just has to be
the most exciting thing for young people to experience in
order to get turned onto business and economics and finance
and recognize these aren't just boring, you know, staid topics.
They're fascinating.
Speaker 1 (46:09):
Thank you for saying that. I really appreciate it, and
also thank you for singing for us. I think that
was an all thoughts first. Yeah, yeah, well on the spot.
I know we've had merl Hazard the country Singing Economist
on before, but that was fantastic day.
Speaker 3 (46:24):
Wallack, thank you so much for coming on the show.
Really appreciate it. Thanks you, guys, than for that was great.
That was really interesting.
Speaker 2 (46:41):
Joe, that was super fun. He was great.
Speaker 1 (46:43):
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.
Speaker 2 (46:52):
I think it makes a lot of sense. And the
especially the fact that you know these are extreme. These
are all startup investing. We know, you know, there's this
power law phenomenon where one of your twenty portfolio company
is going to make all the money.
Speaker 3 (47:06):
Yeah, the lottery ticket, but you.
Speaker 2 (47:08):
Know, like biotech is like lottery tickets upon lottery tickets
there's so much success uncertainty.
Speaker 1 (47:14):
There's so much with lower payouts as.
Speaker 2 (47:16):
Lower payouts, there's so much success uncertainty. There's so much
time that elapses between the initial work and where you
see if there's any signals of traction. It does feel
a lot like the uncertainty that exists in the music
industry and selecting which of these hundred 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.
Speaker 1 (47:39):
Yeah, I thought that 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
(48:01):
get old and.
Speaker 2 (48:02):
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 happens. And to your point or to your observation
about the dinosaurs, like I do think that lots of
(48:24):
people have this fantasy that anytime there is a legacy
industry of any sort, that if you just got twenty
one year olds from Stanford in the same room.
Speaker 3 (48:32):
They gave them a garage to work out.
Speaker 2 (48:34):
Garage, that they would do it a lot better than
the veterans. That was the Doge premise, and Doge doesn't
exist anymore.
Speaker 3 (48:41):
So yeah, shall we leave it there.
Speaker 2 (48:44):
Let's leave it there.
Speaker 1 (48:45):
This has been another episode of the All Thoughts podcast.
I'm Tracy Alloway. You can follow me at Tracy Alloway.
Speaker 2 (48:50):
And I'm Joe wasn't Thal. You can follow me at
the Stalwart, follow our guesst d A Wallack He's at
d A Wallack. Follow our producers Carmen Rodriguez at Carmen
armand Dashel Bennett a Dashboy, and kill Brooks at Kilbrooks.
From our Oddlots content, go to Bloomberg dot com slash
odd Lots were the daily newsletter and all of our episodes,
and you can chat about all of these topics. Twenty
four seven in our discord Discord dot gg slash online.
Speaker 1 (49:13):
And if you enjoy Odd Lots, if you want us
to do more healthcare episodes, then please leave us a
positive review on your favorite podcast platform. And remember, if
you are a Bloomberg subscriber, you can listen to all
of our episodes absolutely ad free. All you need to
do is find the Bloomberg channel on Apple Podcasts and
follow the instructions there.
Speaker 3 (49:32):
Thanks for listening, oh
Hey, they're aud Loots listeners. It is that time of
the year again. We are going to be doing a
call in show on the podcast. You can ask us
any of your burning questions.
Speaker 2 (00:12):
That's right. You want to ask us about finance, markets
and economics, go for it. You want to ask us
about the year in podcasting, go for it. You want
to ask about where Tracy is with growing chicken or
raising chicken, growing chickens, raising chickens on her versioning firm
in Connecticut, go for it. This is your chance to
(00:33):
ask us anything.
Speaker 3 (00:34):
Joe's favorite cut of steak.
Speaker 2 (00:36):
Right, my favorite cut of steak, my favorite Chinese restaurant
in the East Village. It's all fair game, all right.
Speaker 1 (00:41):
All you have to do is send a voice memo
with your question, your name, your age, and your location
to od Loots at Bloomberg dot net.
Speaker 2 (00:51):
Deadline to submit is December seventeenth, So get the men,
assume as you can.
Speaker 1 (00:55):
We're looking forward to hearing what you have to ask
and yeah, that's coming up.
Speaker 4 (01:02):
Bloomberg Audio Studios, Podcasts, Radio News.
Speaker 1 (01:18):
Hello and welcome to another episode of the Odd Lots podcast.
Speaker 3 (01:21):
I'm Tracy Alloway.
Speaker 2 (01:22):
And I'm Joe Why isn't they Joe.
Speaker 3 (01:23):
We were doing a Q and A this morning.
Speaker 2 (01:25):
That's right.
Speaker 3 (01:26):
It's a lot of fun go on a live Q
and A.
Speaker 1 (01:29):
And someone asked a question about whether or not we're
going to do more healthcare episodes, and no, we don't,
and there's a reason for that. I personally am incredibly
intimidated by the US healthcare 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
(01:51):
that question that this same day, that's right, we're actually
recording a healthcare episode with someone that we've wanted to
speak to for a long time.
Speaker 2 (02:01):
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 healthcare system works.
I don't even know where to begin asking the right questions.
There is athing 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
they're so it seems so big and sprawling, etc. That
(02:21):
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 healthcare episodes, which we should have done
a long time.
Speaker 1 (02:32):
Again, that's exactly right. There's also a lot of new
stuff happening in healthcare at the moment, and we 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 US side of biotech and nesting,
and we do have another episode plan that's sort of
tangentially related to that. But clearly there's a lot to
(02:53):
talk about. The other very odd lotsy thing with this
guest is we like people who have interest in career histories, right.
Speaker 2 (03:01):
That's right. How 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 they got their NBA.
Speaker 3 (03:14):
And okay, you forgive them, I forgive them.
Speaker 2 (03:16):
That's totally fine. But it's also interesting to hear about
the people who maybe walked in through the side door,
so to speak.
Speaker 1 (03:22):
Absolutely so, we do, in fact have the perfect guest.
We have someone who has a lot of thoughts on
US healthcare and who is also a biotech investor and
also formerly the lead singer of Chester French. So Da Wallack,
Welcome to the show. Thanks so much for coming on.
Speaker 5 (03:39):
Thanks for having me, guys. I'm I'm a odd lots junkie.
So this is like going to the Grammys.
Speaker 2 (03:45):
Amazing, Thank you ever Grammy. No, don't sorry, sorry, sorry,
I shouldn't have I shouldn't have it.
Speaker 5 (03:52):
Not yet is the right answer.
Speaker 3 (03:53):
Not yet, not yet, not yet.
Speaker 1 (03:55):
I guess my first question should be, can you talk
to us about the through line between being musician and
healthcare and how and biotech and how you got into
the space, because I think you know, it's not a
natural transition, to say the least.
Speaker 5 (04:10):
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 about
(04:32):
thirteen 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 SpaceX and Ripple and a bunch of interesting
other startups, and then ultimately a guy I knew started
(04:56):
an early stage a healthcare 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,
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 healthcare system and was just
blown away by how screwed up and stupid it was.
(05:18):
And then that eventually evolved into learning more about biotechnology
and the other sub sectors of healthcare 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
(05:40):
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, And in healthcare there's
a similar parallel challenge, which is how do you combine
medicine and capitalism, which don't naturally go together very well?
Speaker 2 (06:00):
Producer, analogy makes a ton of sense. And you know,
there are probably a lot of musicians who are really brilliant,
they're 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, et cetera,
but the path from brilliant science to commercial blockbuster can often,
I assume, be tricky or dispiriting in many ways, et cetera.
(06:23):
Biotech specifically, of all the things in investing, biotech strikes
me is 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, et cetera. 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
(06:46):
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.
Speaker 5 (07:02):
Oh, that's absolutely true. 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
(07:23):
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 five percent probability of success from the
(07:44):
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
(08:04):
probabilities of success, and the entire challenge as a biotech
investor is 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
(08:26):
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 wins
(08:48):
are not as big.
Speaker 1 (08:50):
So one thing I'm really curious about is how you
source potential investments and how you find you use the
analogy of the record, 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 software
or tech space that we usually talk about when it
(09:12):
comes to venture capital.
Speaker 5 (09:14):
You know, when I started doing venture investing, it was,
like I said, twelve thirteen 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 decades.
(09:37):
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. 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 to the caliber
(09:57):
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 a 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,
(10:20):
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. There are just
an immense number of cool ideas. If you go into
(10:41):
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. So that is really what the large pharmaceutical
(11:03):
companies have a specialized expertise and they train people in
this translational work. How do you go from early science
to real products?
Speaker 2 (11:29):
When I go to a typical venture capitalist website or
I see their Twitter bio or something like that, it'll
say like, we bet great founders, and I'm like, thanks,
that's very helpful because that distinguishes you from the venture
capitalists who back crappy founders. So I'm glad I'm gonna
invest with you. And said, what's the biotech equivalent? What's
the cliche in your industry that every VC says that
(11:51):
ostensibly distinguishes them from all the others.
Speaker 5 (11:55):
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 thirty 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
(12:16):
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 to have had a lot of failures.
(12:36):
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, it 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
(12:57):
in for thirty or forty million bucks, an easy door
to walk back out of. 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
(13:20):
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 twenty one year olds coming out
of Stanford and that hypothesis people have been testing now
(13:42):
for a few years. I'd say it's a little too
early to issue a verdict, but that's never really been
our theory.
Speaker 1 (13:50):
Is that hypothesis just predicated on AI coming in and
making you know, drug development easier.
Speaker 3 (13:56):
Is that all it is.
Speaker 5 (13:58):
There's a lot of that. I'd say there are two
parts of it. One of it is maybe more substantive
than that, and this is a little nuanced, but I
know odd lots of people like Nuance 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,
(14:21):
many of them are public. What really gave rise to
that industry was the big pharmas 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
(14:43):
was just let all these crazy guys like da finance
startups and once they work, just buy them. 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 a very specialized technical experts
from the pharma companies, and it created the so called
(15:04):
cro or contract research organization ecosystem. So you now, as
a consequence of that, for the past twenty 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
(15:25):
the best analogy to 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
(15:48):
kind of infrastructure through which they can build companies in
a really agile way. The other argument, you know exactly
your question, is around AI, and that is basically, look
these old people don't understand AI. Let's get some young
Silicon Valley computer science he types to do this, and
they're gonna show them how it's done.
Speaker 2 (16:10):
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 you're twenty twenty five,
(16:32):
it must be out of date by now and they
haven't figured this out.
Speaker 3 (16:35):
And if we could just cough cough, journalism.
Speaker 2 (16:38):
Yeah right, if we could just hire wiz kids, then
we could reinvent the industry from first principles and just
do a much better job than the legacy of things.
And I think, whether it's healthcare 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 brain power,
(17:01):
we could figure out what that thing is.
Speaker 5 (17:04):
I think that is a reasonable characterization or what people
say today 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.
(17:25):
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 Demisisabus at deep Mind the Nobel
Prize last year with alpha fold, which was this amazing
discovery they made that using machine learning models you could
(17:47):
solve a problem that had gone unsolved for decades, which
was can you predict from the sequence of a protein's
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
(18:08):
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
(18:28):
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.
Speaker 2 (18:44):
Just real quickly, if we had been having this conversation
in a month ago, would you have said Gemini or
would you have said CHADJPT Because I switched from chad
JPT to Gemini in the last month, and I'm just
curious whether you're what you would have said a month ago.
Speaker 5 (18:57):
A month ago, I was using all of them. Now
I'm only using Gemen.
Speaker 2 (19:01):
It's interesting, all right, good data plant.
Speaker 1 (19:03):
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 are the major I guess, like
(19:24):
stumbling blocks to getting something to the market.
Speaker 5 (19:29):
Your question held the answer. 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
(19:49):
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 actually
modifies the disease that you're trying to treat. And the
tragedy of our moment is that the only way to
(20:10):
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
(20:33):
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
(20:54):
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.
Speaker 2 (21:08):
This is really 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, oh,
the FDA must be super slow and do things one
way we could expede 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
(21:31):
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 going, it takes time.
Speaker 5 (21:39):
Well, we don't need to do anything. We could have
no FDA 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 yeah, time and the
way we deal with it. Milton Friedman famously thought that
the FDA should only assess the safety of drugs, and
(22:00):
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
(22:22):
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
(22:45):
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.
Speaker 2 (22:59):
And I just want to up and 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 this sort of slot machine that makes
weird videos, et cetera. But really we're trying to find
these wonder drugs in long term. But for what it
(23:19):
sounds like you said, candidates are not where the shortages like.
The issue is not that we lack sufficiently a number
of sufficiently promising molecule combinations. The scarcity is not on
that at that point.
Speaker 5 (23:33):
That's my view. I mean, I'll steal me in the
other argument. The other argument would be, well, look, Dea,
you said ten minutes ago that these drugs have a
five percent 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,
(23:56):
but how would we know that we've done that? Meaning
if the three of us tomorrow invented a black box
that produced drug candidate concepts, and we were certain that
our model doubled the prior probability from five percent to
ten percent, that would be a truly revolutionary innovation on
our part. But how many candidates from that model would
(24:20):
we need to take all the way to an approval
before we had statistically demonstrated that we in fact increased
the rate of success. So people may have already cracked
that code. You know, Google may have already cracked that code.
Sam Waltman may have cracked that code. But someone's going
to need to spend thirty billion dollars developing the drug
(24:43):
ideas he has before we know whether he's done that,
And until that money is spent, it's pure conjecture and salesmanship.
Speaker 1 (25:06):
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.
Speaker 5 (25:23):
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
their advantages are multiple. I mean, their advantages are regulatory,
they relate to the personnel. We have lost an amazing
(25:47):
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.
(26:08):
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 US 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,
(26:32):
the clinical trials to China. That's going to make a
huge impact on the AUA.
Speaker 1 (26:35):
Yeah, this was actually my next question. I guess how
translatable is a successful clinical trial in China to a
market like the US.
Speaker 5 (26:44):
Three or four 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
(27:05):
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
(27:26):
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 and their data.
If they can do that. I think it's a global industry.
(27:48):
A lot of the companies are multinationals. They don't care
if the drug comes out of the US or comes
out of China.
Speaker 2 (27:54):
This is a really good question about private or VC
stage investing per se, but about biotech more broadly. 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 doc is, are you insane
to try to invest in biotech if you don't have PhD?
Level understanding of biology, Like, can anyone have alpha in
(28:17):
this industry if they don't actually know science.
Speaker 5 (28:21):
I think it's tough.
Speaker 2 (28:23):
Yeah, it seems very tough to you me.
Speaker 5 (28:25):
Look, 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 in the rest
of the public equity landscape. And so whereas there is
(28:46):
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 it.
Speaker 2 (29:01):
Is and they all have real science expertise on Stowe
they do.
Speaker 5 (29:04):
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
(29:25):
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
(29:47):
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.
Speaker 1 (29:59):
Back into wait, the biotech investing downturn, was that just
a function of higher interest rates or was something else
going on?
Speaker 5 (30:06):
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. Add to that this dynamic
where the generalists had gotten out of the sector, that
(30:30):
ultimately is fatal. And then consider the fact that we
had such a come down 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.
(30:51):
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,
your dad gets cancer, your kid gets some rare disease,
and you go, holy cow. I wish I had thought
about this before. Maybe all these people who are doing
(31:11):
this with their lives are not evil bloodsuckers who Bernie
Sanders needs to take down. And 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.
Speaker 1 (31:30):
Talk a little bit more about, I guess, the financial
incentives about actually developing new drugs. So 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 five
hundred dollars or perhaps even more in the US. And
(31:51):
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, the risk that they actually
take on and for some reason, the US seems to
be the designated place to do that.
Speaker 3 (32:07):
But like, why why? Is my question? Why US drugs?
Speaker 5 (32:12):
Well, 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,
(32:34):
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
(32:56):
or Astro Zeneca, look, if you want your drugs 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
(33:16):
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.
(33:38):
And so I don't know that there is 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
(34:01):
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
(34:21):
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.
Speaker 2 (34:32):
You mentioned the Bernie Sanders of the world, who they
look at the profits of drug companies, or they look
at the prices of drugs, and you know if perhaps
if they got their way, there would be less investment
in drug discovery, etc. At all, maybe less profits. Going
back to COVID. However, there was also the backlash on
the other side, essentially just this deep skepticism towards the
(34:54):
premise of pharma and that what are these scientists doing
and why don't they tell you about this root the
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 this sort of political environment investing in biotech
in a political environment, or a growing number of people
(35:15):
frankly seem to distrust the premise of scientific expertise.
Speaker 5 (35:22):
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. Some of the presentation of
data regarding the efficacy of the vaccines was not transparent,
(35:47):
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
(36:13):
science as total witchcraft and sorcery. So if you go
back to antiquity, the first people calling themselves doctors objectively
understood nothing. So this was pure sophistry from the beginning.
And we are on this long journey through which medicine
is going from total bs and witchcraft to slowly turning
(36:38):
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
(37:01):
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, Joe,
and the trust is critical because it is what gives
permission to this industry's existence.
Speaker 1 (37:17):
Wait, 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
(37:38):
is always death or so your brain damage. You're something 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
(37:59):
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?
Speaker 5 (38:21):
Actually?
Speaker 1 (38:22):
It sounds weird but you know, given the lack of experience,
and given the way other systems work around the world,
how much, say, should people have in their own medical treatment.
Speaker 5 (38:33):
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
(38:56):
in many other countries they completely socialize medical costs 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.
Speaker 1 (39:10):
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 the governments to make those decisions. Are insurers
the sort of another limiting factor here?
Speaker 5 (39:30):
I believe they are. I believe the private insurance industry
adds zero value to the United States healthcare system almost that.
I mean that 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.
Speaker 2 (39:48):
I notice they're in the video. You have a really
nice looking microphone? Is that a musical? Is that a
microphone for recording music?
Speaker 5 (39:55):
Yeah? This is the one I uh, this is the
one I sing on.
Speaker 2 (39:58):
It's it's first of all, you sound good, but it
also looks a lot cooler than the typical microphone that
are that our guests to is do you do you?
Are you still? Are you still playing much music?
Speaker 5 (40:09):
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.
Speaker 2 (40:16):
Are you do you think it all about AI generated music?
And uh, the effect that that's going to have on musicians.
I feel like a lot of musicians, like the ones
that I follow on Instagram, is there have a lot
of anxiety about this.
Speaker 5 (40:32):
There is anxiety, And look, I mean it's really hard
to make a living as a musician now It's always
been really hard, and you know, I can't imagine what
the lifestyle was of a loot player in George the
Second Royal Court or something but you know, it's a
tough business and it is scary when new technology comes
(40:53):
on the scene that might change the way you make
money as an artist. I live through that with Spotify,
people were terrified of it, and you know, fortunately what
it did.
Speaker 2 (41:02):
Over done what you did at long Spotify and then
hedge their own risk to it. But keep going.
Speaker 5 (41:08):
No, but looks spot Spotify by multiples increased the total
revenue of the recorded music business, which was the goal.
So mission accomplished. Now, look, AI is going to make music,
and I think like all creative people, like journalists, like investors,
everyone's going to think about how they can use it
(41:30):
to be more effective, have more leverage, have a cooler output.
I mean, I have very little doubt that artists are
going to do unbelievably 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 and.
Speaker 2 (41:55):
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 Suno
and some of these other AI music companies have talked
about this is like, well, music, learning to play instruments
is really hard, and therefore, can we separate in some
(42:18):
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 both 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
(42:40):
whether one can create great art if they never had
to learn the craft.
Speaker 5 (42:48):
I think the nuance with which one can communicate through
music is a function of how many options you perceive.
In other words, if you know the piano inside out,
you're aware of so many creative choices that are at
(43:11):
your disposal at any given moment. And if your ability
to express yourself is squeezed down to what you can
put into a natural language prompt, now those musical ideas
are having to pass through the medium of language to
be realized, and that inherently erodes the resolution and the
(43:35):
expansiveness with which you can express yourself.
Speaker 1 (43:38):
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.
Speaker 2 (43:46):
No, but I do think this that answered very deciightful, 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. But I thought
that answer made last time.
Speaker 3 (44:02):
DA.
Speaker 1 (44:02):
We're gonna have to wrap it up soon. I have
one last question, and I'm gonna kind of I'm gonna
put you on the spot. Can you can you sing
a little odd lot song for us? Like three bars
of an odd lot song? I don't care if you
generate it with you know, I guess Gemini now, but.
Speaker 5 (44:18):
Do you think you could Let's see? I mean, oh wow,
I'm gonna turn this. Let's see here.
Speaker 2 (44:27):
This is really cool. Yeah, if you came, you are
watching the video. So he's moving his microphone, he's moving
his microphone to his keyboard.
Speaker 5 (44:35):
Okay, can you see great?
Speaker 2 (44:37):
Yeah? Go for it?
Speaker 5 (44:39):
Okay, We're gonna try.
Speaker 6 (44:44):
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.
Speaker 5 (44:58):
How's that pretty good?
Speaker 2 (45:00):
You have a great voice.
Speaker 3 (45:01):
Yeah it is.
Speaker 2 (45:02):
Do you ever want to compose an outro song for uh? Yeah,
something like that?
Speaker 5 (45:06):
Oh, I would love to. I'm I'm. I am the
composer of two or three podcast theme songs. And I
have to say, I love your guys theme music. It
gets me excited. And 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 and my.
Speaker 1 (45:25):
Hobby, we heard that you actually wrote like some a
paper that won like a prize from the FED or
something like that.
Speaker 5 (45:32):
So the Federal Reserve had this nerd competition they sponsored
called FED Challenge. And I was the captain of my
high school team one year and we got to DC
and we we saw Green Span walk out with his
wizened 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 touch on
(45:53):
so much interesting stuff, and this just has to be
the most exciting thing for young people to experience in
order to get turned onto business and economics and finance
and recognize these aren't just boring, you know, staid topics.
They're fascinating.
Speaker 1 (46:09):
Thank you for saying that. I really appreciate it, and
also thank you for singing for us. I think that
was an all thoughts first. Yeah, yeah, well on the spot.
I know we've had merl Hazard the country Singing Economist
on before, but that was fantastic day.
Speaker 3 (46:24):
Wallack, thank you so much for coming on the show.
Really appreciate it. Thanks you, guys, than for that was great.
That was really interesting.
Speaker 2 (46:41):
Joe, that was super fun. He was great.
Speaker 1 (46:43):
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.
Speaker 2 (46:52):
I think it makes a lot of sense. And the
especially the fact that you know these are extreme. These
are all startup investing. We know, you know, there's this
power law phenomenon where one of your twenty portfolio company
is going to make all the money.
Speaker 3 (47:06):
Yeah, the lottery ticket, but you.
Speaker 2 (47:08):
Know, like biotech is like lottery tickets upon lottery tickets
there's so much success uncertainty.
Speaker 1 (47:14):
There's so much with lower payouts as.
Speaker 2 (47:16):
Lower payouts, there's so much success uncertainty. There's so much
time that elapses between the initial work and where you
see if there's any signals of traction. It does feel
a lot like the uncertainty that exists in the music
industry and selecting which of these hundred 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.
Speaker 1 (47:39):
Yeah, I thought that 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
(48:01):
get old and.
Speaker 2 (48:02):
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 happens. And to your point or to your observation
about the dinosaurs, like I do think that lots of
(48:24):
people have this fantasy that anytime there is a legacy
industry of any sort, that if you just got twenty
one year olds from Stanford in the same room.
Speaker 3 (48:32):
They gave them a garage to work out.
Speaker 2 (48:34):
Garage, that they would do it a lot better than
the veterans. That was the Doge premise, and Doge doesn't
exist anymore.
Speaker 3 (48:41):
So yeah, shall we leave it there.
Speaker 2 (48:44):
Let's leave it there.
Speaker 1 (48:45):
This has been another episode of the All Thoughts podcast.
I'm Tracy Alloway. You can follow me at Tracy Alloway.
Speaker 2 (48:50):
And I'm Joe wasn't Thal. You can follow me at
the Stalwart, follow our guesst d A Wallack He's at
d A Wallack. Follow our producers Carmen Rodriguez at Carmen
armand Dashel Bennett a Dashboy, and kill Brooks at Kilbrooks.
From our Oddlots content, go to Bloomberg dot com slash
odd Lots were the daily newsletter and all of our episodes,
and you can chat about all of these topics. Twenty
four seven in our discord Discord dot gg slash online.
Speaker 1 (49:13):
And if you enjoy Odd Lots, if you want us
to do more healthcare episodes, then please leave us a
positive review on your favorite podcast platform. And remember, if
you are a Bloomberg subscriber, you can listen to all
of our episodes absolutely ad free. All you need to
do is find the Bloomberg channel on Apple Podcasts and
follow the instructions there.
Speaker 3 (49:32):
Thanks for listening, oh
Hosts And Creators
Joe Weisenthal
Tracy Alloway
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