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RTW’s Rod Wong on Biotech’s Revival and the Global Shift · Vanguards of Healthcare by Bloomberg Intelligence

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Speaker 1: Welcome to another episode of Vanguards of Healthcare, the podcast
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Speaker 1: from Bloomberg Intelligence where we speak to leaders in the
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Speaker 1: healthcare industry and of course drug development sector. And today
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Speaker 1: I have the pleasure of having Rod Wong, who is
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Speaker 1: the founder of RTW, one of the key healthcare investors
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Speaker 1: in the space, based out.
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Speaker 2: Of New York.
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Speaker 1: All of our research is available to clients on the
0:55
Speaker 1: Bloomberg terminal under the bi Pharma bi Bioti Diseases dashboards.
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Speaker 1: So without further Ado, I'm going to start the conversation
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Speaker 1: with Rod. Thank you very much, Rod for joining us today.
1:08
Speaker 1: I'm based in Boston today for random reasons, and of
1:11
Speaker 1: course Rod is based out of New York, so as
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Speaker 1: is typical, I'd love to start this conversation by asking
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Speaker 1: Rod to give us a little bit of a background
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Speaker 1: on himself and how he got to.
1:24
Speaker 2: Where he is in terms of his career today.
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Speaker 3: Hey, Sam, thanks for having me. Happy to be here
1:29
Speaker 3: with you, sure so super quickly. I grew up in
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Speaker 3: the Midwest. I basically lived kind of the American dream.
1:35
Speaker 3: My parents grew up in Hong Kong. They came over
1:38
Speaker 3: for college. They ended up in Lawrence, Kansas, which is
1:41
Speaker 3: a college town where the University of Kansas is o KU.
1:44
Speaker 3: So that's where I grew up as a wonderful place
1:47
Speaker 3: to grow up. You know. I ended up doing a
1:50
Speaker 3: standard pre med med kind of track, and I ended
1:53
Speaker 3: up in medical school at UPenn. Tried to figure out
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Speaker 3: I love science, but I tried to figure out the
1:58
Speaker 3: best way for me to express that interest. And I
2:01
Speaker 3: ended up doing a business degree in MBA at Harvard
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Speaker 3: and found that path. As I was interviewing for jobs,
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Speaker 3: ended up being seal side research. And then from there
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Speaker 3: my career was relatively linear.
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Speaker 1: You know.
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Speaker 3: I worked at a couple investment firms before starting RTW
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Speaker 3: and that was about seventeen years ago. And then obviously
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Speaker 3: we've gone through a lot of evolutions in the last
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Speaker 3: seventeen years as well, which happy to talk about.
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Speaker 2: Brilliant. That's that's a pretty good trajectory. I've got a
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Speaker 2: similar one to you. I'm a PhD, not medic.
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Speaker 1: Got into the finance, but kind of got stuck at
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Speaker 1: the cell side five side of things until I moved
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Speaker 1: to Bloomberg, where I've been for almost fifteen years. So
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Speaker 1: very a wonderful experience at Bloomberg Intelligence. So let's talk
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Speaker 1: about our tw as you said, seventeen years, so the history, philosophy,
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Speaker 1: current investment approach. I'm going to pile a whole lot
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Speaker 1: into this question, so take as much as you like
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Speaker 1: future direction.
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Speaker 2: So I'll remind you one of these tups we haven't
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Speaker 2: touched on.
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Speaker 3: Great, Yeah, sure, I'll take a crack at some of that.
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Speaker 3: So you know, when we started out, we started out
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Speaker 3: like any single strategy, single manager investment firm or hedge fund.
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Speaker 3: We had a small team. I think back then, even
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Speaker 3: at the beginning, we took pride in a couple things.
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Speaker 3: It's mainly a couple areas of deep research capability. You know,
3:20
Speaker 3: we were good at figuring out whether science would work
3:24
Speaker 3: or not. And then we also took a lot of
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Speaker 3: pride in doing good commercial forecasting work, and those two
3:30
Speaker 3: skills I think you know, served us well early on.
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Speaker 3: That was in a backdrop of a time where there's
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Speaker 3: very little specialist talent at all investing in biotech, and
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Speaker 3: so it was enough to give us an edge and
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Speaker 3: to do well. And then I would say over the
3:45
Speaker 3: last seventeen years, we kind of went through two other
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Speaker 3: stages of major evolutions of the firm. The middle stage
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Speaker 3: was kind of the convergence of private and public investing.
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Speaker 3: Everyone in biotech now knows that as the crossover ecosystem.
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Speaker 3: We were one of the early hand full of firms
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Speaker 3: that were kind of pushing that convergence.
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Speaker 2: You know.
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Speaker 3: It turns out that investing in private companies has a
4:07
Speaker 3: lot of benefits to making good investment decision decisions when
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Speaker 3: those companies are public. I think a big reason is
4:13
Speaker 3: because fire to companies go public so young in their
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Speaker 3: life cycle. So by being a private investor, you have
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Speaker 3: this opportunity to get to no management teams more deeply
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Speaker 3: than you otherwise would, get to know data better than
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Speaker 3: you otherwise would, and that's helpful throughout the life cycle
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Speaker 3: of investment many years, you know, after a private company
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Speaker 3: goes public. So that was the middle stage, and then,
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Speaker 3: of course the most recent stage of the firm was
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Speaker 3: really its institutionalization. We made this decision a little bit
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Speaker 3: north of half a dozen years ago, and the driving
4:45
Speaker 3: reason was we just saw this acceleration in science, right
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Speaker 3: and the pace of innovation, and we said, if we
4:51
Speaker 3: want to stay true and continue to aspire to be
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Speaker 3: among the smartest in the room, right, take pride in
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Speaker 3: that deep research edge. Then we're going to have to
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Speaker 3: change how we do business. We're going to need a
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Speaker 3: much bigger team than we had historically. That team should
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Speaker 3: be sub specialized in obvious things like disease areas and technologies.
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Speaker 3: And you know that scale is going to be critical
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Speaker 3: to keep pace with how our industry is growing. So
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Speaker 3: that's the journey we've been on the last half dozen
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Speaker 3: years or so. And you know, and now we're kind
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Speaker 3: of shifting our focus as well towards the future. We think,
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Speaker 3: of course, technology is going to dramatically change how our
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Speaker 3: jobs are done. You know, healthcare is no different from
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Speaker 3: any other industry. AI is going to dramatically change things.
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Speaker 3: So we're focused on that. And the other thing that
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Speaker 3: we're really focused on is the globalization of innovation and
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Speaker 3: specifically the emergence of China as a major player and innovation.
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Speaker 3: So both of those things are difficult things to go
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Speaker 3: after if you don't have the resources and the scale
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Speaker 3: of team. And so we're glad we made that institutionalization decision.
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Speaker 3: I think it positions us well for the future. So anyway,
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Speaker 3: I'll pause there, happy to chat about any of that more.
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Speaker 1: So, you touched on quite a lot of the topics
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Speaker 1: that we're going to unpack hopefully as we discuss here.
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Speaker 1: But so give us a quantum there. When you said
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Speaker 1: about six years ago you expanded the team, what's that size?
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Speaker 4: Now?
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Speaker 2: How many are you?
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Speaker 3: Yeah, so we went from around a couple dozen employees
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Speaker 3: a little bit more than that, so now more than
6:20
Speaker 3: tripling our head counts. So now we're pushing about one
6:23
Speaker 3: hundred people. Most of those folks are in New York City,
6:26
Speaker 3: where we're headquartered, but we have people now all around
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Speaker 3: the world, of course in Asia, but also London and
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Speaker 3: soon in the Middle East also.
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Speaker 1: Oh interesting, that's interesting timing for that. I know one
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Speaker 1: of your team in Hong Kong because she used to
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Speaker 1: work with me, So you've got a very good analyst
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Speaker 1: from our team.
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Speaker 3: Thank you for that. She's so far.
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Speaker 1: Let's let's talk about the states of the biotic market
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Speaker 1: right now. The XBI, which is the one that a
6:51
Speaker 1: lot of people refer to, although they rather not, but
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Speaker 1: that's the one that they look at, is doing reasonably
6:57
Speaker 1: well despite the risk that the world is undergoing. We
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Speaker 1: have this discussion sometimes amongst my friends on the sell side,
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Speaker 1: on byside about whether we have a disconnect between where
7:09
Speaker 1: the risk profile of the globe is at the potential
7:13
Speaker 1: for interest rates going up because of inflation.
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Speaker 2: And I think.
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Speaker 1: A lot of us blamed partly the high level of
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Speaker 1: return that people could get with little risk in the
7:26
Speaker 1: days in the say up to about August time last year,
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Speaker 1: where interest rates or the direction of interest rates started
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Speaker 1: looking downwards. And therefore that was one of the reasons
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Speaker 1: I was given for the sudden real interest in biotech.
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Speaker 2: But so, how do you see this date of the
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Speaker 2: market right now?
7:45
Speaker 1: We've seen fundraisings that especially followers that are great IPOs.
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Speaker 1: I think people hoped for a bit more maybe by now,
7:52
Speaker 1: and things have.
7:53
Speaker 2: Been a bit colder or slower. So just give me
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Speaker 2: your give us your general feel about how we are.
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Speaker 3: Yeah, I kind of frame it this way. You know,
8:03
Speaker 3: for the last few years, as you know, well, you know,
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Speaker 3: we were in this prolonged bear market, and during that period,
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Speaker 3: I think we kind of had three things going against us.
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Speaker 3: Right One, fundamentals, because the last bull market you had
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Speaker 3: too much early stage science that ended up being a
8:18
Speaker 3: lot of public companies, some of them shouldn't have been public.
8:21
Speaker 3: The ones that were, there's a lot of setbacks, right,
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Speaker 3: So there's the fundamental bucket. Then the one you mentioned.
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Speaker 3: We're in a rising rate cycle, and the last one
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Speaker 3: was especially the last couple of years. We're in a
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Speaker 3: period of high policy uncertainty. So we had kind of
8:34
Speaker 3: triple headwinds and then and I think that explained why
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Speaker 3: we had this four year record setting kind of bear market.
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Speaker 2: Now now I.
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Speaker 3: Think, you know, things the balance has shifted materially, right,
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Speaker 3: Two out of the three of those things have changed
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Speaker 3: a lot, and the third one is at least not
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Speaker 3: as bad as it was.
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Speaker 2: Right.
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Speaker 3: So, starting with interest rates, I think things have plateaued.
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Speaker 3: And now there's this bulbear debate on you know, could
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Speaker 3: we go into an easing cycle or is it going
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Speaker 3: to be stick here hopefully not continue to rise. But
9:02
Speaker 3: let's just say that there are plateaued and the risk
9:05
Speaker 3: award is more even on both sides policy uncertainty. That
9:09
Speaker 3: really has come a long way. Right last year, in
9:11
Speaker 3: the first year of Trump's second administration, he did a
9:14
Speaker 3: fair amount of deal making to address a couple of
9:16
Speaker 3: his major policy concerns, you know, the reshoring of drug
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Speaker 3: manufacturing to the States. He struck a lot of deals
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Speaker 3: with the majority of the large pharmacy, and then of
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Speaker 3: course on drug pricing, he did some deals to try
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Speaker 3: to make a dent in this large price difference between
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Speaker 3: the US and Europe, right, And I think from what
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Speaker 3: we hear, the view is now that he wants to
9:36
Speaker 3: move on or focus increasingly on other issues.
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Speaker 1: Now.
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Speaker 3: To me, the most important one though, is actually the fundamentals.
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Speaker 3: Right now that boom in innovation that was too young
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Speaker 3: at the time, I think the story has changed a lot, right,
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Speaker 3: So now it's maturing. You're seeing the successes of that.
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Speaker 3: You're seeing increased numbers of new drugs getting approved, and
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Speaker 3: not only that, you're seeing really successful, commercially successful businesses
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Speaker 3: emerge and very significant ones.
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Speaker 1: Right.
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Speaker 3: You have companies like ucb R, gen x, al nylem b,
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Speaker 3: one Insmed, and then of course we just saw the
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Speaker 3: Phase three data from Revmed a few days ago in
10:13
Speaker 3: pancreatic cancer. That's that's going to be one of the
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Speaker 3: next major ones, right. That company is already a thirty
10:19
Speaker 3: billion dollar market camp. So I think the combination of
10:21
Speaker 3: those things, especially the change in fundamentals, has made it
10:26
Speaker 3: so that this balance is much healthier. You know, you
10:29
Speaker 3: mentioned you know, IPOs just as one example as the
10:33
Speaker 3: marker of where we are on the cycle. I think
10:34
Speaker 3: it's trying to normalize.
10:36
Speaker 1: Right.
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Speaker 3: Last year was a very low number of IPOs sub ten.
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Speaker 3: This year, even though the war has caused a bit
10:42
Speaker 3: of a pause. In January and February you had six,
10:47
Speaker 3: you know, versus the eight in total last year. And
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Speaker 3: the first IPO that's made it out, which was Kylera
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Speaker 3: a few days ago since the war started, and did
10:55
Speaker 3: very very well.
10:56
Speaker 1: Right.
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Speaker 3: It priced I think at the top end of the
10:58
Speaker 3: range and it traded up six percent on the first
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Speaker 3: day of trading. So far. To guess, as long as
11:03
Speaker 3: you know, geopolitics doesn't get worse from here, and hopefully
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Speaker 3: it gets better. I still think this year you're going
11:10
Speaker 3: to continue to see this normalization as we're kind of,
11:13
Speaker 3: you know, starting this hopefully a long bull market cycle.
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Speaker 2: Cool. You touched on it on the FDA.
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Speaker 1: In fact, you had it in the bucket out of
11:20
Speaker 1: the three areas that you picked on of being equalizing.
11:24
Speaker 1: I think maybe that's the right phrase. I can't remember
11:26
Speaker 1: what you said, but how sure are we about that?
11:29
Speaker 1: Because we've had some situations where you know, there there
11:32
Speaker 1: is perhaps some I would say, political interference, which is
11:36
Speaker 1: not meant to be the case.
11:37
Speaker 2: You get some back and forth with regards.
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Speaker 1: To the what could be approved by what won't be approved,
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Speaker 1: What is the strategy and who is running the decision making?
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Speaker 1: Is it the career scientists within the FDA, the career regulators?
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Speaker 1: Just do you want to dive in a little bit there,
11:54
Speaker 1: maybe tell us if there are any areas left that
11:57
Speaker 1: you're maybe worried about. I mean, I've heard you speak
11:59
Speaker 1: about diseases a little bit here and there. We hear
12:02
Speaker 1: very nice positive things from the FDA, and then when
12:05
Speaker 1: it comes to the action, it's a little bit more mixed.
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Speaker 2: So just took us through them.
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Speaker 3: Yeah, I think you're exactly right. I think under the
12:12
Speaker 3: umbrella of policy uncertainty, the big outstanding one is these
12:17
Speaker 3: issues at the FDA that you mentioned, you know, in
12:19
Speaker 3: contrast to manufacturing, reshoring and international drug pricing. I think
12:25
Speaker 3: FDA remains the big issue. Now we're going to frame
12:28
Speaker 3: it this way. I think the focus is actually specifically
12:32
Speaker 3: in rare disease. That's where we're seeing I think the biggest,
12:36
Speaker 3: the biggest gaps or setbacks, And you know, I don't
12:39
Speaker 3: think it's any secret that the leadership of Sieber under
12:42
Speaker 3: Vena Prosad seems to have shifted towards less regulatory flexibility.
12:47
Speaker 3: You know, then a before his career at FDA, you know,
12:52
Speaker 3: published significantly specifically in cancer and a lot of his
12:56
Speaker 3: writings he's skeptical that a lot of cancer drugs are
13:00
Speaker 3: effective or worth the cost. Right, So, I do think
13:03
Speaker 3: it's there's this opportunity now that Vene is on his
13:07
Speaker 3: way out. I believe this month or next month, there's
13:10
Speaker 3: this opportunity to change leadership and course correct. And our
13:14
Speaker 3: sense of things is that FT has heard that message
13:17
Speaker 3: that there is an issue here specifically with rare disease
13:20
Speaker 3: and specifically within SEBER, and I'm hoping or optimistic that
13:23
Speaker 3: they'll take the opportunity to put leadership in place that's
13:27
Speaker 3: more pro rare disease and regulatory flexibility. I do think,
13:31
Speaker 3: you know, you need to have leaders that are pro
13:34
Speaker 3: innovation to address this issue, because by definition, if you're
13:39
Speaker 3: going to be a supporter of regulatory flexibility that takes
13:42
Speaker 3: leadership right in the regulations themselves, it's going to skew
13:46
Speaker 3: conservative And so for those diseases and technologies where there's
13:50
Speaker 3: an unmet need and you want to shift that balance.
13:53
Speaker 3: It's not going to be in the regulations by definition.
13:55
Speaker 3: That requires leadership to be able to exercise that flexibility
13:59
Speaker 3: and offer it to drug developers. So, you know what,
14:02
Speaker 3: We'll see what happens with new leadership. But we're cautiously optimistic.
14:07
Speaker 1: Okay, let's keep fingers crossed to see who replaces doctor Prisoad.
14:11
Speaker 1: You know, quite a few of us were probably listening
14:14
Speaker 1: to him. I did a couple of years of almost
14:17
Speaker 1: exclusively vaccines, and I could I do remember his strong
14:20
Speaker 1: views there, and I also it all sounds quite mixed here.
14:24
Speaker 1: I also cover myloma intelligence, and I do know he's
14:27
Speaker 1: got very strong views against using imardine negativity as a
14:31
Speaker 1: as a way of getting drugs approved early on, because
14:34
Speaker 1: survival has got so amazingly long in especially early early detected.
14:40
Speaker 2: Maloma, let alone smoltering myloma.
14:43
Speaker 1: I'm getting into the weeds a bit here that you
14:45
Speaker 1: just can't expect companies to wait five years to see
14:48
Speaker 1: a survival signal, and that maybe having a drug that
14:51
Speaker 1: gives you this minimum residual or measurable residual disease negativity
14:55
Speaker 1: at the level that it does that you deny patients that,
14:59
Speaker 1: So let's see who comes in.
15:00
Speaker 2: I think there is hopefully.
15:03
Speaker 1: I think some of the signals that we've seen from
15:05
Speaker 1: recent people who have been added along the various agencies
15:09
Speaker 1: is beginning to make me feel a little bit optimistic
15:12
Speaker 1: with regards to who might replace doctor Prasad.
15:14
Speaker 2: But we'll find out. So use I mean, I have
15:17
Speaker 2: these questions in different orders.
15:19
Speaker 1: But you spoke about China and are really quite you know,
15:22
Speaker 1: I've been going to China for over twenty years from
15:25
Speaker 1: the days where pretty much what was going on was
15:28
Speaker 1: the very beginnings of doing univative work, some of the
15:31
Speaker 1: work that was being done at Hutchmad all those years ago,
15:34
Speaker 1: which then, of course Hatmad was one of the few
15:36
Speaker 1: that led to a whole bunch of executive leaving and
15:39
Speaker 1: becoming leaders of other companies. So one of the things
15:42
Speaker 1: that occurred to me is, and you know, I've just
15:44
Speaker 1: been at AACR conference, the Association for the of Cancer Research.
15:50
Speaker 1: I can't remember the full data, and looking around talking
15:53
Speaker 1: to various people, a whole bunch of friends from different
15:56
Speaker 1: parts of the institutions in the US, you feel the
16:00
Speaker 1: strength of the innovative science that happens the science that
16:05
Speaker 1: happens in the US, and I'm still wondering where China
16:08
Speaker 1: is on that continuum. I can see, obviously the brute
16:12
Speaker 1: force of ability and experimental approach, where nobody would have
16:16
Speaker 1: tried a VEGFPD one inhibitor by specific suspect in Europe
16:21
Speaker 1: or the US, or being.
16:24
Speaker 2: Able to get the funding for it, and yet China did.
16:26
Speaker 2: Now we're seeing some of.
16:27
Speaker 1: The try specifics with aisle two added or some other
16:30
Speaker 1: molecular added to one side of it.
16:32
Speaker 2: So that's all great.
16:33
Speaker 1: What I'm looking for is are we seeing and you
16:37
Speaker 1: probably are one of the best place people to tell
16:39
Speaker 1: me this in the background science, are we seeing the
16:42
Speaker 1: evolution into really hardcore innovative stuff, new molecular clues, new
16:49
Speaker 1: mechanisms for or understanding of mechanisms of protein protein interactions.
16:53
Speaker 2: Et cetera. What's your what are your thoughts there?
16:56
Speaker 1: How far is China from I mean, they clearly have
16:58
Speaker 1: the money and there's a said that the number of
17:01
Speaker 1: PhDs that are being generated.
17:03
Speaker 2: So how do you see this?
17:05
Speaker 3: Yeah? I think you actually gave a great example, you know,
17:09
Speaker 3: of the combination of two targets like PD one and Jeff,
17:13
Speaker 3: I kind of think of it in three broad buckets. Right,
17:15
Speaker 3: there's the traditional iterative innovation on existing drug target and
17:20
Speaker 3: we all know that China is remarkably efficient at doing
17:24
Speaker 3: that job, right, the bio better or me better bucket.
17:28
Speaker 3: Then there's the middle bucket that you mentioned that does
17:32
Speaker 3: take some creativity, right in combining two things that you
17:35
Speaker 3: wouldn't have thought of or three things. I feel like
17:38
Speaker 3: China's really come on very strong in that bucket specifically
17:43
Speaker 3: really in the last couple of years. It's a pretty
17:45
Speaker 3: new phenomenon, but it's growing very rapidly in that breakthrough science,
17:50
Speaker 3: you know, borderlines sci fi bucket, you know, new modalities,
17:54
Speaker 3: brand new first in disease targets. I think it's still
17:58
Speaker 3: very early days. I think there's reasons for that when
18:00
Speaker 3: you think about the ecosystem, right. You mentioned they have
18:04
Speaker 3: just a huge number of talented scientists, right, I think
18:07
Speaker 3: it's somewhere around two times the number of scientists that
18:10
Speaker 3: we have in the US. But you know, if you
18:13
Speaker 3: think about, for example, NIH funding as a proxy for
18:18
Speaker 3: things that go to the earliest stage science, breakthrough or
18:21
Speaker 3: basic science. You know, the NIH budget, grant budget, I
18:24
Speaker 3: think is still five maybe as high as ten times
18:27
Speaker 3: higher than in China, So they still have a ways
18:30
Speaker 3: to go there. But you know, as we know, relevance
18:34
Speaker 3: near term and medium term to drug development and the
18:37
Speaker 3: production of new impactful medicines are heavily reliant on the
18:41
Speaker 3: first two buckets. So I think their impact, you know,
18:45
Speaker 3: it's already being felt in terms of the drug industry,
18:48
Speaker 3: but it's really going to be outsized over the medium
18:51
Speaker 3: term in terms of their ability to change kind of
18:54
Speaker 3: the global ecosystem for drug discovery, right and the medicines
18:59
Speaker 3: that we actually get to PATS.
19:01
Speaker 1: I mean, look, I always enjoy my time there because
19:03
Speaker 1: I find the energy. And they hate the phrase when
19:06
Speaker 1: I say one of the reasons for success in China
19:08
Speaker 1: is hard work. They said, some of the people told me,
19:11
Speaker 1: don't say that again. Everybody tries to work hard, right.
19:13
Speaker 1: But what's interesting is that if we track, like many
19:16
Speaker 1: other companies do, licensing partnership deals across all regions, and
19:22
Speaker 1: I've found that in the past year, maybe starting to
19:25
Speaker 1: trickle in or not trickle in to see it start
19:28
Speaker 1: pick up in twenty twenty four, but certainly twenty twenty five,
19:30
Speaker 1: and still in twenty twenty six, a meaningful jump twofold
19:34
Speaker 1: threefold jump in the number of platform discovery type deals,
19:37
Speaker 1: which tells you a little bit more about the at
19:39
Speaker 1: least the capabilities, But of course it also tells you
19:42
Speaker 1: that I think that's one thing we can't ignore that
19:47
Speaker 1: they probably companies who are put in a billion dollars
19:50
Speaker 1: into a discovery deal, say Lily Innovant, right, I think
19:54
Speaker 1: Lily is probably getting I mean, it depends what people.
19:57
Speaker 2: Different people tell me, different.
19:58
Speaker 1: Multipliers thought it was worth of effort out of that
20:02
Speaker 1: if it was being done here, and they can get
20:04
Speaker 1: those money cuds much quicker into phase one and get
20:06
Speaker 1: their readout. So I have to try and figure a
20:09
Speaker 1: way out of being able to distinguish the reason being
20:13
Speaker 1: that that they're doing the deals versus actually there's something
20:17
Speaker 1: super novel in what they're doing here.
20:18
Speaker 2: So I don't know if you have any thoughts on that.
20:21
Speaker 3: No, I think that's the right way to think about it.
20:23
Speaker 3: I kind of broadly think of China. You know from
20:27
Speaker 3: our experience there that they can do things in at
20:30
Speaker 3: least half the cost, as a broad generalization, and at
20:32
Speaker 3: least half the time, and they can often beat on
20:36
Speaker 3: both of those, So that's exactly right. You know, people
20:39
Speaker 3: like partnering with Chinese innovators because it's just a really,
20:42
Speaker 3: really efficient way to do things, and there's a lot
20:45
Speaker 3: of great talent there. And to your point, you know,
20:48
Speaker 3: this really accelerate dramatically, really, I think in the last
20:52
Speaker 3: three years. But that was because all the ingredients of
20:55
Speaker 3: the you know, the foundation that you need to make
20:58
Speaker 3: that possible was accomplished over the the previous call it
21:01
Speaker 3: half dozen years, right, And you know what they accomplished
21:05
Speaker 3: as an ecosystem really is quite remarkable because you know,
21:09
Speaker 3: we used to take for granted that what we have
21:11
Speaker 3: in the US really cannot be replicated. And the reason
21:14
Speaker 3: we were confident in that is because it's never been
21:16
Speaker 3: replicated anywhere else in the world. Right, So that China
21:20
Speaker 3: could do it and then not only that, but now
21:22
Speaker 3: have some of these natural advantages and costs and speed
21:26
Speaker 3: is really quite an accomplishment. So you know, I think
21:29
Speaker 3: they're going to be obvious kind of Number two very
21:32
Speaker 3: important player. You know, as we go forward for the
21:35
Speaker 3: foreseeable future.
21:36
Speaker 1: One of the conversations that comes up often in my
21:38
Speaker 1: US colleagues is trying to threat to the US why
21:41
Speaker 1: I take ecosystem, I mean, I never see it like that.
21:44
Speaker 1: I always think competition is how evolution functions, and evolution
21:48
Speaker 1: is good. If the US needs to do something different,
21:51
Speaker 1: that's what it needs to do. But tell me what
21:52
Speaker 1: your perspective is. Do you see it as a threat?
21:55
Speaker 3: Yeah? Well, you know, in every whenever there's new competition,
21:58
Speaker 3: there's going to be winners and losers. I can tell
22:00
Speaker 3: that the biggest winner, number one is patients right all
22:03
Speaker 3: around the world, including American patients, because the more drugs
22:06
Speaker 3: you have, the better. But in terms of, you know,
22:08
Speaker 3: players in the ecosystem and kind of whether they're economic
22:12
Speaker 3: winners or losers, I think right now and for I
22:15
Speaker 3: would say the foreseeable future, probably the single biggest economic
22:19
Speaker 3: winner is pharma, right and that specifically because China has
22:23
Speaker 3: become a source of pipeline innovation for them that is
22:26
Speaker 3: fast and inexpensive, as we already talked about. And because
22:30
Speaker 3: Chinese companies, even the biggest one, which is hongre to
22:33
Speaker 3: fifty billion dollars publicly trade market cap company, they absolutely
22:37
Speaker 3: have the resources to, you know, try to broaden out
22:39
Speaker 3: beyond China to the rest of the world. But they
22:42
Speaker 3: have chosen not to. So even the largest companies are
22:45
Speaker 3: basically staying focused on the Chinese market, which means the
22:50
Speaker 3: vast bulk of the value that accrues from the innovation
22:53
Speaker 3: that they create will then go to their partners, which
22:55
Speaker 3: are the biggest chunk of those will be multinational pharma
22:59
Speaker 3: company right to bring those drugs to market. Now, of course,
23:02
Speaker 3: there are going to be losers. I think the biggest
23:05
Speaker 3: bucket of losers will be you know, Western or US
23:08
Speaker 3: based early stage biotech companies that now have to run
23:12
Speaker 3: that race against entrepreneurial Chinese companies that have these advantages
23:17
Speaker 3: of cost and speed. So as a group, they will
23:20
Speaker 3: be the losing group. But I think you know that
23:23
Speaker 3: competition is definitely good for science.
23:26
Speaker 2: So let me ask you a question.
23:27
Speaker 1: Why not when you come to form a company next,
23:29
Speaker 1: set up a sister or brother or whatever they want
23:32
Speaker 1: to call it, a subsidiary in China for being able
23:36
Speaker 1: to run and take advantage of those advantages.
23:40
Speaker 2: Why not do it that way. I actually heard somebody
23:42
Speaker 2: tell me that that literally that's what they're doing. They're
23:44
Speaker 2: setting up a.
23:44
Speaker 1: Company here, another one in China is going to be
23:47
Speaker 1: responsible for I don't know what they're doing with their
23:49
Speaker 1: intellectual property, were responsible for doing some of the fast
23:54
Speaker 1: science and maybe some of the definitely clinical development. Is
23:58
Speaker 1: that not something that a whole bunch of companies can replicate?
24:00
Speaker 1: What would be in the way of that?
24:02
Speaker 3: I think it's a great idea. I think most of
24:05
Speaker 3: the large pharmas have done exactly that. In fact, many
24:09
Speaker 3: have been doing that for quite a number of years
24:11
Speaker 3: and actually help China build up the ecosystem and develop
24:14
Speaker 3: their talent. So, but you're exactly right, I think now
24:18
Speaker 3: that should filter down to smaller companies who should you know,
24:21
Speaker 3: build teams and infrastructure in China, you know, just as
24:25
Speaker 3: an example, one of those advantages. One reason they're fast
24:29
Speaker 3: and inexpensive is because they have integrated supply chains there, right,
24:33
Speaker 3: so you can produce your drug candidates much more quickly
24:37
Speaker 3: and much more cheaply. You can iterate that more quickly.
24:40
Speaker 3: So why wouldn't you want to have some of those
24:42
Speaker 3: functions there at least for the early stage you know,
24:44
Speaker 3: in discovery, and then same thing for translational development. The
24:48
Speaker 3: patient population is huge there. The number of patients available
24:52
Speaker 3: for clinical trials corresponds to that you can run clinical
24:55
Speaker 3: trials super efficiently there. They're a little bit less bureaucratic
24:59
Speaker 3: than some of the comple academic medical centers that you
25:01
Speaker 3: have in the US now that have been around a
25:03
Speaker 3: long time, and so that you start getting layers of
25:05
Speaker 3: bureaucracy which they have less of. So it absolutely makes
25:09
Speaker 3: sense to have teams out there to take advantage of that.
25:12
Speaker 1: I mean, one of the things I wonder about sometimes
25:14
Speaker 1: is whether early human trials, and this is not saying
25:17
Speaker 1: anything unethical or anything of For example, a molegus, say,
25:22
Speaker 1: say a car tie that needs to be evolved, maybe
25:26
Speaker 1: the way that you do the internal domains or the
25:28
Speaker 1: costumilitary domains you need to evolve, then you can actually
25:31
Speaker 1: test those impatients and not evolve them, but test two
25:35
Speaker 1: or three iterations.
25:36
Speaker 2: And now I don't know if that's going to be
25:38
Speaker 2: doable here. In fact, at the.
25:40
Speaker 1: ACR meeting pre meeting that's organized for partnering type event,
25:45
Speaker 1: Dana Graybush from a lyric was interviewing Rick Pastor, and
25:49
Speaker 1: she asked him, why wouldn't you think it possible that
25:53
Speaker 1: in order to move the bar in mine oncology, rather
25:56
Speaker 1: than going one molecule by one molecule, adding it to a.
25:58
Speaker 2: PDO one or a pedio one. We do like a
26:01
Speaker 2: basket of throwing.
26:03
Speaker 1: I mean to a degree, some of the trials that
26:05
Speaker 1: I've seen astrozeneca for instances, got the Coast trial that
26:08
Speaker 1: that kind of does that a little bit. But it's
26:10
Speaker 1: not like you're still doing one plus one as opposed
26:13
Speaker 1: to one plus two or one plus three to see
26:15
Speaker 1: whether that.
26:15
Speaker 2: Makes a difference.
26:16
Speaker 1: And I think Rick said, well, you want to make
26:19
Speaker 1: sure that you're not just exposing people to a bunch
26:21
Speaker 1: of placebo that gives them some side effect profile. But
26:24
Speaker 1: that is the sort of thing that I think sometimes
26:26
Speaker 1: needs to be done. I don't know if it ever
26:28
Speaker 1: will be able to be done in the US. So
26:31
Speaker 1: while you answer that question, also consider for me, please,
26:34
Speaker 1: what are the things that the US can do now
26:36
Speaker 1: to try and close that gap with China.
26:38
Speaker 3: Yeah, you know, I think you bring up some really
26:41
Speaker 3: good examples there. I think some of the gap. You're right,
26:45
Speaker 3: it comes down to there's a different balance of risk awards,
26:50
Speaker 3: specifically for first in man trials, which may be a
26:53
Speaker 3: preference that's not going to change, right, So we're more
26:56
Speaker 3: concerned with the downside in the US that's naturally going
26:59
Speaker 3: to slow US down a little bit. And that's why
27:00
Speaker 3: even before you had the emergence of China, a lot
27:03
Speaker 3: of Phase one trials had shifted offshore, specifically to the UK, Australia,
27:08
Speaker 3: New Zealand that have become the preferred Phase one trial
27:12
Speaker 3: locations a lot for a lot of diseases, right, So
27:15
Speaker 3: China is not changing that, they're just adding another location
27:18
Speaker 3: where that balance is also favorable. You know, I think
27:21
Speaker 3: one example of how China is on what one end
27:25
Speaker 3: of that risk tolerance spectrum is your ability to explore
27:30
Speaker 3: kind of exactly the scenarios that you're talking about in
27:32
Speaker 3: investigator sponsored or IT studies. They're much more permissive in
27:37
Speaker 3: China for those versus the US. It gives them the
27:40
Speaker 3: flexibility to iterate and experiment and kind of shift gears
27:44
Speaker 3: much more rapidly and flexibly. Okay, So some of those
27:48
Speaker 3: things we're not going to be able to change in
27:50
Speaker 3: a meaningful way because it's a societal risk benefit balance
27:55
Speaker 3: that we're making. But to your point, there's still tons
27:58
Speaker 3: of opportunity to speed things up. The US can innovate
28:02
Speaker 3: in terms of trial designs. You're not running separate protocols,
28:05
Speaker 3: but you have these combined protocols both by stage as
28:08
Speaker 3: well as by what you're studying, you know, so these
28:11
Speaker 3: umbrella kinds of protocols. You know, one of the biggest
28:14
Speaker 3: frictions that we have in the US is the whole
28:16
Speaker 3: IRB process and contracting process. When you go from one
28:21
Speaker 3: protocol to the next. Part of that's bureaucracy at the
28:24
Speaker 3: institutional level. It's very very hard to change. But you
28:28
Speaker 3: can navigate around it by putting things under a single protocol,
28:32
Speaker 3: so you only go through that once and you're seeing
28:35
Speaker 3: you know, you've been seeing a shift towards that already,
28:39
Speaker 3: and I think we just need to be more creative
28:40
Speaker 3: and more aggressive with using tools like that. The other
28:43
Speaker 3: way that the US can innovate is to be kind
28:46
Speaker 3: of at the front of the pack in terms of
28:47
Speaker 3: our use of new technologies, right, data science, AI, right,
28:52
Speaker 3: both of those things. For example, in the former with
28:54
Speaker 3: data science using real world data and being creative very
28:58
Speaker 3: early days on that, but then also an AI getting
29:00
Speaker 3: all the efficiencies as possible out of that trial conduct process.
29:05
Speaker 3: This is not the sexiest stuff that people talk about,
29:07
Speaker 3: but for example, just the document production part of the
29:10
Speaker 3: process over a clinical development program probably takes a year
29:15
Speaker 3: to eighteen months right in total across the seven to
29:18
Speaker 3: ten years that takes to develop the drug. If you
29:21
Speaker 3: can dramatically decrease that with AI, you're going to save
29:25
Speaker 3: material amounts of time.
29:26
Speaker 1: I think I have the fortune of listening to Patrick
29:30
Speaker 1: Troub of Actually I don't remember if I've done a
29:32
Speaker 1: podcast with him, but I might.
29:33
Speaker 2: Get him who's at GSK, who's in charge.
29:37
Speaker 1: Of the AI there, and he calls that the white
29:39
Speaker 1: space in the development process. He says, you know, that
29:42
Speaker 1: white space is really amenable to meaningful change. Let's hope
29:46
Speaker 1: that happens, and we come back to AI in a minute.
29:49
Speaker 1: But let me just close off this conversation by you
29:53
Speaker 1: highlighted one of the key things about the NIH investment
29:56
Speaker 1: in very early research. Of course, I then have din as,
29:59
Speaker 1: a conversations and coffees with friends who work at different
30:03
Speaker 1: institutions across the US, and they're all, without exception, very
30:09
Speaker 1: worried about science funding in the US and the way
30:12
Speaker 1: that it's being altered by the current administration. And you know,
30:17
Speaker 1: so I do worry sometimes that of course, nobody likes
30:20
Speaker 1: their a fifty man lab to be asked to be
30:23
Speaker 1: reduced to forty five. But whatever the impact is, I
30:26
Speaker 1: wonder if you had a view on that or what
30:28
Speaker 1: you've been hearing what I heard particularly at ACR at
30:32
Speaker 1: the conversation started last year, but it just seemed like
30:36
Speaker 1: there were quite a few desperate folks around. But I
30:39
Speaker 1: don't know what the how broadly worriesome that is because
30:43
Speaker 1: that takes one of those key initiatives or advantages in
30:47
Speaker 1: the US away, or starts to take it away. On
30:49
Speaker 1: the other hand, sorry, you could consider this too. What's
30:52
Speaker 1: the alternative? Where are these people are going to go?
30:53
Speaker 1: Europe doesn't have any as much money as you would
30:56
Speaker 1: like to have. You know, we have to invest in defense,
30:59
Speaker 1: we have to invest in everything.
31:01
Speaker 2: But where else do they go? So just talk around that, please?
31:05
Speaker 3: Yeah, sure, you know, I think you're totally right. There's
31:09
Speaker 3: a lot of anxiety out there about the direction of
31:13
Speaker 3: NIH funding because it's going down right, and there there
31:17
Speaker 3: is this uncertainty as well, because there's a proposed I
31:20
Speaker 3: think up to forty percent cut which did not happen,
31:23
Speaker 3: But that causes uncertainty and the general direction is is downward.
31:28
Speaker 3: Now let me put that. So all the people out
31:31
Speaker 3: there that are really really upset about this. I totally
31:34
Speaker 3: get it. But let's just take a big step back
31:37
Speaker 3: for a second and zoom out to put it into
31:39
Speaker 3: context about what does it mean for American leadership? To
31:42
Speaker 3: your point, you know, are we shooting ourselves in the
31:45
Speaker 3: foot and we're going to lose our lead? So just
31:48
Speaker 3: to contextualize it, you know, I think NIH grant funding
31:51
Speaker 3: each year somewhere around forty billion dollars or so. As
31:55
Speaker 3: I mentioned already, that is the biggest single source of
31:58
Speaker 3: government funding for basic science around the world by a
32:01
Speaker 3: country mile. You know, China is at least five times less,
32:04
Speaker 3: maybe up to ten times less, somewhere in that range.
32:07
Speaker 3: And you know, you know, if we did have a
32:09
Speaker 3: forty percent cut, I would have said that's going to
32:11
Speaker 3: be seriously damaging. But so far that hasn't occurred. So
32:15
Speaker 3: what ended up happening so far? I think for the
32:17
Speaker 3: NIH budget for twenty six is it's going to be flat, right,
32:21
Speaker 3: So context wise, I think the sky isn't following Following
32:26
Speaker 3: we will maintain our leadership position. You know, if it
32:30
Speaker 3: does change in a major way in the future, you know,
32:33
Speaker 3: that would be a reason to be worried. But I'm
32:36
Speaker 3: not worried because of what's happened so far that we're
32:38
Speaker 3: going to lose our leadership position.
32:41
Speaker 2: Okay, so let's talk about AI. You brought the subject up.
32:44
Speaker 1: We talked about the much less sixty part of it,
32:46
Speaker 1: which is helping clinic control or going from phase to phase,
32:50
Speaker 1: and maybe the organization will be identification of patients. Talk
32:54
Speaker 1: to us please about where else you see real value
32:58
Speaker 1: being added as opposed to hype for want of a
33:01
Speaker 1: better phrase, you know, the drug discovery. I talked to
33:04
Speaker 1: one very well known chemist and he says, well, yeah,
33:08
Speaker 1: I can use these tools, but at the end of
33:11
Speaker 1: the day, it still comes down to the work that
33:13
Speaker 1: we have to normally do. So just where do you
33:16
Speaker 1: see in the continuum of the life of a drug
33:21
Speaker 1: from inception to getting to patients? Yeah, real value being
33:25
Speaker 1: added today?
33:26
Speaker 3: Yeah. So we talked a little bit already about kind
33:28
Speaker 3: of the efficiency benefits of these kind of during the
33:32
Speaker 3: clinical trial phase. I think the actual biggest benefits are
33:35
Speaker 3: in the drug discovery phase. And you know, the big
33:38
Speaker 3: caveat here is it's super early days, right, So it's
33:42
Speaker 3: not like we have statistics around these things. But I
33:44
Speaker 3: do have a sense that, and I'll try to frame
33:47
Speaker 3: out the way I kind of think about it. But
33:50
Speaker 3: in terms of drug discovery, there's two major buckets I
33:53
Speaker 3: kind of put the application of AI in so far.
33:56
Speaker 3: One is in target discovery and the other is in
34:00
Speaker 3: the design of drugs. So in target discovery, there's a
34:04
Speaker 3: lot of things that we do now or the industry
34:06
Speaker 3: does to discover drugs that really are well suited to
34:09
Speaker 3: AI because they're large data sets, right, and they're complex questions.
34:13
Speaker 3: That's very difficult for the human mind to kind of
34:15
Speaker 3: crunch through large amounts of information. So examples, you know,
34:19
Speaker 3: libraries of small, small molecules and trying to prioritize what
34:23
Speaker 3: are the more interesting ones. Protein modeling, right, alpha fold.
34:28
Speaker 3: A lot of people have heard of the benefits of
34:30
Speaker 3: alpha fol. Now you can predict what a protein's going
34:33
Speaker 3: to look like based on maybe just the sequence genetic
34:37
Speaker 3: data here, I think is intuitively obvious. Right. You can
34:39
Speaker 3: take people with the disease, you compare with genetic databases
34:42
Speaker 3: and you can hypothesize what are the likely causes of
34:46
Speaker 3: the disease, and that's very powerful stuff. And then pairing
34:49
Speaker 3: that with things like EMR data, which we're increasingly having
34:54
Speaker 3: available another example of large, complex, sometimes messy data sets
34:58
Speaker 3: perfect for AI to crunch through. So I think those
35:02
Speaker 3: are just some of the key kind of exercises that
35:07
Speaker 3: have to be done for target discovery that I think
35:10
Speaker 3: AI will have a meaningful contribution to. In drug design,
35:14
Speaker 3: you have things like three D eighted design again I
35:18
Speaker 3: think well suited to AI. And then traditional med can right,
35:23
Speaker 3: like you have a molecule, there are you know, a
35:25
Speaker 3: thousand different ways you can modify it, you know, having
35:28
Speaker 3: an AI assist to say, well, what are the top
35:30
Speaker 3: one hundred ways, So that then a great medicinal chemist
35:33
Speaker 3: can go in and say, what does my judgment, experience
35:36
Speaker 3: and intuition tell me to take it from here? So
35:39
Speaker 3: and what could that translate into. I actually like to
35:43
Speaker 3: use the China discussion as a good analogy. Right We
35:46
Speaker 3: talked about how they have probably two times the number
35:49
Speaker 3: of scientists as the States have to cost half the time,
35:52
Speaker 3: and what has that gotten you? And that's a purely
35:55
Speaker 3: manual thing. Right In the last three years, they're now
35:58
Speaker 3: thirty percent of ear least stage drug discovery innovation. So
36:03
Speaker 3: I kind of think that's a good bar for the
36:05
Speaker 3: minimum of what you might expect for AI's application to
36:09
Speaker 3: target discovery and drug design, because I would guess that
36:12
Speaker 3: it's going to be you know, you'll increase a single
36:15
Speaker 3: scientist productivity at least two x, right, so I think,
36:19
Speaker 3: and if you believe higher, you think it might increase
36:22
Speaker 3: a scientist productivity by three x. Then just multiply those numbers.
36:26
Speaker 3: So I expected really to have a major impact. And
36:29
Speaker 3: combined with China, you know, I think innovation is going
36:33
Speaker 3: to continue to accelerate over the next five to ten years.
36:37
Speaker 1: So Rod, you're with your obvious current hat on and
36:41
Speaker 1: the old cell side experience. I'm sure I used to
36:45
Speaker 1: building models for let's take a phase one drug or
36:48
Speaker 1: let's take it pre clinical drug. You're putting it through,
36:52
Speaker 1: forecast the years, put your probably success. What does that
36:55
Speaker 1: look like if you're applying AI on top of it.
36:58
Speaker 1: So not not AI to more, but AI to say, now,
37:01
Speaker 1: I'm going to do this for a drug that's being
37:04
Speaker 1: developed with AI being applied everywhere along the value chain
37:08
Speaker 1: or the development line, so we're reducing the time to
37:11
Speaker 1: market because we're shortenly in the clinical trial period. We
37:15
Speaker 1: of course, one of the problems I have is that
37:17
Speaker 1: IRA kind of gets in the way of the value
37:20
Speaker 1: you add by being nothing to do with the length
37:24
Speaker 1: of pattern that you've got, So that upsets me a
37:27
Speaker 1: little bit. It doesn't matter how hard you work to
37:29
Speaker 1: get it more moleculed to market. It's good for patients,
37:32
Speaker 1: it still doesn't make any difference because you've got that
37:34
Speaker 1: time set to make money out of it. But let's
37:36
Speaker 1: say you do that, and you do you modulate your
37:39
Speaker 1: probability of success because you've had more the human and
37:43
Speaker 1: the artificial intelligence added into it.
37:46
Speaker 2: So where do you see the most Where do I
37:48
Speaker 2: get that MPV accretion?
37:50
Speaker 3: Yeah, so you know, when I started in my career,
37:53
Speaker 3: the stats I remember for drug discovery was when you
37:58
Speaker 3: have a drug and it is first man, you have
38:01
Speaker 3: about a three percent chance of making across the finish line,
38:04
Speaker 3: and the average amount of time it would take was
38:06
Speaker 3: somewhere north of ten years to get to approval. Now
38:10
Speaker 3: let's take kind of the example of the exact opposite extreme.
38:15
Speaker 3: Now this is biased because you have to pick the
38:18
Speaker 3: modalities are the most mature with the highest probability of success.
38:23
Speaker 3: So antibodies are a good example. You know, a big
38:27
Speaker 3: chunk of the reason is because you're much less likely
38:30
Speaker 3: to have off target side effects, just unanticipated side effects.
38:34
Speaker 3: RNA medicines have emerged to be somewhere in that zip
38:37
Speaker 3: code as well. So when you have something like that
38:39
Speaker 3: and it's for let's say, you know, a relatively homogeneous
38:44
Speaker 3: disease with a high and met need, the numbers are
38:46
Speaker 3: somewhere north of thirty percent success from first and man
38:50
Speaker 3: and can be as quick as four years to the
38:53
Speaker 3: finish line. So I think everywhere in between is kind
38:57
Speaker 3: of this opportunity to improve thanks to AI, thanks to
39:01
Speaker 3: other things, you know, data science as a separate bucket,
39:05
Speaker 3: thanks to the speed of China, all these things. So
39:07
Speaker 3: I expect when you're starting at three percent in ten
39:10
Speaker 3: plus years, it's actually not very hard to shift the
39:14
Speaker 3: industry statistics in a positive way. That's so meaningful, right,
39:18
Speaker 3: because if you take three percent to six percent average,
39:20
Speaker 3: take ten years to seven years, which I think I
39:23
Speaker 3: think are easy assumptions, the return on invested capital, to
39:27
Speaker 3: your point, improves dramatically. And just to put that in
39:30
Speaker 3: context for people, because I think a lot of people
39:32
Speaker 3: don't think about the financials of the industry. Again, when
39:35
Speaker 3: I started all the analysis that I saw and there's
39:39
Speaker 3: this really good analysis people referred to by Deloitte that
39:43
Speaker 3: analyze this. The return on invested capital of drug discovery
39:47
Speaker 3: for pharmaceutical companies was low single digit, okay, and that's
39:53
Speaker 3: when the average large fully mature company is spending between
39:57
Speaker 3: twenty and twenty five percent of revenue every year on
40:02
Speaker 3: R and D. So overlay it on that. If you
40:06
Speaker 3: increase the odds from three to six percent, shorten the time,
40:11
Speaker 3: a low single digit return on invested capital all of
40:14
Speaker 3: a sudden become actually interesting. It could you double could
40:17
Speaker 3: become a double digit and start comparing to maybe tech,
40:22
Speaker 3: and that would really change from an investor's perspective, change
40:26
Speaker 3: their view of the industry as a whole. So, you know,
40:29
Speaker 3: we've been talking about, oh, we're getting out of this
40:31
Speaker 3: bear market and things are getting better, but this is
40:34
Speaker 3: a separate conversation of not only could things get better,
40:37
Speaker 3: but this could actually become a very, very attractive industry
40:40
Speaker 3: when historically the economics have been modest.
40:43
Speaker 1: I think we can do a podcast just on this topic. Yeah,
40:46
Speaker 1: and you know, get a group of folks. It is
40:48
Speaker 1: fun modeling it. I have to say, that's one of
40:50
Speaker 1: the things that I've always enjoyed doing so we have.
40:53
Speaker 2: Tried to model it.
40:54
Speaker 1: We get to ridiculous numbers in some cases if you
40:57
Speaker 1: go to the top end of what you were talking about,
40:58
Speaker 1: thirty percent, et cetera.
41:00
Speaker 2: So last question on this, where will that value add?
41:04
Speaker 2: Who would the crew to? What do the crew to?
41:06
Speaker 2: Shareholders a crew to?
41:08
Speaker 1: I mean, obviously, if you if you just put this
41:10
Speaker 1: into the bearer of what PNN looks like, you're just
41:13
Speaker 1: going to get a much bigger operating margin, let's say,
41:15
Speaker 1: But is society going to be able to accept that
41:17
Speaker 1: and drug prices stay as they are?
41:20
Speaker 2: That's the bit I struggle a bit of bit.
41:21
Speaker 3: Yeah, I think that's a great question. So first, I think,
41:24
Speaker 3: you know, if if the process overall becomes more capital efficient,
41:30
Speaker 3: it's going to that value will of course accrue to
41:33
Speaker 3: all companies, big and small. You know, I think we
41:36
Speaker 3: haven't talked about this, but I think smaller companies increasingly
41:39
Speaker 3: can go all the way themselves. Part of that reason
41:42
Speaker 3: is because the ecosystem has matured more so the idea
41:45
Speaker 3: of building up your own sales infrastructure and your own
41:47
Speaker 3: salesforce has become less scary than it has in the past,
41:51
Speaker 3: and sadly, because the number of countries outside of the
41:55
Speaker 3: US willing to pay for innovation has declined, especially Europe,
41:59
Speaker 3: and the focus has increasingly become the United States. More
42:03
Speaker 3: companies are able to do that because you're only addressing
42:06
Speaker 3: the States, so it will accrue to companies of all kinds.
42:10
Speaker 3: Now to the question of sustainability and affordability, I'd just
42:13
Speaker 3: like to make this point, which is because our industry
42:17
Speaker 3: is the only one right where you have automatic generic
42:20
Speaker 3: substitution after a patent expires. The result of those the
42:24
Speaker 3: balance of those things right, high drug prices for a
42:27
Speaker 3: fixed period of time, and then you know, revenue plummet
42:30
Speaker 3: to zero. Is actually that the amount the average American
42:35
Speaker 3: spends on drugs has as a percentage of the total
42:38
Speaker 3: cost spent in healthcare, has been declining recently in the
42:41
Speaker 3: last few years, and most people aren't aware of that.
42:43
Speaker 3: So it's back down to single digit percent of total
42:46
Speaker 3: health care spending in the US. I think somewhere between
42:49
Speaker 3: nine and ten percent, and it translates to roughly one
42:51
Speaker 3: hundred dollars a month. And I think if you talk
42:53
Speaker 3: to most Americans and you said, just from an abstract perspective,
42:57
Speaker 3: if you had to spend one hundred dollars a month
42:59
Speaker 3: and you we got access, just like Netflix, to all
43:02
Speaker 3: branded medicines, which is ten percent of medicines now and
43:05
Speaker 3: in the future, and the ninety percent of America of
43:08
Speaker 3: medicines that are generic. Would you think that's a good deal?
43:11
Speaker 3: Most Americans, I think would say, I think that's that's
43:13
Speaker 3: a very fair reasonable deal. That's probably what I pay
43:15
Speaker 3: for my iPhone or whatever other technology that they really
43:19
Speaker 3: value in their lives. We do know, you know, that's abstract.
43:22
Speaker 3: There are issues that we don't have to get into.
43:24
Speaker 3: But like you know, there's copay issues. So there's a
43:27
Speaker 3: percentage of Americans paying for those branded medicines that who
43:30
Speaker 3: need them, who are paying thousands or tens of thousands
43:33
Speaker 3: of dollars per month because insurance isn't you know, fully
43:37
Speaker 3: covering it when you need it. Now, that's a separate
43:39
Speaker 3: issue that we live within the real world. But I
43:42
Speaker 3: think the main sustainability question in the US is actually,
43:46
Speaker 3: you know, our services and hospital costs. They have been
43:49
Speaker 3: it's one of the fastest growing above inflation categories in
43:53
Speaker 3: the US. There are structural reasons for this, right There's
43:56
Speaker 3: been a wave of consolidation and services in the States,
43:59
Speaker 3: there's not price trans parentcy that nothing ever goes generic,
44:02
Speaker 3: and so there's real issues that we're going to have
44:04
Speaker 3: to tackle as as a country with services inflation that's
44:08
Speaker 3: going to make a bigger difference on sustainability than drugs
44:11
Speaker 3: ever will. So my viewpoint is that you know, drugs
44:15
Speaker 3: are actually quite sustainable separate from these cope issues, out
44:19
Speaker 3: of pocket issues, and the innovation. The value of the
44:21
Speaker 3: innovation that you're getting is terrific.
44:23
Speaker 2: Right, we haven't got very many minutes left, but in
44:25
Speaker 2: the last few that we have, I want to talk to.
44:28
Speaker 1: Ask you about RTW's if want of a better phrase,
44:31
Speaker 1: favorite segments.
44:33
Speaker 2: So I if I just set this up by saying,
44:36
Speaker 2: I think it's been a couple.
44:37
Speaker 4: Of years where everybody was going iron iron I and
44:41
Speaker 4: by the way, that means autoimmune disease mostly that's the
44:44
Speaker 4: area to be forget cancer, and this year we're seeing
44:49
Speaker 4: significant I mean amazing which had been happening in cancer
44:53
Speaker 4: all for quite a while.
44:54
Speaker 2: You got the let's say, take Vailey plus Darzalex.
44:58
Speaker 1: In multiple maloma with multimonllum as my space, So you're
45:01
Speaker 1: going to get a lot of examples of that in
45:03
Speaker 1: Majestic three trial, which got amazingly rapidly approved.
45:07
Speaker 2: By the FDA, make a huge difference to early stage
45:11
Speaker 2: multiple level patients.
45:12
Speaker 1: We've got direc soon RACIP that just came out of
45:15
Speaker 1: Revolution Medicine, doubling survival in second line pancreatic cancer. So
45:21
Speaker 1: I'm going to put this as a proper pose is oncology.
45:24
Speaker 1: I don't think oncology was had they ever gone away,
45:26
Speaker 1: because I kept seeing the deals. The deal volumes are
45:28
Speaker 1: around the fifty percent or so that they'd always been
45:32
Speaker 1: in terms of licensing deals. So but talk to us
45:35
Speaker 1: about where you think we are, and this is our
45:37
Speaker 1: last question, and where are you excited by And you
45:40
Speaker 1: could take your pick from neuroscience iron I rare diseases,
45:44
Speaker 1: specific types of as a firm going forward.
45:47
Speaker 3: Yeah, I think you nailed it. You know, I and
45:49
Speaker 3: I has been great the last several years, but cancer
45:52
Speaker 3: is back. I think this, and specifically for biottech with
45:57
Speaker 3: the poster child kind of leading the way, the flag
45:59
Speaker 3: bearer being read ned. But I think this asco you know,
46:02
Speaker 3: we're starting to make our plans now for the conference
46:04
Speaker 3: you know, about a month away and I think this
46:06
Speaker 3: is going to be the most eventful bio asco for
46:08
Speaker 3: biotech in a while. Of course, all the pancreatic data,
46:12
Speaker 3: but also you're going to see some second line breast
46:14
Speaker 3: cancer data, hopefully from cell acuity. You're going to see
46:17
Speaker 3: bladder cancer data possibly from CG oncology as an example.
46:22
Speaker 3: So cancer is back and specifically for biotech in a
46:25
Speaker 3: big way. You mentioned another one, psych or neuropsych. I
46:29
Speaker 3: think psychedelics are are a huge deal. I'm excited that
46:33
Speaker 3: the first product will hopefully get to market, you know,
46:35
Speaker 3: before the end of this year. And you know, the
46:37
Speaker 3: applicability across some high endmet need diseases is really high.
46:42
Speaker 1: Right.
46:42
Speaker 3: It's not just treatment resistant depression, which is the first indication.
46:46
Speaker 3: It's things like PTSD, serious anxiety disorders, potentially severe addiction
46:51
Speaker 3: disorders also. So I think that's just going. It's part
46:55
Speaker 3: of this broader theme of a resurgence and innovation in
46:59
Speaker 3: neuropsych in general. I and I still going. I think
47:02
Speaker 3: the shift there's been a bit of a shift not
47:04
Speaker 3: just to first in class targets, but now also the
47:07
Speaker 3: combination of some of those targets, especially in tough diseases
47:10
Speaker 3: like inflammatory Biel diseases right where no single drug, even
47:14
Speaker 3: the best new ones, can get more than a quarter
47:16
Speaker 3: of patients in a complete remission. So still tons of
47:20
Speaker 3: innovation and need left in immunology. And then rare we
47:24
Speaker 3: didn't touch on, but you know, rare disease. Yes, there
47:27
Speaker 3: are issues at FDA, but that's for I would say,
47:30
Speaker 3: you know, I don't know, call it the twenty percent
47:32
Speaker 3: programs that are on the margin right where there's a
47:36
Speaker 3: lot of debate, but there's eighty percent where the results
47:39
Speaker 3: are terrific. Whether you're flexible or not at FDA, those
47:43
Speaker 3: drugs are going to succeed, and rare just continues. You
47:47
Speaker 3: just continue to have a steady cadence of innovation there,
47:50
Speaker 3: which is which is terrific.
47:51
Speaker 1: Well, so science is doing amazing stuff, you know. I
47:55
Speaker 1: mean when we think about how direction and recive actually works,
47:58
Speaker 1: the way that was the marriage of two ideas together,
48:02
Speaker 1: I think it's super exciting. It's just so cool right now.
48:07
Speaker 1: Lots of other companies trying to target to with good
48:10
Speaker 1: data coming. Oh that we've seen some early data there.
48:13
Speaker 1: So rod One, thank you for your time. Really wonderful
48:17
Speaker 1: to catch up with you. It's been a long time
48:19
Speaker 1: that I wanted to do this, so it's great. So
48:21
Speaker 1: hopefully we can catch up whenever the time is right
48:24
Speaker 1: to have a refresh of how these ideas have evolved
48:27
Speaker 1: and how the world around us has evolved.
48:30
Speaker 2: So thank you for your time.
48:31
Speaker 3: Thank you.
48:32
Speaker 1: So this is Sam Fazelli from Lumberg Intelligence and the
48:35
Speaker 1: Vanguards of Healthcare podcast and please join us on the
48:39
Speaker 1: next one and you can listen to all the back
48:41
Speaker 1: episodes on Spotify or Apple podcasts, and of course on
48:45
Speaker 1: the termine we can find a link to all our
48:46
Speaker 1: podcasts which go way beyond.
48:48
Speaker 2: Healthcare, et cetera. So thank you very much for joining.
49:25
Speaker 1: Uses as basis Uses
49:37
Speaker 4: Bases