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Xontogeny's Case for Drug Developers Over Storytellers · Vanguards of Healthcare by Bloomberg Intelligence

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Speaker 1: Welcome to another episode of Vangas of Healthcare, the Bloomberg
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Speaker 1: Intelligence podcast, where we speak to leaders and top experts
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Speaker 1: within the pharmaceutical healthcare industry. My name is Sam Fazzili
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Speaker 1: and one of the senior pharmaceutical analysts at Bloomberg Intelligence.
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Speaker 1: Bloomberg Intelligence is the research arm of one of the
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Speaker 1: research arms of Bloomberg, with about five hundred folks in it,
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Speaker 1: and the Healthcare team rounds up to around fifty people,
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Speaker 1: and we are proud to say that we cover pretty
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Speaker 1: much the waterfront of healthcare from therapeutics to medical devices, diagnostics,
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Speaker 1: et cetera, with a very strong bench of analysts our research,
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Speaker 1: which of course can be found on the Bloomberg Intelligence
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Speaker 1: b I go. And today I have the pleasure of
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Speaker 1: hosting Chris Garabedian, someone with whom I've spoken a lot,
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Speaker 1: mostly remotely through the Biotech Hangout, where we have an
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Speaker 1: opportunity sometimes to overlap in terms of the conversations we have.
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Speaker 1: And of course Chris has got a very i would
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Speaker 1: say interesting and varied history background within the sector, touch
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Speaker 1: having touched several aspects of biotech and drug development, and
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Speaker 1: I think has some very in my view, will have
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Speaker 1: very unique platform or position from which to look at
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Speaker 1: the world of drug development, and of course outside of
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Speaker 1: drug development, in the business that is running today, which
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Speaker 1: is ontogeny, part of perceptive or related to perceptive, you'll
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Speaker 1: explain all that has a very interesting platform from which
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Speaker 1: to look at companies, and of course in there there
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Speaker 1: are some non therapeutic type companies which I think it
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Speaker 1: would be interesting to touch on. So, Chris, welcome to
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Speaker 1: the conversation.
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Speaker 2: Yeah, thanks, Sam, great to be here and thanks for
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Speaker 2: having me.
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Speaker 1: Well, it's a pleasure. So I thought, as usual, I
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Speaker 1: would start with you telling us a little bit about yourself,
2:08
Speaker 1: on your background and how you went from whenever you
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Speaker 1: started in this business to where you are today.
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Speaker 2: Yeah, I'll go through it pretty rapid fire. But I
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Speaker 2: have over thirty five years in the biopharma sector. The
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Speaker 2: first twenty five years of that I spent as an operator.
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Speaker 2: I started consulting. I went to ab the working with
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Speaker 2: R and D teams on new product development and figuring out,
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Speaker 2: you know, how to advance pipeline products. I did some
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Speaker 2: brand management while I was at ABVI. Then I went
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Speaker 2: to Gilead. In the earlier days, they were less than
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Speaker 2: half a billion market cap when I joined them eight
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Speaker 2: years later they were more than a twenty five billion
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Speaker 2: dollar market cap. So that was a great experience leading
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Speaker 2: medical affairs, commercial development, business development, you know, corporate strategy,
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Speaker 2: et cetera for Gilliad. Then I went to Celgene as
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Speaker 2: head of corporate Strategy, also reporting to the C suite,
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Speaker 2: where again really helping them prioritize their pipeline, do some
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Speaker 2: investments of M and A larger transformational deals, and then
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Speaker 2: help with project management project leadership as well. There From there,
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Speaker 2: I joined the board of a company called Avii and
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Speaker 2: quickly became the CEO, which I renamed Surrepta and refocused
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Speaker 2: that company on dschen muscular dystrophy. That was joined the
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Speaker 2: board in twenty ten, took over a CEO on January first,
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Speaker 2: twenty eleven. I left in twenty fifteen and moved to
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Speaker 2: the investing side where I oversee a venture studio called
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Speaker 2: Zontogeny that I founded that does seed and precede investments
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Speaker 2: usually with first time CEOs and scientific founders. And then
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Speaker 2: I joined Perceptive, who was an investor in that venture studio,
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Speaker 2: to lead their first ever venture funds. Their branded Perceptive
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Speaker 2: zontogyny ventures. Those are under the perceptive umbrella. We've raised
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Speaker 2: seven hundred million plus of AUMs. We've made over forty
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Speaker 2: investments across life sciences, mostly in therapeutics, but like you mentioned,
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Speaker 2: some in the non therapeutic space, device diagnostics, tools and
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Speaker 2: services CDMO, CROs, etc. So that's what I do. I
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Speaker 2: set a lot of boards and you have been excited
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Speaker 2: to get to know you better through the biotech hangout.
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Speaker 1: That's very kind of you, Chris. So when you go
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Speaker 1: through that list, Gilliad obvious success, today, cell Gene obvious
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Speaker 1: success which was then sold to Bristol Myers Surrepta another success.
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Speaker 1: So you've got a pretty good pedigree here. Is there
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Speaker 1: some kind of magic touch there? Chris? Now?
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Speaker 2: You know? I, you know, I really make a point
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Speaker 2: to differentiate between lab research that you might pursue a
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Speaker 2: PhD to use in academia or to drive great research papers,
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Speaker 2: or an MD that goes to medical school might consider
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Speaker 2: clinical practice, but really is the practice of medicine. I
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Speaker 2: draw a distinction between a PhD and an MD who
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Speaker 2: embraces quote the science versus a drug developer, which is
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Speaker 2: not taught in medical school. It's not taught when you
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Speaker 2: pursue your PhD. It's not taught when you're a you know,
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Speaker 2: get your bachelor's in biology, right, So that is an
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Speaker 2: industry gained experience, and I was fortunate to have worked
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Speaker 2: for companies and teams that did it better than the
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Speaker 2: average biotech So it started when I was at Abbot
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Speaker 2: where I really wanted to understand what drove success in
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Speaker 2: the marketplace. And at the end of the day, it
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Speaker 2: really was driven on what got in your package insert
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Speaker 2: What got in your package insurt was usually what was
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Speaker 2: the clinical study you did, the pivotal studies that were
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Speaker 2: often published in the New England Journal Medicine or other
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Speaker 2: peer reviewed publications, and I started reading those to understand
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Speaker 2: how they designed those studies, what were the endpoints that
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Speaker 2: drove the success, what ended up in their label, what
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Speaker 2: ultimately led to blockbuster drugs was again the discipline of
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Speaker 2: drug developer development. So I consider myself a drug developer
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Speaker 2: first and an investor second. And I don't like when
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Speaker 2: I hear people in industry describe, well, there's science and
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Speaker 2: there's business, or there's research and development and then there's commercial.
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Speaker 2: I think that misses a huge chasm of what we
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Speaker 2: really need to focus on, which is the art and
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Speaker 2: practice and best practice of drug development. I hope that
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Speaker 2: makes sense.
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Speaker 1: It does, it does, it's and it actually it's put
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Speaker 1: really succinctly and nicely in the in what you just said,
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Speaker 1: because I think there's a there's a lot of people
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Speaker 1: who think that FARMA companies or young biotech companies are
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Speaker 1: automatically all equally risky, which of course is potentially the case.
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Speaker 1: But it just talks again to to the critical value
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Speaker 1: that management brings to these things, which I'm sure is
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Speaker 1: a major part of your discussion and your around the
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Speaker 1: investment committee when you look at the incoming companies. Yeah.
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Speaker 2: Well, just to add a finer point on that, Sam,
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Speaker 2: I think you know a lot of people are like, well, Chris,
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Speaker 2: how did you raise the first time venture fund when
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Speaker 2: you've never done it before. I didn't try to be
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Speaker 2: a venture capitalist. When I spoke to our LPs. I
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Speaker 2: try to say, look, I know drug development. I know
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Speaker 2: if I have a track record of deploying capital wisely
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Speaker 2: and generating value in operating companies, the due diligence process
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Speaker 2: is not that different from doing business development M and
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Speaker 2: a right for a biopharma company. Right, you're looking at
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Speaker 2: and looking at the same criteria, maybe for a different end,
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Speaker 2: right to boost earnings or to fill a pipeline gap,
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Speaker 2: et cetera. But basically the LPs really responded to that.
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Speaker 2: As a drug developer first, who could understand how to
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Speaker 2: do due diligence and make good strategic investments for their
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Speaker 2: with their money to generate good returns.
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Speaker 1: But why VC, I mean, you could have pretty much
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Speaker 1: surely had to pick up any type of next move.
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Speaker 1: Why why go into the investing world as opposed to
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Speaker 1: continueing the I don't want to draw too much of
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Speaker 1: a line there, but into an operating world.
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Speaker 2: Yeah, well, look, you know, every personality is different. And
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Speaker 2: while I felt that I could do the overseeing a
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Speaker 2: CEO role and being a CEO of a public company, well,
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Speaker 2: I didn't enjoy many aspects of it. I would argue
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Speaker 2: that more than half of your time as a public
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Speaker 2: company CEO is devoted to things that are not drug development,
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Speaker 2: which is what I love, right and loving to figure
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Speaker 2: it out and get it right. Right, You're you're dealing
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Speaker 2: with governance issues, preparing for the next board meeting, and materials.
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Speaker 2: You're you know, you've got SEC filings, You've got to
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Speaker 2: review that and sign off on SEC files. You're dealing
8:30
Speaker 2: with investor calls constantly, right a CEO. The stock moved
8:34
Speaker 2: eight percent today because somebody posted something on Twitter and
8:37
Speaker 2: you're fielding calls all day when it had nothing to
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Speaker 2: do with what was happening. So certain, Yeah, and that
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Speaker 2: was really part of it, and just dealing with HR issues.
8:46
Speaker 2: When you have a big company, you know, there's a
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Speaker 2: lot of things that are not related to executing on
8:52
Speaker 2: the program, but dealing with a lot of things and
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Speaker 2: the other piece of it is very binary. When you're CEO,
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Speaker 2: you live and die by that. You can do very well,
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Speaker 2: and some days I think it would have been easier
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Speaker 2: to make money right being a CEO, But in reality,
9:06
Speaker 2: I was at a point in my career where I
9:07
Speaker 2: wanted to be involved in more than one thing and
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Speaker 2: that the investing side allowed me to sit on boards
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Speaker 2: and to influence even companies that I'm not on the
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Speaker 2: board of, but I'm portfolio manager of that investment. I
9:20
Speaker 2: can influence that for somebody who might be representing the
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Speaker 2: board role for us, or if we don't have any
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Speaker 2: board rep presence, we can still meet with management and
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Speaker 2: tell them our view. So for me, it was the
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Speaker 2: excitement of getting involved in the most important parts that
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Speaker 2: I enjoyed across a portfolio of companies. Now I can
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Speaker 2: also tell you that it's not just being on the
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Speaker 2: investing side. I could not do public equity investing like
9:45
Speaker 2: my colleagues at Perceptive do so well. It's a different beast, right,
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Speaker 2: That's a very different animal, dealing with volumes of public information,
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Speaker 2: psychology of public investing, figuring out the valuation, are you
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Speaker 2: oversold or overbought? You know, what's going to happen with
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Speaker 2: a catalyst event. That's much much harder, in my opinion
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Speaker 2: than just doing good drug development early and creating value
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Speaker 2: with a positive clinical data set.
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Speaker 1: But Chris has an AI solved all of the things
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Speaker 1: for you. I mean, they don't have to do any
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Speaker 1: work at all anymore. They can get AI to analyze
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Speaker 1: all the data.
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Speaker 2: And I'll be facetious, yeah, I mean I know, but
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Speaker 2: I think that there is some truth to that, which is,
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Speaker 2: first of all, you know, we've been in a workforce
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Speaker 2: where okay, and I'm generalizing here, but usually the first
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Speaker 2: half of your career you're getting overpaid and you're learning
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Speaker 2: from the companies and organizations you work for, right, In
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Speaker 2: other words, you're getting more out of them than they're
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Speaker 2: getting out of you. And then in the second half
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Speaker 2: of your career, you're you're carrying a lot of the water, right,
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Speaker 2: You're pulling a lot of weight, and you're leading teams
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Speaker 2: and you're getting people exposure to best practices and all that.
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Speaker 2: And so AI I think is an alternative and an
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Speaker 2: awe augmentation of that junior associate that you might bring
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Speaker 2: in because you need them to do a task. I
11:07
Speaker 2: need you to work on this project because I don't
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Speaker 2: have time or the bandwidth to go deep into this
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Speaker 2: new technology area.
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Speaker 1: Right.
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Speaker 2: Well, now you can bypass that. And then the question is, well,
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Speaker 2: do you need to hire that junior person to just
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Speaker 2: navigate the AI tools right to gather that information? And
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Speaker 2: that's hotly debated. Right. Some of them are more savvy,
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Speaker 2: they're understanding prompts better, but there's also people that are
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Speaker 2: our peers that are doing that quite well. The other
11:34
Speaker 2: piece of it is is that we've always heard the
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Speaker 2: old adage, right, and I think it was a Derek
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Speaker 2: Lowe who quoted it for chemists, right, it's not that
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Speaker 2: computers are going to replace chemists, but chemists with computers
11:46
Speaker 2: are going to replace chemists who don't use computers. And
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Speaker 2: so I think as it relates to AI, I think
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Speaker 2: I see some of the smartest people in our industry,
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Speaker 2: the ones that you wouldn't think wouldn't embrace he said,
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Speaker 2: don't need it, right, they're they're they're you know, they're
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Speaker 2: on the far end of the curve on intelligence. You know,
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Speaker 2: these are the people who are embracing it and are
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Speaker 2: using it to even enhance further their understanding. So, uh,
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Speaker 2: it may be validating, right if you have a question
12:14
Speaker 2: around a due diligence question, it may find a blind
12:17
Speaker 2: spot that you hadn't thought about that you want to
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Speaker 2: dig deeper on. So I think it really is a
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Speaker 2: tool that those of us who've been in history for
12:24
Speaker 2: decades understand how to use those tools. I think a
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Speaker 2: little bit better than the newbie who's just doesn't have
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Speaker 2: that experience and is just trying to prompt it their
12:33
Speaker 2: way to the right answer.
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Speaker 1: Yeah, they don't know what they don't know, sure, but
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Speaker 1: as we do know what, we don't know exactly. So, Chris,
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Speaker 1: I will get back to this in a minute. But
12:43
Speaker 1: let's talk about sometogeny, preceptives and sergeny, et cetera. What
12:47
Speaker 1: is the what's the story about what are you looking for?
12:50
Speaker 1: I mean, one way of telling what you're looking for
12:53
Speaker 1: is looking at the companies you've invested in, And I
12:55
Speaker 1: think I can get a good sense of what are
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Speaker 1: you looking for, which is it's not a therapeutic area,
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Speaker 1: it's not a type of disease. It's what comes through
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Speaker 1: the door that looks exciting and interesting. So, yeah, I
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Speaker 1: didn't want to answer the question for you. Yeah, let
13:07
Speaker 1: me bounce that back to you. So how does that work?
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Speaker 1: Who should bother picking up the phone to Chris and team? Yeah, well,
13:14
Speaker 1: you know, I brand new idea.
13:15
Speaker 2: Yeah, there's there's there's two answers to that, maybe two
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Speaker 2: and a half. But but first is the venture studio. Right,
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Speaker 2: So I founded the venture studio because what I saw
13:24
Speaker 2: over you know, forty years of the industry. Now it's
13:27
Speaker 2: forty five years of the industry if you if you
13:30
Speaker 2: peg it to nineteen eighty as the birth of biotech
13:32
Speaker 2: with gen Entech's IPO. Let's say, one thing that has
13:36
Speaker 2: been true, regardless of the macro market environment is that
13:40
Speaker 2: if you can take a pre clinical compound and move
13:44
Speaker 2: it to a clinical proof of concept data set that
13:47
Speaker 2: is positive and beyond reproach a well designed study, nothing
13:51
Speaker 2: beats that return on investment. Right. You go from you know,
13:55
Speaker 2: tens of millions of value to hundreds of millions, if
13:58
Speaker 2: not billions of value with that journey from pre clinical asset,
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Speaker 2: development candidate to clinical proof of concept. And what I
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Speaker 2: saw when I was at Gilead and cell Gene and
14:07
Speaker 2: meeting with all of these early stage biotechs, they would
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Speaker 2: often make some early mistakes that you couldn't really recover from.
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Speaker 2: And so what I wanted to do was get involved
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Speaker 2: early before those mistakes were made to be able to
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Speaker 2: pick the best technologies and advance those companies through that
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Speaker 2: clinical proof of concept. Now, at the seed stage and
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Speaker 2: the venture studio, we're mostly interested in getting to a
14:30
Speaker 2: development candidate. If we have a development candidate, we want
14:33
Speaker 2: to get that or the precursor to the development candidate
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Speaker 2: to a well characterized pre clinical data set. Right. So
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Speaker 2: this may be you know, some patients sell line data,
14:44
Speaker 2: some rodent models, maybe a larger species model, maybe some PKPD,
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Speaker 2: maybe some talk screening. Maybe we have a pre id
14:52
Speaker 2: meeting with the FDA, but we're trying to get this
14:54
Speaker 2: ready for moving to a Series A investment that is
14:59
Speaker 2: ready to bring it into the clinic. Oftentimes you need
15:02
Speaker 2: to do a healthy volunteer sad MAD first before you
15:04
Speaker 2: go into patients. In some disease areas like cancer, like
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Speaker 2: rare disease, you can go right into patients. But the
15:10
Speaker 2: idea is that is what we're trying to do with
15:12
Speaker 2: the seed stage is pick the best pre clinical assets
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Speaker 2: that don't usually have a lot of data, better characterizing those,
15:19
Speaker 2: better de risking them, and getting them prepared for a
15:23
Speaker 2: Series A to bring them through I ind enabling work
15:26
Speaker 2: into the clinic. On the venture side, we started as
15:29
Speaker 2: a almost solely Series A fund, but because of the
15:33
Speaker 2: market downturn and the crossover hedge fund that Perceptive Manages,
15:38
Speaker 2: which was doing a lot of crossovers. I would argue
15:40
Speaker 2: they were in the top three of the most kind
15:42
Speaker 2: of crossover investments taking companies IPO during that you know,
15:46
Speaker 2: two thousand and fourteen to twenty twenty one phase, they
15:50
Speaker 2: really curtailed a lot of their earlier private investments that
15:54
Speaker 2: were beyond the Series A and so we started to
15:57
Speaker 2: pick up more of that opportunistic investment. So you'll see
16:01
Speaker 2: we did some more Series B, Series C, We've even
16:04
Speaker 2: done Series D rounds. We still like our core, which
16:08
Speaker 2: is a larger position size with a Series A where
16:11
Speaker 2: we can take a board seat and play a more
16:13
Speaker 2: active role. We do like to lead or co lead.
16:15
Speaker 2: But you're right exactly. Your observation is that we're agnostic
16:19
Speaker 2: to therapeutic category, agnostic to modality. We are what I
16:23
Speaker 2: would say bottoms up investors as opposed to top down.
16:27
Speaker 2: We don't quickly embrace new technologies that are not validated,
16:31
Speaker 2: like a lot of firms like Arch and Flagship and
16:34
Speaker 2: others that you know a sixteen Z on the tech bioside,
16:38
Speaker 2: where they're willing to take on a lot of that
16:40
Speaker 2: early risk with new technologies. The only we have done
16:43
Speaker 2: device and diagnostics and tools and services out of the
16:45
Speaker 2: venture pond. I would say it's harder to get there
16:48
Speaker 2: on the seed strategy because it's harder to add value
16:52
Speaker 2: with a million to three million dollars in a seed
16:54
Speaker 2: I'm getting averages here and really d risk and create
16:58
Speaker 2: value if it's not in the drug space, and the
17:00
Speaker 2: drug space, you can do that it's harder to do
17:03
Speaker 2: that in the device or diagnostic or tools and service
17:06
Speaker 2: to space with a small kind of smaller seed investment.
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Speaker 1: That's interesting. Do you want to just drill down into that.
17:12
Speaker 1: Why that's the case, because one would have thought that devices, diagnostics,
17:17
Speaker 1: proof of concept or proof of yeah, first value should
17:23
Speaker 1: be easier. Yeah, that sounded that sounds a little counterintuitive
17:27
Speaker 1: to me.
17:27
Speaker 2: Well, you know, yeah, I'm glad you asked that question,
17:30
Speaker 2: because here's the thing. So I we draw the distinction
17:33
Speaker 2: between what I would call a five to ten K
17:36
Speaker 2: device and a device that you need to do the
17:39
Speaker 2: clinical studies, you need to pursue a PMA that's going
17:42
Speaker 2: to come with label claims, and that's going to allow
17:45
Speaker 2: you to really move the standard of care in a
17:48
Speaker 2: different direction with your technology. Right. That rarely, if ever
17:52
Speaker 2: happens with a five to ten K device strategy. So
17:55
Speaker 2: what you're really when you when you talk to a
17:58
Speaker 2: device startup, you know, if they're pursuing a five to
18:01
Speaker 2: ten K it's all about commercial strategy. It's all about
18:04
Speaker 2: how we can market this. We were proven safe, we
18:06
Speaker 2: can start selling it tomorrow. Okay, Well, that's not where
18:09
Speaker 2: the value inflection starts, how many accounts are using it?
18:13
Speaker 2: What's your you know, month over month revenue increase? Right,
18:16
Speaker 2: what's going to be your peak sales? I mean, and
18:19
Speaker 2: you know you might be able to move the needle
18:21
Speaker 2: if you're investing you know at a you know, a
18:24
Speaker 2: few hundred thousand pre money, and you might want to
18:27
Speaker 2: try to sell the company for a million. That's a
18:29
Speaker 2: different scale than what we work at. But for a PMA. Increasingly,
18:34
Speaker 2: the the medtech buyers will usually not step in until
18:39
Speaker 2: you clearly have a large clinical data set, until you
18:43
Speaker 2: potentially might even have the FDA approval, they might not
18:46
Speaker 2: acquire it even then. They usually have a cap of
18:49
Speaker 2: about a half a billion of their takeouts. If you
18:52
Speaker 2: want to get to that really high takeout that a
18:54
Speaker 2: drug can provide, right billions, then you really need to commercialize,
18:58
Speaker 2: probably go ipo. That is a huge and long journey
19:02
Speaker 2: of raising capital. So that's what I mean. It's really
19:06
Speaker 2: hard to add a lot like outsized you know, exponential value.
19:11
Speaker 2: In device diagnostics, you can usually do an early pilot
19:15
Speaker 2: study and hey, it looks like we may have best
19:17
Speaker 2: in class sensitivity or specificity. Well, now we have to
19:20
Speaker 2: reproduce that in a larger set and make sure we
19:23
Speaker 2: can be standard, and that requires more capital. You're not
19:26
Speaker 2: going to get there on a seed stage, right, So
19:29
Speaker 2: that's where the investors who are coming in in the
19:31
Speaker 2: next round don't give you a lot of credit. But
19:34
Speaker 2: if you take an early lead of a drug and
19:40
Speaker 2: you turn that into development candidate and well characterize that,
19:43
Speaker 2: you can move a company with a few million dollars
19:46
Speaker 2: to a twenty million pre money okay, pretty easily. If
19:50
Speaker 2: you're ready to go into the clinic and do a
19:53
Speaker 2: you know, sad mad and a clinical proof of concept,
19:55
Speaker 2: many investors will write a fifty million dollar, eighty million
19:58
Speaker 2: dollars one hundred and fifty million dollar round, right, a
20:01
Speaker 2: check for that size round to get it to that,
20:03
Speaker 2: you know, hundreds of millions or billion dollar valuations for that.
20:07
Speaker 2: So that's why we differentiate for mostly focusing on drug
20:11
Speaker 2: in the seed stage.
20:12
Speaker 1: Do you think this is partly the explanation for why
20:15
Speaker 1: there are so many more biotech companies then there are
20:18
Speaker 1: startup medical device diagnostics? Yeah.
20:21
Speaker 2: I also think it's been more institutionalized. In my opinion,
20:25
Speaker 2: I think if you talk to most biotech investors, they
20:28
Speaker 2: could reasonably come up with a top thirty you know,
20:31
Speaker 2: pure play or you know, clearly focused on biotech VC
20:35
Speaker 2: and the series A, series B rounds. Right, it's hard
20:38
Speaker 2: to do that in right, devices or medtech. Some of
20:41
Speaker 2: them only focus on devices, Some don't want devices at
20:45
Speaker 2: all and we'll do diagnostics. Some are more leaned toward
20:47
Speaker 2: tools and services. So you have a little bit more
20:50
Speaker 2: of a you know, you know, a smorgas board of
20:54
Speaker 2: investors in the non drug space. And then Silicon Valley
20:59
Speaker 2: has come into kind of even overwhelmed that further. You've
21:02
Speaker 2: got some big players like A six and Z, but
21:05
Speaker 2: you know, the tech bio, the AI application for health tech,
21:09
Speaker 2: you know, all of that, they're putting more money in,
21:11
Speaker 2: and it dwarfs in many cases, right, what's going into
21:14
Speaker 2: too biotech? So I think it depends and it varies,
21:17
Speaker 2: but I think the pure play biotech drug investors are
21:22
Speaker 2: pretty clear to find, both at the seed, both at
21:24
Speaker 2: the venture capital play and also at the crossover and
21:29
Speaker 2: public equity. Those lists are not you know, you know,
21:32
Speaker 2: extremely long to come up with the top twenty top
21:35
Speaker 2: thirty investors.
21:36
Speaker 1: Okay, so again, so two topics have been going to
21:39
Speaker 1: come back to his AI and also the the you know,
21:42
Speaker 1: I'm going to press you for some of your favorite companies,
21:44
Speaker 1: which of course is very hard. Yeah, answer, et cetera.
21:47
Speaker 1: But everybody does that. This is onto Jenny. Going back
21:50
Speaker 1: to SYRUP Today's what are the when you sit with
21:53
Speaker 1: companies that come through the door. I don't know, you're
21:56
Speaker 1: not involved in SYRUP to anymore, aside from saying to
22:02
Speaker 1: them that it wouldn't be a CEO if I were you,
22:04
Speaker 1: But you know, I guess you're not going to say that. Yeah,
22:07
Speaker 1: But aside from that, what are the key learnings from
22:10
Speaker 1: the surrept todays that you think are particularly relevant as
22:15
Speaker 1: you look at the stories that come through the door,
22:17
Speaker 1: and I'm assuming there's some active involvement with some of
22:20
Speaker 1: the companies you're invested in, at least directly by yourself
22:22
Speaker 1: or by your team members. What are the key things
22:24
Speaker 1: that you learned specifically from there? Because if we just
22:27
Speaker 1: described describe surrepta, it was an ultra orphan disease, at
22:33
Speaker 1: least that it still is. I suppose is it ultra
22:36
Speaker 1: orphan or just O I don't know whatever. Yeah, Well,
22:38
Speaker 1: if you look at therapy, et cetera, et cetera, Yeah, exactly,
22:41
Speaker 1: what did you learn.
22:42
Speaker 2: Yes, So, for first, I want to clarify, I think
22:44
Speaker 2: it's a lot of fun to be a CEO. I
22:45
Speaker 2: think there's a lot of people that love doing it.
22:47
Speaker 2: They love going to the investment banking conferences and being
22:49
Speaker 2: at the podium and delivering and and you know, I
22:52
Speaker 2: enjoyed many aspects of it. But for me, I enjoyed
22:55
Speaker 2: the drug development side and being involved in that far
22:58
Speaker 2: more than being a CEO. So I want to throw
23:00
Speaker 2: any shade on the CEOs that are out there so
23:02
Speaker 2: you need them, yeah, exactly, but here here were the
23:05
Speaker 2: big learning So first of all, we were so first,
23:08
Speaker 2: I would say, Serepta's gone through many lives. And while
23:10
Speaker 2: there are definitely common threads and themes that run through
23:15
Speaker 2: the various CEOs that came after me, and you know
23:19
Speaker 2: the different you know, trials and tribulations that the company received,
23:23
Speaker 2: definitely some threads. There were some differences in terms of
23:25
Speaker 2: how I operated in the early days at Syreptain. I
23:28
Speaker 2: think one of the things for me is we were
23:29
Speaker 2: really on the cutting edge of understanding this disease dcend
23:35
Speaker 2: muscular distrophe, understanding the role of distrophin the biomarker understanding
23:40
Speaker 2: what other implications, understanding the clinical outcomes that are most relevant.
23:44
Speaker 2: That's evolved and changed. But I had two competitors. One
23:48
Speaker 2: a direct competitor that was PERSENSA had a collaborative GSK
23:52
Speaker 2: that unfurled Biomerin ended up buying them. So Biomarn became
23:55
Speaker 2: our direct competitor. And then PTC, which was an indirect
23:59
Speaker 2: competitor but per doing Duschen and looking at distrofin and
24:02
Speaker 2: clinical outcomes in Dushen. And so the three of those
24:06
Speaker 2: companies really and then others came behind it Summit Catabasis,
24:09
Speaker 2: et cetera. That became public. But you know, we were
24:12
Speaker 2: the ones in the trenches really trying to push the FDA,
24:17
Speaker 2: and we were arguing in often cases that our our
24:20
Speaker 2: data set was better than yours, et cetera, et cetera.
24:22
Speaker 2: And patient advocacy was involved, and some took sides on
24:26
Speaker 2: those on those companies. Investors were you know, contentious and
24:31
Speaker 2: some many took sides on those companies. But here were
24:34
Speaker 2: the basic learnings is here as CEO, these were my
24:37
Speaker 2: guiding principles, right, So first when it came to patient advocacy, right,
24:42
Speaker 2: I wanted to be as transparent as possible and share
24:45
Speaker 2: as much data with everybody, so that I took fewer arrows.
24:50
Speaker 2: Now that ended up not being the case, But like
24:53
Speaker 2: I was one of the first CEOs that would put
24:55
Speaker 2: FDA language from our meeting minute documents into our press releases.
25:00
Speaker 2: So instead of saying, just trust me Chris Garabedi and
25:04
Speaker 2: a CEO to tell you what happened in the FDA meeting,
25:07
Speaker 2: let me let you decide what you think. I'm telling
25:10
Speaker 2: you how I'm interpreting the FDA minutes. You tell me
25:13
Speaker 2: how you interpret it. If it's different, that's fine, But
25:15
Speaker 2: I'm telling you why I came to the conclusion I did.
25:18
Speaker 2: So that was wonder number one radical transparency.
25:21
Speaker 1: You would you would suggest that that politics today follow
25:24
Speaker 1: that same rule. Well, I'm not saying, especially in the
25:27
Speaker 1: confusing world.
25:28
Speaker 2: Of well, yeah, I think we were under fire saying oh,
25:31
Speaker 2: I don't believe the FDA said that. So I said, okay,
25:35
Speaker 2: you don't believe the FDA, Well I'm going to give
25:37
Speaker 2: you their language. And as sponsor, we were allowed to
25:40
Speaker 2: do that. Whether the FDA liked that or not, that's debatable.
25:44
Speaker 2: But I wanted to make sure there was radical transparency.
25:46
Speaker 2: But generally, yes, I do support the idea of CRLs
25:50
Speaker 2: being you know, published with redacted information, et cetera. The
25:52
Speaker 2: second thing was the patient community. I from the beginning,
25:56
Speaker 2: I said, I will never tell you what to do,
25:59
Speaker 2: and I'm never going to tell you what not to do.
26:02
Speaker 2: You're on your own. I can't understand what it's like
26:04
Speaker 2: to be in your shoes, and so I'm just going
26:07
Speaker 2: to give you all of the information that I'm giving
26:09
Speaker 2: two investors right to the public, and you will decide
26:13
Speaker 2: what you want to do with that. Okay. But more importantly,
26:17
Speaker 2: I decided, when every many people were urging me to
26:22
Speaker 2: play chicken with the FDA, go ahead and submit the
26:25
Speaker 2: NDA and see what they do. Dare them to reject
26:29
Speaker 2: the NDA and see what fire comes from the patient community.
26:33
Speaker 2: I refused to do that. So what I said, I'm
26:36
Speaker 2: I'm going to work with the FDA. We're going to
26:39
Speaker 2: work together, and I'm not going to take a step
26:42
Speaker 2: forward until I get the clear guidance to move forward, right,
26:47
Speaker 2: And so that was the back and forth that I
26:49
Speaker 2: was dealing with with with Serepta. So, but the thing
26:52
Speaker 2: is is that you know a lot of people were
26:53
Speaker 2: saying oh, this is horrible for rare disease. If the
26:57
Speaker 2: FDA approves a teplerson, that's going to quell investment and
27:02
Speaker 2: research going into Dushen. The exact opposite happened. That set
27:07
Speaker 2: the bar, It set precedent for an approval that everybody
27:11
Speaker 2: crowded in saying I can beat that, I can do better.
27:14
Speaker 2: And you know, fast forward and we had over fifty
27:16
Speaker 2: clinical programs in Dushen. When many were saying, oh, this
27:20
Speaker 2: would be the worst thing for Dushen if e teplerson
27:24
Speaker 2: was rejected, was approved. And so you know, I again,
27:28
Speaker 2: we we like to say those of us involved in
27:30
Speaker 2: those early days, we we ran through the wall. We
27:33
Speaker 2: got a little bruised and battled, you know, battered, but
27:37
Speaker 2: we opened up the pathway for many other companies to
27:41
Speaker 2: pursue a similar and look sir, to remain controversy with
27:44
Speaker 2: FDA decisions, with infighting among the FDA, you know, with
27:48
Speaker 2: the gene therapy and safety you know, risk benefit. But yeah,
27:51
Speaker 2: those were the main learnings that I would recommend to
27:54
Speaker 2: any CEO that was trying to navigate, you know, especially
27:58
Speaker 2: a controversial rare disease like tush.
28:01
Speaker 1: Now, so just while we're on the FDA subject, all
28:03
Speaker 1: the public informations out there in Aprissard came in. Some
28:07
Speaker 1: of us were worried, others were not worried. Then he
28:12
Speaker 1: made some decisions, then he left, then he came back.
28:16
Speaker 1: Some of us were worried, some of us were not worried.
28:18
Speaker 1: And now his sabbatical is over and somebody else will
28:23
Speaker 1: take the rein. But he speaks to you know, I
28:27
Speaker 1: don't know how quickly, and relative to tenure of other
28:32
Speaker 1: seber leads, how often this has happened before. But if
28:37
Speaker 1: you look at the FDA today, understanding that we all
28:41
Speaker 1: have to work with them, there are many things that
28:43
Speaker 1: the FDA, at least the from Martin McCurry, McCarry is
28:47
Speaker 1: saying that are great. What are you excited by and
28:52
Speaker 1: what are you worried by when it comes to the FDA?
28:54
Speaker 2: Yeah, So, look, I maybe it's because I'm partly a
28:58
Speaker 2: contrary and I've been that way my whole career. Maybe
29:01
Speaker 2: it's partly because I have over thirty five years of
29:03
Speaker 2: industry experience and seeing these things play out, and and
29:07
Speaker 2: maybe it's because I often like to look at the
29:12
Speaker 2: media hype on either side through a different lens. But
29:16
Speaker 2: here's the thing. This administration, unlike the first Trump administration,
29:21
Speaker 2: where Scott Gottlieb, right was one of one of our
29:24
Speaker 2: own right who was leading the FDA, this time it
29:28
Speaker 2: was you know, uh RFK Junior. And Trump was elected
29:32
Speaker 2: with a reform a much more clear mandate on reform
29:36
Speaker 2: and and you know, not much short of burn it
29:39
Speaker 2: all down and restart or in some cases, as you know,
29:42
Speaker 2: many you know, agencies were questioned if they should even
29:46
Speaker 2: exist at all, right, not the FDA, but but you know,
29:49
Speaker 2: we we we came into a reform minded administration and
29:55
Speaker 2: you know, I think you know, part of that process
29:58
Speaker 2: is you can't really have ma of reform unless you
30:01
Speaker 2: have a cleaning of the house. Now, many of that
30:04
Speaker 2: was do you agree with our reform minded agenda or not?
30:08
Speaker 2: And many of them, you know, resigned in protest, and
30:10
Speaker 2: many of them felt it wasn't compatible to continue, and
30:13
Speaker 2: many the administration probably felt it wasn't compatible for them
30:16
Speaker 2: to continue. But I think we don't know what this
30:18
Speaker 2: is going to look like. I think for many years, okay,
30:21
Speaker 2: I think a lot of the folks that we came
30:24
Speaker 2: to know over the last several decades are gone. They're
30:27
Speaker 2: not coming back, right that the Janet Woodcocks, the Bob Temples,
30:30
Speaker 2: the John Jenkins, the right, you know, the Ellis Hungers, right,
30:33
Speaker 2: like you know, and so you have some people who've
30:35
Speaker 2: trained under them who might come back in leadership roles
30:39
Speaker 2: if the you know, a new administration comes in. That's democratic.
30:42
Speaker 2: But I think you're right, a lot of us are
30:45
Speaker 2: liking what we're hearing from Mcarey. And look with Viney,
30:49
Speaker 2: you know, it's really hard. I think, you know, there
30:52
Speaker 2: were a lot of people who liked what Vene was
30:54
Speaker 2: saying before Trump was re elected, right, And you know,
30:58
Speaker 2: I think there were a lot of people who were
31:00
Speaker 2: sharing them on of saying we need more rigor we
31:01
Speaker 2: need more right you know, you know, randomized, double blind
31:06
Speaker 2: placy boat controlled studies. You know, we need a higher bar.
31:08
Speaker 2: I think there was a lot of criticism of Peter
31:10
Speaker 2: Marx frankly from our industry before the new administration, except
31:14
Speaker 2: for those who just wanted the rubber stamp for every
31:16
Speaker 2: gene therapy that was out there. Right. So when I
31:19
Speaker 2: look at this in retrospect and I look at VENA,
31:21
Speaker 2: I think there was a clash of this flexibility of
31:25
Speaker 2: we want to be reform minded. We want to make
31:27
Speaker 2: it easier to get drugs approved. We want to consider
31:30
Speaker 2: a non placebook controlled strials. We only need to see
31:32
Speaker 2: one trial and Vinet's legacy of the highest rigor possible
31:37
Speaker 2: before we get a drug approved. So I'd say there
31:41
Speaker 2: was probably even a class even before Pastor of his
31:44
Speaker 2: bent on the rigor he wanted versus what the hierarchy
31:47
Speaker 2: was saying. Now, the other thing I'll say, and this
31:50
Speaker 2: is maybe unfair comparison, is it reminds me a little
31:54
Speaker 2: bit of Steve Jobs. And when I say, I unfair
31:58
Speaker 2: to Steve Jobs to make this comparison. He proved to
32:00
Speaker 2: be an incredible operator. But when he was at Apple
32:04
Speaker 2: in the first tenure, he was young, He was you know, passionate,
32:08
Speaker 2: he was tempestuous. People you know had a hard time
32:11
Speaker 2: with him as a manager, right, and he you know,
32:14
Speaker 2: got kicked out, right, And I think he came back wisened, mature,
32:21
Speaker 2: a stronger leader than I think he ever would have
32:24
Speaker 2: been had he not been chastened a little bit right
32:27
Speaker 2: by that early experience with Apple. And so I don't
32:30
Speaker 2: think Venet's going away. I hope that he learns from
32:35
Speaker 2: this and realizes there's you know, uh, that the method
32:41
Speaker 2: is important and that the ends don't justify the means,
32:44
Speaker 2: that the means in which you do things are important,
32:48
Speaker 2: and that you need to operate in the right way.
32:51
Speaker 2: And you know, whether that's team you know, consensus building,
32:54
Speaker 2: whether that's explaining it, whether making everybody feel that they're
32:57
Speaker 2: being listened to. So again I'm playing our I'm sure
33:00
Speaker 2: psychologists here, but I think it was just he wasn't
33:04
Speaker 2: the right personality for this time and these early days
33:08
Speaker 2: of the reform that the FDA was trying to execute.
33:11
Speaker 1: Now another thing, Chris, that the FDA is perhaps giving
33:16
Speaker 1: mixed signals on or maybe it's my perception that's wrong,
33:19
Speaker 1: isn't the gene therapy front. Gene therapy is often for
33:23
Speaker 1: rare diseases, But then there's all these blocks that are
33:26
Speaker 1: being put in the way of some gene therapy companies.
33:28
Speaker 1: And I know you have an investment in AAV manufacturing,
33:32
Speaker 1: so that's through Forge, And I think you might have
33:34
Speaker 1: talked about this before. Actually, how do you see the
33:37
Speaker 1: future of gene therapy? Both from your perspective of somebody
33:42
Speaker 1: who's been through I can say gene therapy right, Yeah,
33:45
Speaker 1: from a cerept perspective, et cetera. And then and then
33:48
Speaker 1: also from the FDA angle, because without their cooperation, we're
33:52
Speaker 1: never going to get things through to the market. And
33:56
Speaker 1: you the unicure whether the right or wrong, et cetera.
33:59
Speaker 1: I don't know. I have somebody who was very close
34:02
Speaker 1: to us who passed away from Huntington's. I don't think
34:05
Speaker 1: it would have been the right thing for them to do,
34:06
Speaker 1: to have their brains and their skull drilled. You also
34:09
Speaker 1: have I think there are companies around that are trying
34:12
Speaker 1: to get product into the brain without having to go
34:14
Speaker 1: through these kind of approaches, assuming they can get it
34:18
Speaker 1: to the right part of the brain, et cetera to
34:20
Speaker 1: do the job. But through took us through these two
34:23
Speaker 1: elements of actually the future of gene therapy, which of
34:25
Speaker 1: course is you know, fix the thing at the base,
34:30
Speaker 1: and then obviously the FDA regulatory aspect.
34:32
Speaker 2: Yeah, you know, this is such a like multi layered question,
34:38
Speaker 2: and I'm going to try to simplify it and deconstruct
34:41
Speaker 2: it a little bit. So the first thing I'll say
34:43
Speaker 2: is delivery has been a problem with genetic technology going
34:50
Speaker 2: back to the early oligos in the seventies. Right, we've
34:53
Speaker 2: been talking about and delivery still remains. Are you getting
34:57
Speaker 2: to engage the target, is it going to have a
34:59
Speaker 2: therapeutic what is your therapeutic window? Are you going to
35:02
Speaker 2: hit those limiting toxicities before you can have an effect
35:06
Speaker 2: on a large population of patients that would be in
35:08
Speaker 2: a clinical study. That is still one of the reasons
35:11
Speaker 2: we invested in the CDMO of Forge, which we have exited.
35:15
Speaker 2: It was acquired by a Japanese manufacturing company, Jinomoto. But
35:19
Speaker 2: the reason we invested in the service side of that
35:22
Speaker 2: is because we were looking at dozens, if not you know,
35:25
Speaker 2: hundreds of gene therapy programs and thought a lot of
35:29
Speaker 2: them didn't have good proof of concept, and we were
35:32
Speaker 2: taking undue risk in the clinic with a lot of
35:34
Speaker 2: those gene therapy products, right, And so we did well
35:38
Speaker 2: because we knew all of those programs had to manufacture
35:41
Speaker 2: drug and there was a limited supply on that. But
35:45
Speaker 2: let me talk therapeutically. So first, people look retrospectively and say, wow,
35:49
Speaker 2: Peter Marx used to say and brag about there were
35:52
Speaker 2: you know, seven hundred plus, you know, gene therapy programs
35:56
Speaker 2: in the clinic or moving to the clinic. Well, how
35:58
Speaker 2: many of those have we seen gain FD approval or
36:01
Speaker 2: get data sets that are off the charts. So I
36:03
Speaker 2: think investors look at that, They look at the lack
36:06
Speaker 2: of exits, they look at those that have failed and
36:09
Speaker 2: those go to zero. These these were generally binary companies
36:12
Speaker 2: that we may have one gene therapy program. So I
36:15
Speaker 2: think that is what created a lot of the headwinds
36:18
Speaker 2: around gene therapy. I think we also have to differentiate
36:20
Speaker 2: between RNA technology and DNA one and done gene therapy technology, right,
36:27
Speaker 2: and so there's some blurring the lines of repeat dosing
36:29
Speaker 2: on you know, based editing and you know allowing repeat
36:33
Speaker 2: dosing with different delivery modalities, et cetera. But ultimately RNA
36:38
Speaker 2: candidly is a better business model, right, I mean, Serepta's drugs,
36:42
Speaker 2: the oligos have sold more than five billion in revenues
36:46
Speaker 2: since their launches. Right, Their gene therapy is going down
36:49
Speaker 2: because you know, either they got the low hanging fruit
36:52
Speaker 2: or safety issues or limited labeling. So you know, that
36:55
Speaker 2: is something to keep in mind and why that people
36:58
Speaker 2: are less inclined to invest in gene therapy if there
37:01
Speaker 2: are ultra rare whereas they're more inclined to invest. If
37:05
Speaker 2: it's an RNA, you know, repeat dosing over a lifetime,
37:09
Speaker 2: they're more likely to embrace that. The other piece of
37:12
Speaker 2: it is the RNA technologies have advanced and evolved, you know,
37:16
Speaker 2: quite a bit, I would say, with more nuance and
37:19
Speaker 2: more optionality than gene therapy has in that same timeframe.
37:24
Speaker 2: So we have a lot of different Obviously al nylim
37:26
Speaker 2: has shown success. It took a lot of time, but
37:28
Speaker 2: we're seeing good RNA technology now. I think the agency
37:34
Speaker 2: wants to embrace these genetic technologies. Right. The proof of
37:38
Speaker 2: mechanism or plausible mechanistic approach, I think is a good
37:43
Speaker 2: move by the FDA. I think this gets conflated though,
37:47
Speaker 2: with the mr NA, right, which I know you know
37:52
Speaker 2: this well and where there are many and I'll talk
37:55
Speaker 2: to the US populace where this administration is listening to.
38:00
Speaker 2: They felt that the vaccine application of mRNA was not
38:05
Speaker 2: adequately tested over long term, right, you know, some deny
38:08
Speaker 2: that it's an actual traditional vaccine, And so I think
38:13
Speaker 2: that this got conflated with mRNA technology and maybe the
38:17
Speaker 2: agency's conservative view on mRNA as it related to vaccine
38:23
Speaker 2: application and if that encroached on therapeutic which we haven't
38:27
Speaker 2: really seen robustly right, and we know it's being pursued
38:30
Speaker 2: for cancer precision cancer vaccine. But I think, you know,
38:34
Speaker 2: ultimately I would separate mRNA vaccine from therapeutic RNA broadly
38:41
Speaker 2: based technology platforms. And I do think that there's even
38:44
Speaker 2: the ethical piece where people are more comfortable manipulating RNA
38:49
Speaker 2: than DNA right for various you know, philosophical, you know,
38:53
Speaker 2: religious reasons, et cetera, that they don't want to manipulate DNA,
38:57
Speaker 2: and so I think that also favors RNA technology. I
39:00
Speaker 2: don't think DNA technology is going away. I think it's
39:02
Speaker 2: here and you're going to have to do it like
39:05
Speaker 2: every other modality, which is proved that your risk benefit
39:09
Speaker 2: is so far ahead of the other modalities that why
39:13
Speaker 2: would anybody even consider using anything but a DNA gene
39:18
Speaker 2: therapy because nothing else comes close to that, you know,
39:21
Speaker 2: curative or near curative approach. I hope that makes sense
39:24
Speaker 2: how I broke it down, It does.
39:26
Speaker 1: It does now. That was a good way of breaking
39:27
Speaker 1: it down actually in my very old days. As you
39:31
Speaker 1: can see Chris and I can see each other on
39:32
Speaker 1: video I was next to a lab which was using
39:36
Speaker 1: John Wolfe's technology for direct DNA injection into muscle. I
39:40
Speaker 1: guess what. We were injecting mini distrip into MDX mice.
39:45
Speaker 1: So we were always doing something else, but it was
39:47
Speaker 1: the lab next door, so it was hard to get expression,
39:50
Speaker 1: but we got some expression in the muscle fibers. So, Chris,
39:53
Speaker 1: the topic of AI is relevant to everything we just
39:57
Speaker 1: talked about in terms of design of mRNA, MOLLEC, design
40:00
Speaker 1: of proteins. You do have an investment in a company
40:02
Speaker 1: a ALPHA that's into the protein interaction, protein protein interaction
40:06
Speaker 1: in general protein protein or protein drug interaction, et cetera.
40:09
Speaker 1: So if you were to talk to me with the
40:11
Speaker 1: regards to the companies that you're seeing the way they're
40:14
Speaker 1: employing AI. Of course the smaller companies probably have maybe
40:18
Speaker 1: they're a bit more scrappy, but on the other hand,
40:20
Speaker 1: they have a little less funding in terms of going
40:22
Speaker 1: and buying. As Raja said to us the other two thousand,
40:24
Speaker 1: six hundred and whatever the number was h two hundreds
40:27
Speaker 1: from in video, et cetera. If you were looking at
40:30
Speaker 1: this and thinking, Okay, I'm going to divide the trajectory
40:34
Speaker 1: the life of a drug from inception to approval into chunks. Yep,
40:40
Speaker 1: the lead nomination, discovery, lead nomination, pre clinical work, clinical work,
40:46
Speaker 1: where do you see the biggest impact and what do
40:50
Speaker 1: you think that impact would be. There are two options here, right,
40:53
Speaker 1: one is speed, the other one is cost. Of course
40:57
Speaker 1: three options. The number three is novel biology, finding things
41:01
Speaker 1: that you didn't know you didn't know.
41:03
Speaker 2: Yep, yeah, well yeah so. And again part of it
41:07
Speaker 2: is it's a putting my I'll call it consumer professional
41:12
Speaker 2: hat on versus my investor hat, okay, because I think
41:15
Speaker 2: I might have two different answers. And the reason I
41:17
Speaker 2: say that is that no one denies I think of microbiome. Okay.
41:21
Speaker 2: There were many investors who passed, and we were one
41:23
Speaker 2: of those who passed on microbiomes. No one really that
41:26
Speaker 2: I ever met, denied the idea of the microbiome having
41:32
Speaker 2: a immune gut axis that affects inflammation and that affects
41:37
Speaker 2: disease and might cause certain diseases. No one I met
41:41
Speaker 2: doubted that. They doubted whether it was a good investment
41:46
Speaker 2: and if it was easy to get a drug over
41:48
Speaker 2: the finish line, and it was easy to you know,
41:51
Speaker 2: take a microbiome therapy and treat a heterogeneous population that
41:57
Speaker 2: each has an individual microbiome that might change week to
42:00
Speaker 2: week if they've gone on vacation, et cetera. I mean
42:02
Speaker 2: this idea that it was easy from a drug development standpoint.
42:06
Speaker 2: So that's an example of a contrast between nobody was
42:09
Speaker 2: denying that the science was true. A lot of people
42:13
Speaker 2: were denying that it was a good investment strategy, Okay,
42:17
Speaker 2: And so that's why I say, I don't think anybody's
42:20
Speaker 2: denying that AI is going to have an impact across
42:24
Speaker 2: the spectrum to different degrees, across those you know, slices
42:28
Speaker 2: that you've described. So let me try to break that
42:31
Speaker 2: down for you. Drug discovery, Okay, when we saw recursion,
42:36
Speaker 2: I'll use because they've been a consolidator, and you know
42:39
Speaker 2: in the space for early drug discovery AI, well, we
42:43
Speaker 2: already know fharm is using it, other companies are coming
42:46
Speaker 2: for I think they drug discovery application is going to
42:50
Speaker 2: be largely commoditized. And so while it might have looked
42:55
Speaker 2: good to be a first mover in that space in
42:57
Speaker 2: the last five to ten years, I think at the
43:00
Speaker 2: end of the day, it's who's generating the best in
43:03
Speaker 2: class drugs and they're all likely going to be using
43:06
Speaker 2: some kind of drug discovery. Yeah, and I don't think
43:08
Speaker 2: we're going to know what companies. You know, which specific
43:12
Speaker 2: companies are going to be the right ones, right, that
43:15
Speaker 2: got it right with their proprietary algorithm. So when you
43:19
Speaker 2: move toward pre clinical and translational work, I think similar
43:24
Speaker 2: to human biology, animal biology is different. And I think
43:29
Speaker 2: why many people who are trying to predict where AI
43:32
Speaker 2: is going to have the low hanging fruit. Let's take
43:34
Speaker 2: like psychotherapy or psychiatry of providing somebody you know, augmented
43:40
Speaker 2: therapy with a pharmacological therapy to enhance their outcomes in
43:46
Speaker 2: psychiatric conditions. Right, that's low hanging fruit. Right, you could
43:49
Speaker 2: probably do it better than your local psychiatrist right in town.
43:53
Speaker 2: And so, but when it comes to biology and understanding
43:56
Speaker 2: compensatory decompensatory mechanisms, you know, a pathway that you know
44:02
Speaker 2: may be altered by a disease or a drug, right,
44:06
Speaker 2: that is hard to predict. And most people who predict
44:08
Speaker 2: and rank every industry that's going to be affected will
44:11
Speaker 2: generally rank human biology as yes, it will be affected,
44:16
Speaker 2: but it'll be one of the last ones affected. Right, So,
44:19
Speaker 2: either AI is going to control everything and every aspect
44:22
Speaker 2: of every industry on the face of the earth, or
44:25
Speaker 2: it's not. And I'd say biotech is the most protected
44:29
Speaker 2: right versus physics or things that are more engineering or right,
44:33
Speaker 2: things that are more predictive, unlike human biology. And so
44:37
Speaker 2: when you look at translational models and why many of
44:40
Speaker 2: us when we hear the agencies say we want to
44:42
Speaker 2: do away with animal testing, We're like, not so fast,
44:45
Speaker 2: because it still has some predictive power. It's not perfect,
44:49
Speaker 2: but it's still better than just doing in silico. Right now,
44:53
Speaker 2: that may change, but I think that is an area
44:56
Speaker 2: where both human subject biology and in EVA biology because
45:01
Speaker 2: we're not looking at large numbers yet. And I also
45:04
Speaker 2: like to say that remember in most biotechs, not all.
45:08
Speaker 2: We're not talking about the twentieth PD one or the
45:10
Speaker 2: twentieth GLP one. Those are easier to replicate and understand
45:15
Speaker 2: how you might engineer something using AI. But often biotechs
45:19
Speaker 2: are a novel target, a novel drug chemistry at a
45:23
Speaker 2: specific dose, going after a you know, specific target with specificity,
45:29
Speaker 2: and in a disease population that they might be going
45:31
Speaker 2: after a subset population in an risk population or rare disease.
45:35
Speaker 2: It's never been tested. So here you have never never never,
45:39
Speaker 2: never never never in the permutations around the multiply. There's
45:42
Speaker 2: nothing in the database that has ever looked at anything
45:45
Speaker 2: like this. Not to mention that if you take the
45:48
Speaker 2: entire database of biotech, you're still looking at ninety percent failure.
45:52
Speaker 2: So we might be good at predicting failure, we're not
45:55
Speaker 2: going to be that great at predicting success because we
45:57
Speaker 2: haven't had much success. And so that's why I am.
46:01
Speaker 1: More still a game though, if you could reduce the
46:03
Speaker 1: risk of failure.
46:04
Speaker 2: Right, But if you follow Bruce Booth's annual report, he's
46:07
Speaker 2: showing it's going down. The failure rate is going up
46:10
Speaker 2: that the success. So all I'm saying is that I
46:12
Speaker 2: don't think this is going to happen quickly, and I
46:15
Speaker 2: think it's going to happen incrementally, evolutionarily, not revolutionarily. And
46:20
Speaker 2: then the other piece of it, which I do think
46:22
Speaker 2: it can have a big impact and you're probably seeing
46:24
Speaker 2: it with the GLP ones, where you have millions of patients,
46:28
Speaker 2: hundreds of thousands of patient data that can be used
46:31
Speaker 2: to better just like we go to social media and
46:34
Speaker 2: we know those algorithms know us better than we know ourselves.
46:37
Speaker 2: I think you're going to see that with medicine on
46:40
Speaker 2: the commercial stage. I think the hardest part is in
46:43
Speaker 2: between that clinical stage, right, that pre clinical translational work
46:47
Speaker 2: to clinical clear data set that shows the drug works.
46:52
Speaker 2: That is going to be the hardest nuts crrect. I
46:54
Speaker 2: think we'll get it in discovery. We'll get it into
46:56
Speaker 2: some tools, enhancing tools like a ALPHA you mentioned to
46:59
Speaker 2: get a better what I call better thoroughbred at the
47:01
Speaker 2: starting gate. We don't have the tools yet to run
47:04
Speaker 2: the race, right being a good jockey or even knowing
47:08
Speaker 2: how to use AI as the right prompts right that
47:11
Speaker 2: you still need the jockey to run the race. But
47:14
Speaker 2: I do think we're getting good thoroughbreds in the starting gate,
47:18
Speaker 2: much like professional sports. The last analogy I'll make is
47:21
Speaker 2: that you know, the people who played baseball or football
47:24
Speaker 2: in the fifties, right, were not as well conditioned as
47:27
Speaker 2: the people today. But it doesn't mean it was any
47:30
Speaker 2: less competitive in terms of being the winner of the championship.
47:34
Speaker 1: Just a quick one on the speed of going from
47:37
Speaker 1: starting phase one, So I in D two finishing your trials.
47:41
Speaker 1: A lot of people say that we can cut down
47:43
Speaker 1: the white noise between ending one trial starting the next.
47:46
Speaker 1: The FDA is trying to get also the IRBs to
47:49
Speaker 1: go faster with AI involvement. How much do you think
47:52
Speaker 1: you can shorten that by say, let's say it's the
47:54
Speaker 1: standard zero two in the phase three drug six years.
47:58
Speaker 2: Yeah, well, I think we could do that. I think
48:00
Speaker 2: we can do that a lot today without AI, and
48:03
Speaker 2: we see that with the contract with China. And what
48:07
Speaker 2: I think McCarey recognizes is, you know, he is not
48:10
Speaker 2: going to look as good if he can't accelerate that
48:12
Speaker 2: or get people to do more US studies first. So
48:15
Speaker 2: I think part of it is getting into a clinical
48:17
Speaker 2: study more quickly because the other stuff. Enrollment can be
48:22
Speaker 2: enhanced by finding patients, but there are other limitations there.
48:25
Speaker 2: So I think AI will be a a factor of
48:29
Speaker 2: accelerating that, but not the factor. So I think we
48:33
Speaker 2: can work on a lot of other things with AI
48:37
Speaker 2: side by side with AI to accelerate that pathway. And
48:41
Speaker 2: I'm not even getting into like digital twins, which will
48:43
Speaker 2: accelerate things and all of that, and whether the FDA
48:46
Speaker 2: moves toward accepting other augmented data. You know, supplemental data
48:50
Speaker 2: rather than just a safety database of live human subjects
48:53
Speaker 2: to prove that a drugs safe.
48:55
Speaker 1: Yep, No, we've got we talked. You talked about China
48:57
Speaker 1: that I'm not going to go into China at a
48:59
Speaker 1: minute age when I got a minute left or not.
49:02
Speaker 1: But I do want one last question for you. What
49:05
Speaker 1: do you find Because at the end of the day,
49:07
Speaker 1: these companies are exited either by M and A or
49:10
Speaker 1: they go onto the market through IPO and they either
49:13
Speaker 1: get then sold at some point or they fail or
49:16
Speaker 1: they succeed significantly if you look at and most of
49:20
Speaker 1: those acquisitions are done by companies larger than them. So
49:23
Speaker 1: let's call them FARMA. What is FARMA looking for at
49:26
Speaker 1: the minute? Yeah? Well, the where is the area that's
49:30
Speaker 1: hottest in your mind?
49:31
Speaker 2: Yeah, well, look, I think you probably know the statistics
49:35
Speaker 2: as well as I do. But look, the encouraging part
49:38
Speaker 2: of it is that they have become much more diversified
49:41
Speaker 2: in their areas of interest. Right, So we saw I
49:44
Speaker 2: and I tick up and maybe surpass for new ideas.
49:48
Speaker 2: Right oncology. Oncology will always be a mainstak rare disease
49:51
Speaker 2: has started to swing back, right, But you see CNS,
49:55
Speaker 2: you see optimology, retinal disease, you see pulmonary and respiratory, right,
49:59
Speaker 2: you know, you're seeing a lot of these other areas.
50:01
Speaker 2: And CNS is not just rare, but neurology general and
50:05
Speaker 2: psych neuropsych and so you know, see a lot of
50:08
Speaker 2: you know, dermatology, you see you know and more serious
50:10
Speaker 2: like you know, skin diseases, et cetera. So I think
50:14
Speaker 2: I'm encouraged. Cardio Metabolic obviously is blown up big and
50:17
Speaker 2: so that goes from MASH to write type one and
50:21
Speaker 2: type two diabetes to obesity and the broader constellation there.
50:24
Speaker 2: So I think, but everybody who invests in these companies
50:28
Speaker 2: wants natural acquirers and they usually want several to generate
50:31
Speaker 2: some potential bidding wars and have many that need it
50:34
Speaker 2: for their pipeline. And I think that's where a lot
50:37
Speaker 2: of investors are listening to pharma. What are they looking
50:40
Speaker 2: to fill their pipeline, especially when the IPO window has
50:43
Speaker 2: not been as robust. That can change when the IPO
50:46
Speaker 2: window is open, but when it's not, we really listen
50:49
Speaker 2: hard to what pharma is interested, including European pharma, and
50:53
Speaker 2: you know, any multinationals.
50:55
Speaker 1: Okay, Chris Garvidian, it's been a pleasure speaking with you.
50:59
Speaker 1: Thank you for joining the Angers of Healthcare podcast of
51:02
Speaker 1: Bloomberg Intelligence Again. My name is Sam Fazelli. Chris, it's
51:05
Speaker 1: been a pleasure, and I'll speak to you very soon,
51:07
Speaker 1: and I'm pretty sure there'll be a medical conference together
51:10
Speaker 1: at some point.
51:11
Speaker 2: You got it, Sam, Thanks for having me. I really
51:13
Speaker 2: enjoyed the questions. They were very thoughtful. Take care, cheers,
52:03
Speaker 2: Pas