Latest / The BioHub - by Avetix / Episode 196 - Michael Rome - Managing Director at Foresite Capital

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Episode 196 - Michael Rome - Managing Director at Foresite Capital · The BioHub - by Avetix

0:06
Welcome back to the Biohub podcast by Avetix.
0:09
Today I'm joined by Michael Rome, managing Director at
0:13
Forsythe Capital Now. Michael joined Forsythe in 2016
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and now leads the firm's therapeutic investing practice
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spanning company incubation, syndicated private financings,
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and public market investing. Before Forsythe, Michael was an
0:28
analyst at Dafna Capital Management.
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He also brings a deep scientific foundation to investing with a
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bachelor's in molecular, cellular, and Developmental
0:37
biology from UCLA&APHD in Biochemistry from Caltech.
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In this episode, we'll explore Michael's path from science into
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biotech investing, how Foresight thinks about building and
0:48
backing therapeutic companies, the interaction between public
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and private markets, and what it takes to identify truly
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differentiated biology in the challenging funding environment.
0:58
Michael, it's a pleasure to have you with me today.
1:01
Thanks so much for having me, Ben.
1:03
Yeah, no worries at all. Just to start off with then, I
1:06
mean, as I just mentioned, you've trained as a scientist at
1:09
both UCLA and Caltech before moving into biotech investing.
1:13
What was the moment that you really realized you didn't want
1:16
to spend your career at the bench?
1:18
And how did that shut scientific training really shape the way
1:21
that you evaluate companies today?
1:24
Yeah, I think that decision to pursue a career in investing
1:29
took many years. So as you mentioned, I started
1:32
my scientific training at UCLAI was very fortunate to work in
1:37
different labs of, of principal investigators at the university.
1:41
So I worked in a in a neurobiology lab for many years.
1:45
I then spent time doing molecular biology, studying the
1:48
parasite toxoplasmicondi, which was a pretty interesting
1:51
experience. And then I even spent a year as
1:54
a lab technician after I graduated.
1:57
You know, I knew enough about the research career that I
2:02
wanted to go on and pursue my PhD.
2:05
During that time. I got, you know, obviously even
2:07
more experience as a bench scientist.
2:09
But what I found that really drew me into the career was the
2:15
intellectual curiosity that comes and the continual learning
2:18
process right when you're when you're studying science.
2:22
And I found that I enjoyed that much more than, say, working at
2:26
the bench, you know, doing doing pipetting or working on a
2:30
microscope or something. And that's, you know, anywhere
2:33
from can be 80 to 90% of your time.
2:36
But what really drew me into it was, you know, having the
2:39
journal clubs, having, you know, interaction with colleagues, you
2:44
know, going to seminars, all of that, you know, drew me into
2:47
looking at other careers besides being a best scientist.
2:51
And then I ended up, you know, right out of Graduate School,
2:53
you know, pursuing a career in the biotech field, going
2:56
straight into investing pretty much a year after I graduated.
3:00
Yeah. And I know a lot of people, I
3:04
mean, the investing market has changed over the past 10 years.
3:07
I think back sort of 20-30 years ago, that scientific background
3:11
wasn't a massive feature within a lot of these investors.
3:13
It was a lot more sort of business backgrounds, but the
3:17
market has changed, it changed, you know, things have developed
3:19
and scientific backgrounds do tend to be a lot more, you know,
3:23
apparent within the, the, the venture and investment space
3:27
nowadays. I mean, you know, how does that
3:30
mindset really help and that that sort of background
3:32
understanding when it comes to evaluating those opportunities?
3:36
Yeah, you're, you're absolutely right, Ben.
3:37
You know, when I first entered the career, it wasn't as common
3:42
to have a team of people with M DS or pH DS or advanced degrees
3:47
in science. If you look at the history of
3:50
biotech investing, I mean, there were people pursuing us with
3:52
many different backgrounds. And that's because the field of
3:56
investing has really changed over the years.
3:57
And biotech is a really interesting, you know, niche
4:00
kind of area in the, in the investing world.
4:05
It's, you know, it's, it's changed.
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I can just give you an example. You know, like 15 years ago,
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investors used to have an asymmetry of information, like
4:15
when a drug had FDA approval, like it could be posted on the
4:19
website first before a press release.
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So if you were just looking at different strategies, you know,
4:25
to make money in the market, you could essentially have that
4:28
asymmetry. What we have now is, you know,
4:32
to some degree, markets that are more fair and people are on, you
4:36
know, a a level playing ground. So when you're investing in
4:39
small and mid cap biotech companies or you're doing early
4:42
stage venture capital, you really are underwriting to a
4:46
technical thesis. You're trying to understand if a
4:49
drug is going to work or not, the nuances around patient
4:52
populations trying to and even the business principles that are
4:56
intertwined there. So it's become a very specialist
5:00
field. I like to make the analogy that,
5:01
you know, you're playing at a poker table, You're playing all
5:04
with poker pros and not, you know, not people who just have a
5:09
yeah, right. Yeah.
5:12
And you know, it, it's got to that point point where a lot of
5:15
people do understand the science, but you know, it's the
5:19
the market cycles that determine whether companies can raise
5:23
capital, can IPO, can partner or or even can survive is something
5:26
that perhaps isn't always understood as well.
5:30
For for the non financial listeners, those who are sort of
5:33
perhaps operators within the biotech realm, how do you
5:37
explain the connection between public markets, interest rates,
5:41
investor risk appetite and the amount of capital that's
5:43
available to biotech companies? Yeah.
5:46
These these are all the factors that really play into how
5:50
biotech markets are thinking at any given time.
5:53
Maybe to use an example of, of, you know, a prominent market
5:56
cycle that I, that a lot of people in biotech, you know,
5:59
executives, entrepreneurs, investors experienced, you know,
6:03
over the last, you know, call it six or seven years, You know, so
6:07
thinking about the period right before COVID, we had a pretty, I
6:11
wouldn't say completely steady biotech market, but we saw, you
6:15
know, more of a linear progression as far as companies
6:17
making advances. Interest rates were relatively,
6:22
you know, steady. I would say, you know, in that,
6:25
in that period following the great financial crisis, but
6:28
really going into 2019 and then into COVID, we really had a
6:33
pretty abrupt change in the, in the market cycle.
6:37
So as we all know, COVID came in, the Fed ended up lowering
6:42
interest rates to basically zero.
6:45
And when that occurs, there's a very tight correlation between
6:49
risk assets like biotech and interest rates.
6:52
So obviously, if you lower interest rates to 0, the
6:54
borrowing costs, you know, effectively become very cheap.
6:58
And so you can then enter into, you know, so-called riskier
7:02
markets like biotech. But that's, you know, there's
7:06
also money would go into earlier stage tech and even in that
7:09
period would be some money going into crypto currencies.
7:12
So a lot of speculation as investors were kind of chasing
7:14
yield. And so during that period we saw
7:18
money essentially just rush into the biotech market.
7:21
You probably remember the 2020 era we had, you know, a record
7:26
year as far as IP OS and saw right.
7:29
We saw companies who were going public, you know, that were
7:31
pretty clinical that had could be a year or two from the
7:34
clinic. That was highly unusual, you
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know, in the in the years, in the years leading up to this.
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And then we saw a pretty robust market going to 2021.
7:45
The music basically stopped when it became apparent that we had
7:49
an issue with inflation kind of at the tail end of COVID.
7:52
And then the Fed, you know, effectively went through a rate
7:57
increase cycle. And because of that, we saw
7:59
money come out of the biotech sector and really the fastest
8:03
money that went in, call it those IP OS or, or deals that
8:07
occurred for earlier stage companies.
8:09
Those were the companies that were disproportionately hit when
8:12
we went through that rate cycle, right?
8:16
And so as a result, if public market investors are unable or,
8:20
or venture, you know, earlier stage venture funds are unable
8:24
to get their companies public, that essentially creates, you
8:29
know, a stop in the funding because if you can't get your
8:32
earlier stage companies public, then what is the route to
8:36
liquidity, so to speak, besides M&A for an earlier stage
8:40
company? So we went through this cycle
8:42
and then as you Fast forward to today, you know, we're going to
8:44
have somewhat more of a steady rate environment.
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I think the industry's picking up some with respect to M&A in
8:50
the field. That's another driving factor to
8:53
think about South for in a really simplistic model, you can
8:56
look where interest rates are, where pharma is acquiring
8:59
assets, yes or no. And those two factors can really
9:02
influence how investors think about biotech investing, you
9:07
know, as a whole. Yeah.
9:10
Jumping back to sort of your background, I mean you started
9:12
on the buy side, you were typically covering small and mid
9:15
cap biotechs when you were looking across really you know
9:19
dozens of public biotech companies, What separated the
9:23
stories that were genuinely investable from those that have
9:27
had, you know, scientific interest but were potentially
9:30
financially a little bit more fragile?
9:33
Yeah. So, you know, your investment
9:36
mandate is somewhat a function of what kind of a fund that
9:40
you're in, right. So to to take an example, if
9:43
you're, you know, I started off working at a fund that was only
9:47
focused on on public securities and the fund, you know, most
9:52
hedge funds have a much shorter sort of term.
9:56
They end up becoming incentivized a lot of times on
9:59
what their performance was year to date.
10:02
And because of that, they could take more of a short term view,
10:04
like they're investing in companies that have a catalyst,
10:08
so to speak, maybe a clinical data event that could determine
10:10
if the company goes up 50% or not within that year time frame.
10:14
So because of that type of mandate, you're essentially
10:17
looking for shorter term things to play out.
10:20
And as you're, you know, looking through as a public investor,
10:23
you're looking at hundreds of biotech companies and trying to
10:25
understand what their data flow is at at any given time.
10:28
So that'll influence what you're investing strategy is.
10:32
Now if you take the inverse of that, if you think about it in a
10:35
venture capital sense, your time frame is much longer.
10:38
Venture capital firms tend to have lock up periods that can be
10:42
10 years in length. So that enables you to take that
10:46
longer term, you know, investment view, you can invest
10:49
in an early stage company in year one or two of your fund and
10:52
have the ability to play out multiple market cycles.
10:55
So if you go back and think about the error we were just
10:57
describing like in 2020 and you were in a longer duration in
11:01
fund, perhaps you have the time frame to wait out some of those
11:05
market cycles. And then in that case that as
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you're, as you're saying, the best science ends up, you know,
11:10
prevailing. And you can take that mindset
11:13
now. I don't want to, you know, when
11:14
you think about it again, as a, as a public market investor,
11:17
you're still underwriting the best science, but your time
11:20
horizon can be, can be different.
11:23
Yeah. And let's let's jump into
11:25
Foresight specifically. I mean, it's, it's fairly
11:28
unusual that a company invests across company creation, private
11:33
syndicated rounds and public markets.
11:36
How does really having that visibility across both public
11:39
and private markets change the way that you think about things
11:42
like timing, company valuation, and really the the the factors
11:47
that a biotech company needs to prove at each stage?
11:52
Yeah, it's a great question. So at Foresight, as you said,
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our mandate is fairly unique. We are investing out of a
11:59
venture capital private equity fund, but we're able to make
12:02
later stage public investments all out of the same fund.
12:06
So we'll focus, you know, anywhere from 50% of our efforts
12:10
doing company incubation. We even have an incubator called
12:13
Foresight Labs that enables us to do these earlier stage
12:16
efforts. We'll then do, you know, company
12:20
syndication with other, you know, venture investors call
12:24
those series as where we're investing, you know, in a
12:27
company might not be an incubation that we did, but you
12:31
know, is that something we're doing in collaboration with
12:33
another firm. We then do another call it, you
12:36
know, 30 percent, 40% of times into later stage investments.
12:41
And those can be companies that you know are doing a so-called
12:45
crossover round or later stage private round before going
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public. It can be companies, you know,
12:51
like our portfolio companies that are growing up that are
12:54
going through an IPO or can be a follow on financing.
12:58
So we really have the ability to invest, you know, across all of
13:02
these different cycles of of a company.
13:05
And, you know, at the end of the day, what we're trying to do is,
13:09
is underwrite A thesis where we're looking to affect areas of
13:15
large unmet medical need, regardless if they're a private
13:18
company, if they're a public company.
13:19
So, you know, take an example. You know, if you say you're
13:23
investing in an area like pancreatic cancer or lung
13:26
cancer, lung cancer tends to be more saturated.
13:29
There's been, you know, a fairly steady amount of advances over
13:33
the past decade. Whereas pancreatic cancer, you
13:37
know, there's really only been a handful of things that have made
13:40
a difference, including, you know, Revolution medicines has
13:43
had a breakthrough in pancreatic cancer.
13:46
So you could, you could go, you could, you could go back and you
13:48
could say, hey, you know, we're trying to underwrite earlier
13:51
stage investments. Maybe we're going to look in
13:53
pancreatic cancer areas of large unmet medical need where you
13:57
know, therapies are are needed. And so that can influence how we
14:03
think about, you know, earlier stage versus later stage.
14:06
Now what's what's fascinating is I like to think of, you know,
14:09
both of the the ability to do both as like a positive feedback
14:13
loop. So if we're thinking about the
14:15
market right as a public, as a public investor, we're trying to
14:20
find, you know, things that are more product centric.
14:22
As we said, the time horizons can be different.
14:24
So public investor would probably favour an asset that's
14:28
in phase two or phase 3 / a platform.
14:31
That's almost always the case. So understanding the market
14:34
needs say, you know, we understand that there needs to
14:38
be, you know, advances in pancreatic cancer and we're
14:42
thinking about it as a public market investor.
14:44
That'll influence how we think about it at on the earlier stage
14:47
side. So we might say to ourselves,
14:49
how do we get to an early stage concept to a product?
14:54
And I would say a lot of earlier stage investors tend not to
14:56
think that way. They tend to make bets in larger
14:59
categories. And that's obviously a strategy
15:02
that has been very has been very profitable to a lot of venture
15:06
firms. But we like to think of things,
15:08
you know, for the most part on these sort of product cycles and
15:11
how do we do that with a with that kind of mindset.
15:14
Now conversely, if we're doing a later stage investment, we use
15:18
all of that experience from sitting on private company
15:20
boards going through those long cycles.
15:23
We tend to do due diligence really on all aspects of drug
15:27
development, whether that's, you know, underwriting A clinical
15:30
trial or doing independent IP due diligence, doing
15:34
manufacturing due diligence. Again, all that comes from being
15:36
really involved on the private side.
15:38
And then we use that knowledge to make those later stage public
15:41
investments where we're able to focus on all the facets of the
15:44
business and trying to find, you know really those long term
15:47
winners again that are addressing those large unmet
15:50
medical needs. Yeah.
15:52
And your your therapeutic strategy typically includes, you
15:55
know, backing experience entrepreneurs, incubating new
15:58
companies, licensing or acquiring assets, building
16:02
around really differentiated biology.
16:05
From your seat, where you're leading this entire strategy,
16:08
what does a great company formation opportunity look like
16:11
before it's typically obvious to the rest of the market?
16:15
Sure. So maybe to take a specific
16:17
example and you mentioned in licensing, we recently had a
16:22
portfolio company called Candy Therapeutics, which was required
16:25
by UCB earlier this year. Candid started really as an idea
16:32
in the T cell engager space. So to just go over the
16:36
background really quick, there was a Seminole paper that was
16:40
put out by Georg Schetz lab in Germany where they were using
16:45
CAR TCD 19 CAR T cells to treat indications in autoimmune
16:51
disease, in this case lupus, instead of using CAR T for the
16:55
more traditional indications like hematological malignancies.
17:00
So the insight that York Chet had was that you could
17:04
essentially use these CAR T cells.
17:06
Again, CAR T is taking cells out of your body and reprogramming
17:10
them to attack essentially CD 19 positive cells and and for the
17:17
most part cancer patients. In certain indications, their
17:21
malignancies could be caused by a dysregulation of these CD19
17:26
expressing cells. But it turns out in autoimmunity
17:29
you can also reset these CD19-B cells that are important in the
17:36
pathogenesis of diseases like lupus.
17:39
So lupus patients will have autoreactive antibodies from
17:43
these CD 19 positive B cells and that for the most part mediates
17:46
the disease or is one of the primary drivers.
17:49
So Chef put these CD 19 cells into into patients and saw
17:54
remarkable responses for the first time really seeing durable
17:58
responses in lupus patients. So we thought about this, this
18:03
concept and again going back to our public market experience,
18:06
there were several public companies that were developing
18:10
CD19 CAR T therapy and we saw public market, public market
18:14
investors really respond positively to this trend because
18:17
it opened up this door of you know, going after a range of
18:21
autoimmune disorders. We started thinking about
18:24
thinking about this and we said, you know, CAR T cells for
18:27
autoimmune patients really is going to be a commercial
18:29
challenge. These patients are not like late
18:32
stage oncology patients where they would go through this kind
18:36
of process for CAR T cells. For CAR T you have to get pre
18:39
emptive chemotherapy. It takes anywhere from 30 to 60
18:42
days to manufacturing the cells. There's an issue with cell
18:45
quality as it goes back into patients.
18:47
It's hard to control the side effects a lot of times because
18:51
it's a one and done therapy at the same time.
18:54
We saw emerging technology in T cell engagers and T cell
18:58
engagers are really interesting molecules.
19:01
One arm of AT cell engager binds your target of interest.
19:05
This could be CD19 on AB cell. The other actually engages your
19:09
immune system to effectively do What Car T does.
19:12
And you're doing this in the format of an antibody.
19:15
So it's easy to administer. We understand the size and we
19:18
have the thesis that you could essentially repurpose T cell
19:21
engagers to do the same thing that CAR T was doing in
19:24
autoimmune and it would solve those commercial challenges and
19:27
issues for for patients. And again, these autoimmune
19:30
patients are not in the same state as an oncology patient.
19:33
They want, you know, convenient therapies.
19:35
And so we said, you know, T cell engages could be the next sort
19:39
of frontier in autoimmunity. And using that lens again as
19:43
public market investors, we went back to our sort of venture
19:46
venture creation hats and we said let's go find T cell
19:49
engagers. So we went on this exhaustive
19:52
effort for, you know, almost two years trying to find the best
19:56
targets for T cell engagers. We came away thinking that a
19:59
target called BCMA, which is again expressed on B cells and
20:03
it has a major role in the pathogenesis of autoimmune
20:06
disease, would be a good target. So, you know, we've probably
20:10
looked at hundreds of companies. You know, looking at companies
20:13
in not only the US but EU and then a large concentration in,
20:17
in Asia, we've built up a practice of doing this in Asia.
20:21
We've done, you know, almost 12 transactions total including
20:25
staff incubator out of our portfolio companies.
20:28
So essentially we went on this path.
20:30
We ended up licensing 3T cell engagers into into a company.
20:35
The first were assets that we found.
20:37
One was a BCMAT cell engager from a company in China that was
20:42
and then there was a second T cell engager.
20:44
Then another investor group found, and then we found a third
20:47
T cell engager that was actually targeting two different
20:51
antigens. So when we found that first T
20:54
cell engager, we actually ended up engaging an entrepreneur
20:57
named Ken Song. Ken had recently sold his
21:01
previous company raised bio to BMS and he was looking for his
21:04
next venture. And so we ended up organizing
21:06
candidate therapeutics around these assets and Ken brought his
21:10
entire team back from Ray's. They really did a phenomenal
21:12
job. They ended up developing this,
21:15
these T cell engagers in, in autoimmune patients and our
21:19
original thesis played out where we if you use a BCBCMA targeting
21:24
agent that can have a profound effect.
21:27
And so we showed in various autoimmune diseases that we
21:30
could see profound efficacy and so and also have a, a good
21:35
safety profile. And and lastly could be you know
21:39
a patient could possibly inject these at home.
21:42
And this is this is something that you can do with with T cell
21:46
engagers, especially at small volumes.
21:48
And so all of that data we generated and we ended up
21:50
generating over 50% of the data in China.
21:53
We can talk about that more, but that led to the company being
21:57
acquired again in less than two years from UCB for for about $2
22:01
billion upfront. Yeah.
22:04
I mean, it's a fascinating story.
22:06
And to anyone who's who's not familiar with it, I'd recommend
22:08
going and doing some some reading up on candid.
22:12
Something you touched on there was Asia and I want to delve
22:14
into this a little bit deeper, but particularly focusing on
22:17
China. I mean, there's been a huge
22:19
amount of activity around China originated assets, particularly
22:22
in oncology and immunology. Like you mentioned Foresight
22:26
themselves have been looking at China since around 2019 and you
22:30
know, you've been using China source science within company
22:32
formation strategies across a number of different companies.
22:35
What? What's what's really changed in
22:37
the quality, the competitiveness and the global relevance of
22:41
China within the global biotech community in the last five
22:44
years? Yeah, it's really a fascinating
22:48
time for what is going on in China for biotech.
22:52
If you take a step back and maybe think about China in the
22:54
framework of a market cycle, it's a it's, it's illustrative
23:00
to think about this for where we are today.
23:02
So China has gone through, believe it or not, a few kind of
23:05
boom and bust cycles in biotech. The most recent cycle happened
23:09
about 7 years ago where a lot of money went into China.
23:13
And this was due to various reasons, a lot of advances in
23:17
the tech industry that some of that flow through to biotech in
23:21
the form of venture capital dollars.
23:23
And then you saw a really, you know, a nice steady stream of,
23:26
of, of innovation occur when you had capital flowing into the
23:30
cycle. And then China ended up having,
23:33
you know, a sort of robust market for, for, for biotech
23:36
during that time that brought even more money into the cycle.
23:40
And then something interesting happened about, you know, I
23:42
think it was about six years ago or so where the public markets
23:47
ended up going through an issue similar to the US where the
23:50
windows started closing for biotech companies.
23:52
So you have this really this bolus of money that went into
23:55
the sector that caused a lot of innovation.
23:57
And then we saw it sort of slow down dramatically when the
24:00
public markets change. So as a result, you had a lot of
24:04
companies become financed, as we say, the music kind of stopped
24:07
at that time and companies kind of ended up becoming trapped, so
24:11
to speak, for accessing capital. And that created an opportunity
24:15
for not only investors for but also, you know, multinational
24:19
corporations, large pharma companies that were looking for
24:22
assets. And what started, you know,
24:24
happening is in a very gradual fashion.
24:27
You know, you were able to go into China and form partnerships
24:30
with companies or do acquisitions of assets and put
24:33
those, you know, as we were describing for candidate into
24:36
separate companies. Now these companies, you know,
24:39
for the most part would be domiciled in the US or in the
24:42
Caymans. It would be separated, you know,
24:44
from entities that are in China. But nonetheless, you saw all of
24:47
these transactions and pharma started, you know, getting smart
24:51
on the space and they said, you know, the industry's really
24:54
evolved. Now, there used to be this
24:56
perception that generating data in China was inferior to other,
25:00
other, you know, geographies like the US and, and EU.
25:04
And as the sector advanced, all of that started to change.
25:07
So now, if you look at clinical data that's coming out of China
25:09
now, in a lot of ways, it's it's indistinguishable from data you
25:13
would find in the in the US. They have high quality
25:16
hospitals, they have specialty hospitals for oncology
25:20
autoimmunity. So a lot of these doctors and
25:21
investigators are well trained in these fields.
25:24
There are going to be differences in the way patients
25:26
respond due to background genetics for for some therapies.
25:29
We see this in the oncology space, for instance, and in some
25:33
cases in autoimmunity. But then companies can really
25:36
look at full data packages, things that were occurring in
25:39
clinical trials and extrapolate whether they would work in the
25:42
US. So if you, this is a really
25:43
interesting, interesting status, something like five years ago,
25:47
you know that that the, IT was was basically single digit, the
25:50
percentage of deals that pharma was doing in China.
25:53
And if you Fast forward to today, it's almost 50% of deal
25:57
value by all transactions. So you know, going through that
26:01
that that sort of capital cycle. And So what happened was all
26:04
these transactions started occurring that caused another
26:06
boom cycle as capital went back in the sector and then the IPO
26:10
window actually opened again and this time on the Hong Kong
26:12
exchange. So that's fueling right now all
26:15
of this M&A, you know, the quality and data having a public
26:18
market now that is, you know, receptive to having biotech
26:22
companies that's causing this, you know, really, you know,
26:26
impressive, you know, you know, biotech, you know,
26:31
transformation that's that's that's occurring right now.
26:34
The last thing I'll say is the public markets are always
26:37
changing. The Hong Kong Stock Exchange
26:39
just had another rule go into effect now where it will
26:43
somewhat limit the types of companies that can go public in
26:45
China. So we could see a little bit
26:48
slowing in that cycle. Right now, there's no indication
26:50
because M&A volume is just is just so large.
26:52
But yeah, it's certainly and an interesting time.
26:58
Yeah. And it's going to be going to be
26:59
an interesting one to watch over the next few years and see how
27:02
how things develop and how how obviously they impact things
27:04
over in the States as well. I think one challenge that we do
27:08
typically see in Biosec is that capital can quickly move into a
27:13
hot area and suddenly there's many companies that have been
27:16
developing similar assets. And you know, you've cautioned
27:19
in our previous conversations about, you know, a lot of people
27:22
developing the same drug. How do you really distinguish A
27:26
genuine first in class or best in class opportunity from more
27:31
of a crowded me to thesis? Yeah.
27:35
It really goes back to the industry being motivated to be
27:39
product centric. And this goes back to when we
27:42
had the correction in 2022 with the rise of interest rates,
27:46
investors really flocked to safe assets.
27:49
So things that they can handicap the probability of success for.
27:52
So we saw a lot of investors crowd into companies that were
27:56
going after the same target. And what that does is it does
28:01
sort of enhance the probability of success, but it also limits
28:05
your upside, right? So if you're invested in a
28:06
company that, to use an example there, there were, you know,
28:11
dozens of companies trying to develop the the T slip space.
28:14
T slip's a target, you know, for indications like asthma.
28:18
So it was well defined. You can understand the clinical
28:21
path well, but because of all of this crowding, you know, from an
28:25
investment point of view, it does limit your investment.
28:28
Now if you go back to an area we were talking about earlier, like
28:31
pancreatic cancer, right, it's pancreatic cancer has been an
28:35
area that traditionally it's been really hard to develop
28:37
novel therapeutics. So you might think that your
28:40
probability of success there would be much lower that would
28:43
be a correct intuition. But when you have breakthroughs
28:46
that occur and again, going back to revved had this really
28:49
interesting breakthrough where they can make these small
28:51
molecule drugs that were able to antagonize driver mutations in
28:56
proteins like Ras. That was a scientific
28:59
breakthrough, right? And because the competition,
29:01
there was no competition giving given that the space was so
29:04
difficult, that in a sense presented a lot more upside.
29:08
So because, you know, I think the market is really good at
29:12
rewarding companies that are going after large unmet medical
29:15
needs. And you see this over and over
29:16
again in in acquisitions. I mean, pharma is going after
29:21
novel products a lot of times that will, you know, give them
29:26
that will increase their sales a lot of times in the near term.
29:30
So it's, you know, crowding is still an issue today.
29:38
We still see it across a number of therapeutic categories,
29:40
whether you're trying to modify an existing drug, maybe it's a
29:45
little bit better or maybe it's better, you know, for a patient
29:47
from the frequency of taking the drug, but you know it, it does
29:52
help to focus on areas where you're not where others are.
29:56
And again, from an, from an investment point of view, you
29:59
would probably say to yourself, I'm underwriting that,
30:02
underwriting the risk. Maybe it's a 50% chance
30:05
something's going to work, but if it does work, then the upside
30:08
can be 10X. So using a probability adjusted
30:12
point of view, you know, your upside of that case would be,
30:14
you know, would be 5X versus if you were again, in a sort of in
30:18
a crowded category, maybe your probability success is 80%, but
30:22
your upside is 2X. So the math definitely works,
30:25
you know, works your favor in this case if you're going after
30:27
large unmet medical needs, but it is risky.
30:30
I I will say that. Yeah, of course.
30:33
But yeah, without, without risk, there's no reward, right?
30:37
Exactly. Let let's take sort of a focus
30:40
on now as, as, as a biotech lens.
30:44
Your most recent fund was a $900 million fund focused, you know,
30:48
split between precision therapeutics, life science
30:51
infrastructure and healthcare delivery with therapeutics still
30:54
being a major part of the strategy.
30:56
But when you look across the likes of, you know, oncology,
30:59
immunology, neuroscience and other therapeutic areas, where
31:03
do you think the market is massively underestimating that
31:06
next wave of therapeutic innovation?
31:09
Sure. Yeah.
31:10
So in our fund, we do about 70% or so on the therapeutic side,
31:14
another 30% in areas like healthcare services or genomics
31:19
and sequencing. And, and for therapeutics, we
31:21
really concentrate most on on novel therapies.
31:26
So we're trying to find things that are really going to, you
31:29
know, set the standard of care for, you know, various
31:32
indications. And when we look across areas,
31:35
it's fascinating because areas like oncology, we've seen a lot
31:38
of innovation over the last 10 years.
31:41
You can actually look at survival curves for oncology
31:44
patients and you now see meaningful differences in
31:47
survival, you know, over shorter periods of time.
31:50
And this was a factor of us understanding the underlying
31:54
issues that occur with different oncology indications.
31:58
So, you know, 15 years ago, we used to use chemotherapy in the
32:01
majority of patients, regardless if you're a lung cancer patient,
32:05
if you're a Melanoma patient. But now we understand the
32:08
molecular features of these different cancers that enables
32:11
us to do in a lot of sense targeted therapies and not, you
32:16
know, just say, hey, you've got lung cancer, we're just going to
32:18
give you chemotherapy. And those advances, you know,
32:21
using the latest science to target these different driver
32:24
mutations has been a major breakthrough.
32:27
And so we're still investing heavily in the oncology space.
32:30
We're seeing, we're seeing lots of breakthroughs and I, I can
32:33
even tell you about areas that we're, that we're going into,
32:36
but areas like autoimmunity now are going through a similar
32:40
cycle. They were understanding the
32:42
underlying pathogenesis. Pathogenesis is better.
32:45
So we're not just saying, you know, if you have lupus and you
32:48
have kidney involvement, we're not giving, you know, thinking
32:51
about it as like a blanket therapy.
32:53
Instead, we're now starting to think about it as a genetic
32:56
signature that could occur and again, using that sort of
32:59
precision framework for going into autoimmunity.
33:02
So we're spending a lot of time in this space, especially as we
33:06
understand, you know, molecular features again, of different
33:10
patient subsets and different indications.
33:12
I believe that we're going to go in, we're going to have now a
33:14
major revolution that's going to occur in autoimmunity as we did
33:18
in cancer. So we're spending a lot of time
33:19
there. Another area we're spending time
33:22
in which is probably not a surprise to you is in the cardio
33:26
metabolic space, and in particular what's going on right
33:29
now in the GLP 1 space. So GLP ones are on track now to
33:33
be the most successful drug, you know, really in the biotech
33:36
industry. What's fascinating is you're
33:38
seeing patients that are paying out of pocket, not necessarily
33:42
going through, you know, their insurance.
33:44
There's pharmaceutical companies that are like Lilly now that are
33:47
offering pills, you know, for as little as $150.00 a month could
33:51
be cheaper than than things like your, your monthly iPhone
33:55
payment. So this is a major revolution
33:59
that's going on right now. And companies like Eli Lilly
34:01
have so much capital that they're, you know, buying
34:04
biotech companies like a record pace.
34:06
So we're watching this trend occur, whether it's Eli Lilly,
34:09
Novo, Roche that are that are that are in these areas.
34:12
And we're thinking, well, what's the next step now?
34:15
And the biggest issue with GLP one therapies is, you know, you
34:19
end up losing a lot of fat mass, but you also lose muscle mass.
34:23
And so this is creating a large unmet medical need.
34:27
We've seen in patients where if they're on high protein diets,
34:31
maybe they're eating a gram of protein per gram a body, sorry,
34:36
per pound of body weight that can mitigate this.
34:39
But that's a pretty tall order to ask, you know, a patient to
34:43
do that. And so if we had an, an agent
34:45
that directly went after different mechanisms in, in
34:49
building muscle, that could be a huge aid for patients who go on
34:53
GLP 1. And it can also be something
34:55
that you could treat older patients with that are, you
34:58
know, that's definitely an issue as you age, you know, losing,
35:00
losing muscle mass, right. And so what's really
35:03
fascinating, I, I encourage your, your viewers to do this,
35:06
you know, Google the myostatin knockout bowl.
35:10
And what you'll see is that if you knock out a protein called
35:12
myostatin, you get like this, you know, Arnold Schwarzenegger
35:16
bull that's just has tons of muscle.
35:18
And that was like one of the earliest cases where we could go
35:22
after certain proteins to increase muscle mass.
35:25
And now we're seeing several therapies, early stage science
35:29
that's doing exactly that. And we're going after these
35:32
novel targets because we think the market is headed there.
35:35
So that's an area of unmet medical need that we're
35:37
gravitating towards. There's no approved drugs in
35:40
this space. We think it's going to offer a
35:42
lot of benefit to patients. Again, not only for GLP one, but
35:45
maybe you're an older patient, you know, concerned about losing
35:49
muscle mass. So we're going after that area.
35:51
And then the last area I'll mention is in the neuroscience
35:54
space. We think there are profound
35:57
therapies that are emerging now and depression and anxiety, I
36:00
can talk more about that, but we are spending a lot of time there
36:03
as well. Yeah, and that's that's a pretty
36:06
big area of focus at the minute, especially with all the hype
36:09
that's surrounding psychedelics as well.
36:12
Yeah. So we are definitely interested
36:14
in this space. And there I would say you're
36:17
right, there is a lot of hype, but there also is a lot of data
36:21
now to support the efficacy of these of these medications.
36:25
And so it's really interesting. You can, you can, you can try to
36:29
study in animal models what different drugs are doing.
36:33
You know, in traditional, you know, neuroscience, you know,
36:37
you have drugs like SSRIs that are affecting neurotransmitters
36:40
like like serotonin. You have other classes of drugs
36:44
that patients might cycle through that are affecting
36:46
different pathways in the brains.
36:48
And there's a ton of overlap between all these drugs for
36:51
different psychiatric conditions.
36:53
So a long winded way of saying we don't really understand well,
36:56
a lot of these mechanisms and what's going on.
36:59
And we've had a lot of these drugs, you know, going on 50
37:01
years, a lot of the same drugs that patients are taking.
37:04
And we're finding now that, you know, most patients will end up
37:07
over the course of their, you know, of this therapy, end up
37:11
needing a new class of medication.
37:13
And So what, you know, Fast forward to today, there was a
37:16
lot of anecdotal evidence in the in the psychedelic medicine
37:20
space that these were having a profound impact in patients.
37:24
And so now there are several companies developing different
37:27
psychedelic drugs. Probably the most notable is
37:30
J&J, which is developing a version of inhaled ketamine that
37:35
is selling really well. A patient goes into psychiatric,
37:38
goes into their psychiatrist's office, it's around 2 hours,
37:41
They get a ketamine administration and then that
37:45
produces durable effects in patients.
37:49
There are companies now that are developing different
37:51
psychedelics. You have public companies
37:53
developing LSD and psilocybin. Psilocybin is being developed by
37:57
by by Compass and there are other companies as well that are
38:02
developing, you know, therapeutics like DMT.
38:06
The issue with the long acting psychedelics like psilocybin or
38:10
LSD is that that could take a patient 8 hours to see an
38:14
effect, whereas you know, medication or where psychedelics
38:19
like DMT offer a much shorter experience, in some cases only
38:23
30 minutes. So we think there's a, you know,
38:26
commercial advantage to having a shorter acting psychedelic.
38:29
And again, if you look at the clinical data for all of these,
38:31
it's producing some of the most profound effects for for things
38:36
like depression. We're trying to understand the
38:38
mechanism better because patients will undergo this
38:41
hallucinogenic state for some period of time.
38:44
It's unclear whether that is coupled to the therapeutic
38:47
effect. Some, some scientists believe
38:51
that these drugs and it's been shown in animal models will
38:54
produce new neuronal connections and in some cases new neurons.
38:59
That's almost unheard of with other with other therapies.
39:03
So as we're, you know, even thinking about the next
39:05
generation of psychedelic drugs, perhaps we can engineer out some
39:09
of those effects. You know, where you essentially,
39:12
you know, where are, are in a, in a state where you know,
39:16
you're, you're, you haven't lost a sense of reality, but you're
39:19
you're certainly, you know, going through a mystical
39:23
experience. So it would be interesting to
39:24
see actually become come up with drugs that, you know, become
39:27
even safer for patients. Yeah, 100%.
39:31
I mean something that we've touched on quite a lot today has
39:33
been the difference between the long term and short term
39:35
investor mindset. You know, cycles can be brutal.
39:39
There are windows where almost everything gets funded, windows
39:42
where even the the best of companies struggle.
39:45
How as a long term investor do you really stay disciplined
39:49
during those different cycles and you know, ignore the reality
39:53
of, you know, the market that you're operating in?
39:56
Yeah, definitely. I think the keyword here,
39:59
especially for early stage venture capital is resilience.
40:04
So you really have to have a mindset where you can weather
40:08
these cycles. And I think it also is helpful
40:11
to start with your baseline. And the baseline is that most
40:14
biotech companies will fail in, in some form of another.
40:18
You know, whether they be whether it's a competitive
40:22
reason or a reason where you can't access capital at certain
40:25
times. If you just at least enter into
40:27
the space knowing that the failure rate is high, then that
40:31
definitely helps. I will say that the industry has
40:33
gotten a lot better. Now we're really able to make
40:37
investments and have a much higher success rate or at least
40:40
able to, you know, exit a business in a downside scenario,
40:44
you know, close to your cost. So entering into that space,
40:47
knowing that it's incredibly volatile and the failure rate
40:50
is, is higher, that can help you weather different, different
40:55
market cycles. And I think, you know, it isn't
40:59
quite appreciated, but at times the mindset of of, or if you, if
41:03
you, sorry, if you just kind of look at the stats and what makes
41:06
this successful venture capital fund, they can be successful on
41:09
having one or two outcomes. So one company that ends up
41:12
becoming a $10 billion exit can essentially, you know, cause a
41:17
fund to be successful off of 1 investment.
41:20
Now there's many different ways to go about it.
41:22
You know, there are certainly funds that are successful having
41:24
10 investments where maybe the outcomes were more on A2 to 3X
41:28
basis. So you can't just have a fund
41:31
that is, you know, has one or two exits that that ends up
41:35
driving returns. And knowing that the range of
41:38
outcomes can be so wide, you know, depending on how things
41:41
shake out, that really helps frame your mindset.
41:45
So again, expect volatility. You know, you need to be
41:49
resilient. It's not the end of the world if
41:51
one of your companies that, you know, ends up not being
41:54
successful where you previously thought it was because it's
41:57
really hard to predict at the end of the day what's going to
41:59
happen. And again, it's so influenced by
42:01
things that are outside of your control, like like, you know, a
42:05
given market cycle. Yeah, exactly.
42:08
I mean, just to sort of wrap things up here then, Michael,
42:11
you know the final question that we ask every guest, guest that
42:14
comes on, if you could have dinner with any scientist or
42:16
innovator, past or present, who would it be and why?
42:21
Yeah, definitely. I would say if I had to pick
42:25
one, you know, a dinner where there was three people, one from
42:30
the investment world, one from the science world, I would say,
42:34
you know, from the investment world.
42:36
A big fan of the late Charlie Munger.
42:40
And I, you know, I think where Charlie Munger's really
42:42
interesting is he had a reputation of always, you know,
42:45
sort of telling the truth and, and not being, you know, afraid
42:49
to have a viewpoint that's not consensus.
42:53
And that would be a really fun lunch to have.
42:56
I'd be really curious what he thinks of the current market
42:58
cycle we're in today where AI is sort of dominating and
43:02
valuations have gotten really high.
43:03
I'm sure you'd have a contrary view there.
43:05
And then from the science side, I think of innovators like like
43:09
David Baltimore. David Baltimore won the Nobel
43:12
Prize at a very young age for discovering an end time, call it
43:14
for first transcript days. He then went on to not only do
43:18
that, but you could argue maybe he should have had another Nobel
43:22
Prize for all the work he did after even contributed to the to
43:26
the to the car T field. So I think it would be fun to
43:28
have, you know, someone who's demonstrated, who's demonstrated
43:33
success, you know, in science and multiple angles and also
43:36
have someone on the on the investment side.
43:38
I think that would that would probably be a pretty, pretty
43:40
interesting dinner. Yeah, most certainly would.
43:43
And if if you ever managed to make it happen, let me know and
43:45
and see if you can wrangle me an invite as well.
43:49
That's right. It's been a been an absolute
43:52
pleasure to have you join me today, Michael.
43:54
Yeah. We really appreciate you coming
43:56
on. Thank you so much, Ben.
43:58
It's been great talking today. Yeah, no worries and thanks to
44:02
everyone for tuning in. Make sure you subscribe and and
44:05
drop a like to stay tuned for future episodes.
44:07
But that's all for now. Cheers.