#130 - Bihua Chen: Inside Biotech Investing

0:00Welcome to the Insightful Investor Podcast, a weekly series that seeks to share industry, investment, and market insights. Learn more about our show at insightfulinvestor.org. Today's guest is Bihua Chen, joining me in our new podcast studio in Los Angeles. Bihua is the CEO and portfolio manager of Cormorant Asset Management, a Boston-based biotech investment firm. Cormorant manages approximately$2.5 billion in public long-short strategy, as well as a private investment strategy. Today, we're gonna talk about Biwa's path from molecular biology into biotech investing, how she evaluates science and risk across public and private markets, and where she sees the next important breakthroughs in drug development.

0:52Biwa, thank you for joining us today.

0:54Bihua Chen:Oh, thank you for having me. You studied molecular biology before moving into investing. What did you see early on that convinced you capital allocation could be a meaningful way to shaping the future of medicine? Yeah, so I started in biotech investing in 1998. And within the first year, I noticed there's some spectacular failure and spectacular success in clinical trial. And I figured those are the events that I could apply my biology knowledge, do some analysis and a forecast. And I figured out that if more people do that, the capital can go into the idea that eventually will really work. So it's an analyzable to a certain degree process.

1:47Did you notice more failures than successes when you looked early on?

1:50Bihua Chen:Yeah, usually there's more failure, unfortunately. So looking back on that transition, what has remained constant in how you think and what has fundamentally changed? Things are actually pretty constant. The change is more competitive now. So the constant theme is people have scientific hypothesis and very often that hypothesis is wrong. It's just because we don't know. And the drug trial is actually one way to figure out really that process is correct or not. So we still face a lot of failure. But on the other hand, once people figure out a pathway that works, it's very competitive these days.

2:38Bihua Chen:There could be 20 different companies flood into that approach, which I don't see in the early days of biotech. So for someone who is unfamiliar with the field, how do you explain in plain English what a biotech investor actually does? Yeah, biotech investor trying to back companies that eventually win FDA approval of a brand new drug. Now that's in the long term. There's obviously a lot of trading around it, but at the core, that's what it should be. So the FDA approval process is broken down into companies do preclinical toxicity and efficacy study before they get FDA approval to do human testing.

3:34Bihua Chen:And human testing is normally divided into phase one, two, and three. Although in some disease, phase two will be enough. You don't have to do phase three. In some disease, you need to do too large phase three trial. So along the way, there are milestones that companies need to deliver in order to go forward. There are companies sometimes look at less ideal set of data, still decide to go forward. In that case, it's a waste of capital that society should try to avoid. And that's the kind of thing we hope our work will contribute. Your work sits at the intersection of science, capital, and judgment.

4:27What makes biotech investing intellectually distinct from most other sectors in that regard?

4:33Bihua Chen:Most people in biotech investing actually have to have a technical knowledge of either biology, chemistry, or clinical practice. Now, it doesn't mean you have to have the degree, even if you don't have the degree, but you still need to acquire that expertise. So I think it's one of the areas that the technical expertise is very important. Now, that alone does not guarantee success because, as you know, stock look forward, speculate on the probability of success or failure already. And to make money, you must differ from the consensus. You founded Cormorant in 2015, a little over a decade ago. What did you want to build that you felt did not already exist in biotech investing?

5:26Bihua Chen:Yeah, so I started Corman in 2013 after about 15 years already in the business. Those 15 years mostly were around secondary market. the company already come IPO. Although I noticed my natural tendency is to invest really for the long term and succeed or fail along with the drug. So I think it would be good for us to do both private and public. So Corman started with a hedge fund and a branch into the private fund, as I figure, it's same core set of expertise. And there's a lot of synergy that come from doing both. And then how did that original vision for the firm compare to what the firm has become today?

6:27Has it essentially played out as you envisioned?

6:29Bihua Chen:Yes, it played out pretty well. The public fund has been carried out as an original strategy. And we launched two years after Cormoran founding to start private investing. And we have just closed fund six of private funds. So we are executing plan on both sides. Okay. And how is it different between your private investments and your public investments? And do you feel like having exposure to both sharpens your skills and your thinking? So private investing deals with a little earlier stage than the public investing, although in a very frothy bull market, a lot of early stage can come public. But in general, private are a little bit earlier stage where risk is higher, feasibility is lower, but the return can also be higher because of the lower valuation to start with.

7:35The risk is probably higher too.

7:37Bihua Chen:The risk is higher in the sense of some early failure has not happened. And also the execution of management team is harder to tell in the very beginning. And later you can tell better. To do both, the synergy is really in the understanding of the disease and the biology and the tools that people use to create drug. Those expertise we can practice year after year and apply to both sides. How does your analysis change as a company moves from, let's say, private to public? And you shift from a scientific idea to a business that's judged daily by public markets and the price moves every day. Yeah, so in the private stage, it's really about doing a lot of scientific due diligence about whether this idea is good or not, and then follow the management execution to see if we are on the right track.

8:41Bihua Chen:The valuation is a little bit easier to manage because you can either say you're in or out. Once it becomes public, sometime we'll overshoot, sometime we'll undershoot. Now, undershoot is okay if you have capital, you just buy more. But when you get really exuberant, the most challenging part will be it's too high for this stage, but it's really low for eventual longer term price target. So you are faced with this dilemma of whether you should get out, come back, but can you really come back? So that happens around year 2000, 2020, during the COVID. it, everybody is enamored by biotech and a lot of companies get pushed to very high valuation, followed by a big crash.

9:38Bihua Chen:But if you look at the company that truly come up with a big drug, 2020 was not the peak of stock price, but it did follow a big dip. So those are the challenge of public market investing is that the sentiment can swing too big, and it's actually pretty hard to gauge when you need to get out. Because it's hard to predict where that price is going to go and how the sentiment may change. Yeah, yeah. As opposed to with private markets, you know what the valuation is. It doesn't shift around based on sentiment. Yeah. And the next round could shift around based on sentiment, but it's still a little bit more reasonable because both sides can negotiate.

10:21Bihua Chen:You know the players. Public market, you don't know the player. You don't know why it's up a lot. So when you first evaluate a new opportunity, where do you naturally start? Is it the patient, the science, the management team, or is it the market? It's always about the patient. So we will learn about the disease, how patients are treated currently, what an ideal product profile will be. And then the next thing will be the scientific hypothesis behind the new drug. We want to go for the hypothesis that's not too speculative. So the most proven hypothesis will be human genetics. So if you know a gene missing will cause a specific disease and you can replace the gene, that hypothesis is very strong.

11:19Bihua Chen:Another hypothesis that's strong, not as strong as the inheritable genetics, will be, say, cancer genetics. There are cancer which become cancer because it has one gene mutated in a specific way. And those are pretty strong hypotheses. And then there's hypotheses like inflammation of all the cytokines that are amplifier of the inflammation, which one people think are the key ones. There you could really go wrong. And that's how drug can fail. But sometimes people do grab the right one. Going back to my earlier comment of competition nowadays, if you prove one cytokine is important, many companies will go make a drug against this.

12:16Bihua Chen:So because biotech has grown so much as an industry, there's so much capital chasing it. We have like thousands of biotech companies now that has become really competitive. I know you've emphasized the importance of an unmet patient need. How do you determine when a problem is truly significant enough to support a great company rather than just an interesting experiment? Yeah, so it's either the quantity of life or quality of life. So in cancer, we hear breakthrough all the time, but one metric people use is overall survival. Before we know that, it's progression-free survival, meaning you survive without cancer progressing on you.

13:08Bihua Chen:In a lot of cancer, it's still very short. It's a year or two years. But we know some cancer have gotten to over 20 years. So we know where the ceiling is and we know where the current status of the drug is. So we want to get into feel where we think the new drug can move needle in a big way. So for example, lung cancer, right? Lung cancer has many different mutations. Some mutations such as ALK actually have a drug now that patients don't progress for seven years. So that's the best. And then there are cancers such as EGFR-driven non-small cell lung cancer. The progression-free survival is only a year and a half.

14:01Bihua Chen:So we want to invest in drugs that can move it to, say, two years or three years. So that's cancer. If it's autoimmune disease, let's say psoriasis, in the olden days, people are just happy if the skin area that's covered by psoriasis plaque clear by 30%. But now the standard has moved to 100%. If you have a drug that can clear 100 % in 30 % of patients, it's a great drug. But maybe one day we'll have a drug that clear in 50 % of patients. So each disease, you look at what the symptom is and how that affects the quality of life and see what current drug can do and what the new drug can do. So once you identify a meaningful problem, what tells you a company's technology is not just clever, but actually the right scientific solution?

15:07Bihua Chen:Yeah, so hopefully you are finding something that has a real causal effect, not just a correlation. And that's where the majority of scientific due diligence is. is actually to figure that out. And a hypothesis is a hypothesis. Every company will tell you something is causal, and most times it's not. We don't know for sure, so we play a probability game also. We want to make sure a theory is solid. So there are different experimental ways of testing how solid a thesis is at the cellular level, at the animal level, and we just kind of accumulate experience along the way to make our judgment call.

16:00Bihua Chen:And usually it's based on incomplete information. And I guess it is helpful to appreciate the data that says that most of the time it is not causal. Yeah, that's the thing. Science is a hypothesis that needs to be validated. So different labs can validate each other at the cellular level or animal level, but the ultimate validation is in human, right? So in human, you can fail based on biology theory is wrong or the technology did not deliver in solving that specific problem. So sometimes that's where it failed. If that's where it fails, you want to bet on the company that come with a sharper technology, a drug that's more potent, more specific.

16:53Bihua Chen:And those make the best project because you know it's an engineering problem, not a bet on whether the theory is correct or not. In biotech, so much value hinges on the development path. How do you think about the journey from promising science to an approved medicine that is causal? So the development path is very nuanced, and we must always remember the time and capital that take to de-risk the concept for a company to be able to raise money to go to the next step. So the better project, financially speaking, are the ones that improve the function because, and in a big way, because you can see before and after, right?

17:49Bihua Chen:But sometimes the drug is about slowing the progression of something bad. And sometimes progression is pretty slow. Those are very expensive projects in the beginning because slowing is something relative to the original trajectory of slowing. So that means you have to follow a patient longer. You may have to do a randomized placebo control trial to really make sure that slowing is not because you pick favorable patient. That doesn't mean we will not do the project that takes longer or more capital, but it's something to consider when you pick project. And I find a lot of biotech entrepreneurs don't think that way because they devoted their life towards certain area or certain molecules and that they just charge ahead.

18:48Bihua Chen:And later they find the road is really, really tough. So we haven't been, I have been biotech investor since 1998. I've watched so many companies, first in the public market, then in the private market. And now I've gotten to the point saying, okay, I cannot do this one. It's beyond me. Like we don't have enough capital to do that. I've heard you say that a scientific background is not necessary, but it is sufficient. What does that reveal about what really differentiates great investors in this space? It's actually not sufficient or necessary. I think scientific thinking is necessary, but doesn't necessarily come from a degree.

19:36Bihua Chen:The degree does not guarantee a person can think truly, rigorously, scientifically. So that's the distinction. And I find a lot of people get enamored by a person's degree or their pedigree or the lab they're being in. Knowledge is different from judgment. And a biotech investment very often is a judgment based on incomplete information. And that's the kind of the gut feeling part or the common sense or street smartness about it. And I think only time will tell who's really a great investor in biotech. It's a pretty exciting area, but it's full of traps. I see. Because the promise and the hope can blind you to what is a reasonable investment.

20:31Bihua Chen:Yes, totally. Yeah. And I can understand, you know, this industry attracts people who want to make a change and they want to invest and try to support the projects that could have meaningful impact. And so you could completely miss the more objective analysis. Yeah. Sometime I think you want to do good, you want the outcome to be good, and you're just not able to see things are not moving the right way. Or after it fails, people doing retrospective signal finding, do another trial, fail again, and then trying to do it again. So like to stay objective, I think that's difficult for every human. It is.

21:17We're in some ways hardwired not to be objective.

21:21Bihua Chen:Yeah. Yeah. Like we should all watch for our own biases and wishes. So in a field that's filled with highly credentialed experts that we just talked about, How do you consistently ask better questions or see things others might miss? How would you describe that? Yeah, it's really interesting. I've noticed over the years, some people are truly curious and some people have a checklist that they think will make them make money. So I think that's the biggest difference between people. And I think the checklist approach may work for the near term. but it may not work for the long term because it's not centered in developing a system to truly improve one's capability of getting better at predicting the outcome.

22:19And when you say checklist, you mean, you know, if it meets criteria A, B, C, and D, it's a good investment and kind of miss a lot of nuances?

22:27Bihua Chen:Yeah, or they have a profile. We see that in the public market a lot. Like in this specific data set, I need these thresholds to be met. But sometimes it's not met because the molecule is not good enough. It's some nuance in the clinical trial that make it not able to meet that, and they would just dump the stock and move on. Whereas in reality, it was imperfection of the early stage trials. So what we really trying to understand is going beyond the superficial numbers and really think about what has caused that, what's like a management's excuse and what is a true, just unforeseen circumstance that shouldn't be punished so severely.

23:28Bihua Chen:So that's why sometimes you see in the public market, stock goes from$20 to$2, and a few years later, it's$40, because that$20 to$2 was unjustified. And I guess it's difficult to know that in the moment, which is what can truly differentiate investors, the ones that can see that difference. Yeah, because there are probably eight of them,$20 to$2 is justified. Maybe two are not justified. You don't know which to unless you really have a whole system of how to look at these things. The odds that you're laying out demonstrate how challenging it can be to be a successful biotech investor. Yeah. The odds are against you.

24:14Bihua Chen:Basket approach doesn't work. And investing based on connection doesn't work. Based on university relationship doesn't work. based on which CEO was successful last time doesn't work. It's an interesting field. And biotech is known for extreme outcomes. You've highlighted some of those. So how do you identify the rare winners without being seduced by compelling narratives that may lack real scientific grounding? So real winners, by definition, has a little bit surprise element to it. They either surprise you in the speed or they surprise you with the probability or the magnitude of how good it is.

25:03Bihua Chen:So for cancer, the surprise of how good it is is what percentage of people end up responding to the therapy and the cancer progression is delayed by how long. Cancer drugs are charged on per month basis. So think about it. If you keep the patient on the drug for a year, you get probably$200 ,000. But if you keep that patient on for five years, you get a million dollars from that patient, right? So sometime a drug become really big because the efficacy was overwhelming. Another way, like say autoimmune disease, it'll be like how big a difference you make in the quality of life. Is it like a small improvement or the person pretty much now is normal?

26:00Bihua Chen:So it's all tied to the peak revenue of each drugs. So you either surprise by keeping the patient on the drug longer or apply to more patients. or it's so much value added, you can charge more. So there's a lot of ways to win as an investor. But those things are difficult to predict as you define them as surprises. Yeah, they are the nice upside surprises sometimes. So you've noted that this is not a sector where a rising tide can lift all boats. What are the most common ways investors fool themselves when evaluating exciting biotech ideas? The biggest way is just run with a theory that's unproven.

26:53Bihua Chen:For example, people say, oh, in autopsy, some of the Alzheimer's patient's brain has certain bacteria. That's the same as the bacteria that cause the dental plaque. Therefore, I could use antibiotics to treat Alzheimer's. I mean, they can really talk in a way for you to believe it, but other people may listen to it like, for some reason, I just don't think that could be causal. That could be just a correlation. I'm not going to go with that hypothesis, right? So the final judgment will be to run an adequately sized placebo control trial in Alzheimer's. And somebody did that, and it did not work.

27:38Bihua Chen:So that would be like just run for the wrong hypothesis. That sounds really good. Another way to lose money will be like, I know something is bad. I can inhibit it and therefore I will succeed. And then it fails. Well, why? Because there's something called potency. Like I see that in the lay press a lot. Like, let's say, oh, this herb can sharpen the memory, but, like, do we know how much is needed to really accomplish the job? Like, remember, resfester, which is this thing from the wine that's supposed to be anti-Asian, right? So you can say stuff like that, but the thing is, sometimes in the cell experiment, you just marinate with it.

28:34Bihua Chen:And in human, you cannot deliver enough into the blood, so you don't see the effect. So that's another way. It's just the technological shortfall that in the storytelling, you will not uncover. You have to really get into the data room and look at all the experimental data. And for example, there's another thing called protein binding of small molecules. So you can say, oh, my molecule is so potent. But if you get into human 99.999 % are bound by protein, then you don't have many molecules that really do its job. So all these like a tiny little thing can trip you off. Yeah, and it seems like as an investor, you have to come in with a highly skeptical perspective.

29:26Bihua Chen:That would be a good starting position. Yeah. But I've seen people very cynical and lose big opportunity too. They're like, there's no way that thing works because this guy doesn't look like a successful guy. Or this guy is from this country. Or like people sometimes miss something huge because of this bias too. So I guess you want a healthy dose of skepticism, but not over skepticism. Yeah. I think you need to be very skeptical, but you actually also need to believe in the beautiful belief in the powerful of technology. Like if you are so jaded, you don't believe any of that, then you wouldn't be able to make money either.