Da Wallach (2:48)

Sure. Well, basically making sense of biotech companies and valuing these companies requires processing a lot of very domain specific information. And that is still a type of work that only a small number of market participants are really expert at doing. And so the argument would be that the biotech hedge funds that basically drive most of the activity around these stocks are being paid by the market for the service that they're providing. And you know that that would be consistent with efficient markets. But, but still explain why there is money to be made and why money has been made by specialist firms. And we're talking here about the public market. The private market's a different story. There is probably even greater asymmetry to specialist knowledge.

Matt Zigler (3:46)

Okay, so just around the idea of a biotech company, full stop, introduce this bag of options framework, because I think this is really cool.

Da Wallach (3:54)

Sure. So the typical biotech company in its early stages is not selling any product commercially. It's a company that exists to try and get new drugs through a highly regulated development process and then ultimately launched commercially. And so we can distinguish between biotech companies that are in that phase where they're, they're not selling a product from biotech companies that are selling a product. And that latter group is going to be valued in a more traditional way based on future cash flows, the development stage. Biotech companies are really distinguished by the fact that there is a high degree of uncertainty that any of their products will get to the market. So let's just imagine a hypothetical biotech company. They've got three drugs that they want to bring to market, and each of those projects they started a year after the one before it. So they've got these three staggered projects. And each of those projects is going to move through the development life cycle. It's going to probably start in what we would call the preclinical phase, which basically means that scientists are researching that drug in the petri dish, so to speak, and then they're going to do animal experiments, unfortunately. But animal experiments are still a major part of how we try to figure out whether drugs are going to be safe and effective in humans. So that's all the preclinical phase of drug development. Any project in that stage of its life has a very, very low probability of making it to the finish line. And the finish line here would be, like I said, an FDA approval and then a commercial launch. So just to give you a general orientation, a drug at that stage might have some somewhere between a 5 and 10% chance of making it to the finish line. And then what will happen is the drug, if it has generated evidence that suggests it's worth spending money to take it further, will submit an application to the FDA or a different regulator in another country, and it will apply for the permission to, to start doing human clinical trials. The first human clinical trials, phase 1 trials, are typically gonna be focused on determining whether the drug is safe. And then the phase two and phase three trials are going to be focused on trying to figure out if the drug is actually effective. And a drug to get approved at the end of the day has to satisfy both of those criteria. It has to be proven safe and effective in the eyes of regulators. And if it satisfies those criteria, it will get a regulatory approval, and then the company will have permission to start selling it on the market. As a drug progresses through each of these phases, the probability goes up that it's going to cross the finish line. And so you can value any one of these companies, typically by basically doing a sum of the parts of the net present value of each of its programs. So this company that we're talking about that has three drugs, you're going to calculate the net present value of each of those projects. And in each case, you're both going to be discounting the potential future market for that program, and you're going to adjust it by the probability that those revenues will ever occur in the future. You're also going to be adjusting for the likelihood that they occur, the costs associated with developing that drug. So the valuation is going to be a sum of each program's net present value. That net present value is going to include the uncertain future revenues and the uncertain future costs that go along with that program.

Matt Zigler (8:09)

Okay, inside of this, how do you think about, for the Mobison nerds, base rates? Like, how do you, what do you tack this back to?

Da Wallach (8:17)

Yeah, well, we have a pretty long history of people trying to develop drugs. And so you can look at what the historical success rates have been. And when I talk about success rates, you can either think of that as the aggregate success rate. Say we've got a drug starting at a preclinical phase, and we're trying to figure out what's the chance that it gets across the finish line. That's going to require you to multiply the probability of it transitioning from each phase to the next through all of those phases I just described. So that's how you get, for a brand new concept, something like a 5 to 10% total probability of success. That would Be like your base rate. Now for the transition between each of these intermediary phases, you can figure out what base rates are based on drugs in the past that have faced that precipice and either made it across or not. So you would use base rates for as granular a part of the evolution of a project as you can. And your goal is to try and anchor your estimate of the likelihood that things succeed to what has been historical experience across different drugs. And of course, for any project, you're going to do a better job the more precise your reference class is. So, for example, drugs that are antibodies are going to have different base rates than drugs that are small molecules. And a lot of the art of biotech investing that specialists like us are engaged in comes down to figuring out what are the right base rates to use for a given situation. And then how might you adjust those base rate expectations depending on the specific facts of the drug in question, how

Matt Zigler (10:22)

much of that is the like the total addressable market for each of these drugs is.

Da Wallach (10:28)

So the, the total addressable market is basically how big the pot of gold is at the end of the rainbow. The probability of success estimate is what you are multiplying that market size by. So you're trying to fundamentally estimate two different things. One, how likely is this thing to get to the finish line? And two, if it gets to the finish line, how much money is it going to make? And the how much money is it going to make part is also quite subjective because you're going to need to figure out will this drug be the drug that doctors always choose to give patients, or will it only capture a certain market share for patients with that disease? And you also need to figure out what is Medicare or other insurance companies, what are they likely to pay for this drug? And that's going to be the outcome of a complex sort of set of strategic and negotiating sort of circumstances for each drug. So there are a ton of these variables that all have error bars around them. And the professional biotech investor's job is to try and have a view about each of these variables. And as a result of those views, figure out what you think the company should be worth today based on all the uncertainty that surrounds it.

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Matt Zigler (13:04)

One time only offer. Okay, so between the bag of options, between all the different layers, calculating how we get to towards the tam, if that we even get to that payoff. The last four years you've said have not been so kind to this space. Could you sort of walk through what, why has everybody been down on this? Why has this not gotten a lot of attention or focus? And why does the market environment kind of create opportunities and cycles here?

Da Wallach (13:31)

Sure. Well, I'm going to talk about the public market here and we can get into the private market if you want to. But as a rough rule of thumb, the private market sort of follows the public market with a lag in terms of what's going on, what its climate is. In the past few years, we had this kind of coincidence of negative developments for biotech. So interest rates went up. That's a major headwind to these companies because, I mean, you know, this isn't, this isn't totally true, but I'm going to give you kind of rough heuristics. The story people tell that has some truth to it is that the valuations of these companies, calculated in the manner that we talked about, are heavily dependent upon cash flows that are in many cases 8 to 10 years away in the future. And so when the discount rate changes, these companies see their valuations fluctuate in a very sensitive way to those discount rates because they're not making any money today. Therefore, all of their value is really contingent upon this big bolus of cash way out in the future. So that's kind of one fact that worked against Biotech starting in 21:22. The other is that within the public markets, biotech is competing with all the other risky sectors for investor interest. And so I think what we saw was that for a couple of years there, um, most of the hedge funds and a lot of bigger generalist allocators of capital decided that biotech was just not an area they wanted to be in. They wanted to do other stuff during that period. And in particular, sort of big tech and the AI narrative created a competitor to biotech for that risk capital. So money flowed out of the biotech sector into other parts of the market, and that just created a massive headwind for all of these companies. So during that period, you had going on what typically sort of drives this sector, which is you had companies doing clinical trials, sometimes getting acquired by large pharma companies. These are the things that drive returns. But those returns were occurring against a backdrop of money being sucked out of the sector. And so it was like all the prices were going down together. And only if you were extremely careful and specific with your bets would you find these little instances where you could make money. And of course, what we hope for the rest of the time in more normal environments is that there should be hopefully kind of like a steady state risk premium of some kind to investing in biotech. In other words, you would hope that it's sort of a good place to always have some money, and then if you're good, you would generate returns, you know, far in excess of that by doing the kind of specialist investing that we talked about. On the other hand, you know, this is, as we're describing it, a market that goes through cycles. And so, you know, it was just definitively a bad place to be for the past few years. And we came out of that, starting about halfway through 2025, there was this massive resurgence of risky biotech investing capital flowing back into the sector. And you saw returns even in the sort of passive biotech indexes of 80, 90, 100%.

Matt Zigler (17:27)

I want to talk about the last time that cycle turned. So I want to go back before four years. Can we just unpack what happened in and around the pandemic to the space? Because I think that's an important system and catalyst to set up sort of like where we are now.

Da Wallach (17:44)

Sure. So what I just walked you through was sort of the comedown from the sugar high of the pandemic. So when the pandemic occurred, of course, we all directly experienced how central biotech can be to everybody's life. You know, most people only discover this when something really bad happens to them, like they get cancer or they get neurodegenerative disease or heart disease, and then their eyes are opened to just how profound this sector is and its contributions to everyone's lives are. But for most of us, we're going through life day to day, hopefully healthy, and you just sort of don't think about what's happening in biotech world. Well, obviously Covid was a rude awakening because, you know, at the outset people were just desperate for a solution. The biotech industry ended up providing a pretty decent solution. But then that of course became itself highly contested with the MRNA vaccines. And what we did see was that at the beginning, just enthusiasm was out of control because everyone realized, whoa, there's going to be a lot of money made around this industry helping us get out of the pandemic. And so valuations went way up, enthusiasm was on high. And then as I described it, you sort of came off this sugar high. Interest rates went up, the world kind of reverted to normalcy. The air was let out of the balloon of the companies that had provided the vaccines, which, you know, at a certain point in time, the assumption was now the MRNA companies are going to be producing a blockbuster product that everyone's getting every six months or every year. Of course, sentiment turned against those vaccines in a big way. And so people's expectations there were changed. And so now we're just, you know, as I mentioned, we've just come out of this big rut that, that, that drove us into.

Matt Zigler (19:48)

Is there any inkling of. And by, by all means, it's nowhere near a pandemic type of awareness on the space. Is some of the stuff that's going on with AI helping draw money back or sort of like as you paired it, biotech and tech sometimes get lumped into the same growth investor attraction. Is there anything that we could see around AI that could be the same size or scale of what we saw in the pandemic?

Da Wallach (20:16)

Well, I would say by and large they're competing with each other for capital. Meaning both early stage tech and biotech are viewed by public market investors as highly risky places to deploy. You know, this is when we're not talking about investing in the big, big companies. Right. So investing in Alphabet's a totally different story from investing in a $3 billion market cap AI company. Right. And that's what more of these clinical stage biotechs look like. You know, one to $10 billion valuations. There are hundreds of these companies and that as a category is viewed as one place where you could place some risky bets if you wanted to. So I think the AI narrative has continued to out compete biotech in terms of the argument that it's made to risk seeking public investors. There certainly is a narrative within biotech around what AI may do to the industry. And I would say, just as with every subsector where there's an AI story, there are people chasing that. It's not a thesis that we have leaned into particularly heavily. But I can definitely, you know, articulate to you the arguments that people would make for, you know, how transformative AI is going to be within biotech.

Matt Zigler (21:42)

I bring this up because this is one of the places that I'm hearing it and it's your work that helps sort of make, make me think of this regularly in this way. The generalist level appreciation for biotech is probably, maybe you tell me if it's more a key determining factor in flows. And when I hear generalist growth investors talking about what AI can bring industries and directly referencing biotech over and over and over again, here's what's going to help with these things. I go, this isn't just a story, this is a flow story. What's happening there. And then maybe you could lay down how they're painting this.

Da Wallach (22:19)

Yeah, well, I, I don't, I'm not sure whether that story has actually driven flows into biotech companies. It has certainly been part of the sales pitch that AI companies make to attract capital to themselves. Right. And so just as one example in Jensen from Nvidia's presentations, if you watch them, there's almost always a major call out to biotech and how transformative the GPUs are already proving in various parts of the biotech sector. The large pharmaceutical companies, just like all the large companies in different sectors, are also making this case to investors that, you know, we're investing heavily in AI. We're going to deploy our capital to kind of leveling up technologically. And so that also may be attracting some flows to the large pharma companies. But I think here it's also particularly clear that it's such a competitive industry that however much the large farmers have to retool, it's probably unlikely that any of them is going to have a durable competitive advantage as a result of AI, meaning multiple of them are all going to run at this in a similar way. And you know, that's probably going to do the same thing to their economics across the board, which hopefully, for the sake of patience, is going to be to increase the number of new drugs that we get and decrease the prices of drugs. That I hope is what happens. But that's going to play out over a 20 or 30 year time horizon. It's not something that's going to change overnight.

Matt Zigler (24:05)

Let's talk about the role that specialists play inside of the business, both as allocators and inside of these Companies. Because I feel like this is something that if this is your thing, this is kind of where you have to stay and where they have to figure out ways to keep you. How do you think about that? Specialist investors and allocators in particular first?

Da Wallach (24:26)

Sure. Well, the specialists in the public biotech markets are basically a number of hedge funds who almost exclusively do biotech. And there are, call it between 30 and 80 of those firms that matter, meaning they're managing, you know, a billion dollars or more, something like that. None of them is that massive. Right. So you don't see $150 billion biotech hedge funds, some of the best players in this space have remained, Even for a 20 or 30 year career, quite small. And I think part of why they've done that is because they are mainly trafficking in these small cap, low float stocks where it is very difficult to scale a strategy beyond a certain point. So it is a market that's very dominated by specialists. The specialists who do this for a living, know what they're doing by and large are quite skilled and they're paid by the market for that skill. And historically I would say the large allocators, be it the pension funds or the endowments and so forth, in most cases we'll have some allocation to the biotech public markets and in many cases allocations to the private biotech markets. This whole ecosystem is a kind of self reinforcing machine where you need the private market to create biotech companies that will go public. Going public in most cases is going to be where the returns are produced for the private investors. And then big pharma is the ultimate engine because the big public large cap pharma companies are ultimately who buys the companies that have gone public. Every once in a while a commercial stage public biotech company will decide not to sell. And so occasionally you will have an independent public biotech company that chooses to remain independent. And a few of those have grown to be quite large in their own right. Amgen would probably be the greatest example of this. But that's an old story, a decades old story. But Amgen, Vertex, Regeneron, those would be companies that are not large pharmas, but that have become quite large independent commercial stage companies because they didn't sell. But the, the day to day bread and butter of returns in this industry is that large pharma companies buy biotech companies often out of the public market. And that's where the returns come from for the public hedge funds, the specialists, and they recycle that capital back into the public market. And that's what enables new companies to ipo.

Matt Zigler (27:21)

So let's talk on the private side just for a second there.

Da Wallach (27:23)

Yeah.

Matt Zigler (27:23)

On the private side, does that mean the level of specialization is that much lower, smaller, tighter, like the only people trafficking in this space are extreme specialists.

Da Wallach (27:35)

You know, there are a few examples of firms that do tech and biotech, but they're few and far between. Most of the venture firms in biotech mainly just do biotech. There are some firms like ours that take a bit of a broader view than only investing in drugs. So as an example, we do drugs, which in the industry people call therapeutics. We also do diagnostics, we do research tools, we do medical devices. And we'll also look at opportunities in healthcare innovation more broadly. You know, companies that are doing something that might enhance the experience of going to the hospital or going to the pharmacy. But I would say the big concentrated players in our landscape mainly focus on drugs. And that's what they do. And they often, maybe even more than in tech, have a very hands on approach to almost building companies. So they're not quite venture foundries, but it's more like that than in the tech world where usually what a VC is doing is finding a company that some entrepreneur has already started that they've maybe already financed for a year or two and then they're just sort of piling onto that. Right. And jumping on that train. In biotech, it's much more common that the venture capital firms will be quite involved with these entrepreneurs from the very inception of a company.

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Da Wallach (29:21)

Steven. Because he's so evil. I do think he is misunderstood. You see everyone face consequences.

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Matt Zigler (29:41)

Inside of that, if they're that much more involved, that also is a big part of the differentiation, I feel like, between being a venture or angel tech investor and being in biotech specifically. Fair.

Da Wallach (29:54)

Yeah, I think so. Venture capital broadly is the closest thing you find in the investment world to entrepreneurship, meaning venture capitalists are close to the entrepreneur. They're often right there in the trenches from the early days. And obviously there's a high range in terms of how involved they are with building early Stage companies. I think biotech investors to my earlier points, are sort of on average more involved in early company building and financing than tech investors often are. But you know, it also depends on the entrepreneur. Some entrepreneurs are really self contained and you know, they know what they're doing and they're going to build something that's likely to be successful irrespective of who's on their cap table. And you know, you get some of that in biotech. But it is a very capital intensive type of company building and therefore the investors and the ability to create a financing story and the right investor syndicate from the early days can be extremely important, maybe more important than it is in intact.

Matt Zigler (31:11)

It kind of feels that way because you can't have the same type of generalist founder type come in and try to build one of these portfolios like they would at least need to surround themselves, it feels like with a different level of specialist to even want to enter this space and not just assume they're going to burn a lot of money.

Da Wallach (31:29)

I think that's true. That's certainly been my experience. I mean, I came into this from the sort of tech generalist venture mindset. And what I pretty quickly figured out was there's sort of a glide path for companies if they're built in the right way. The science obviously is what determines whether companies succeed and progress. But in a perfect world, you'd like to set these businesses up with the right investors, with the right kind of management team from the outset, such that if the science plays out the way that you hope it does, all the other risks have been mitigated. And I think part of why that's important is these companies, as we discussed, don't make money for a long time. So what you do get as time goes on is more and more data that reduces how risky investors would feel the bet is. Nevertheless, there is still a huge amount of narrative at play and the investors ultimately have to believe in the scientific story that the company is chasing. Whereas with say enterprise software company, within the first year or two, you've got all kinds of evidence as to whether or not it's working. You, you can talk to customers, you see revenues, you see what the retention rates are and what the lifetime value is. And so you can anchor and investment analysis to all these facts. In biotech there's still so much narrative that it becomes especially important that you have contextualized a project with all of the things that signal to the market that it's on the path to success.

Matt Zigler (33:30)

It's so interesting to think, too. And as a. Because as a private investor, that also cements. You kind of have to be there for a long time when nothing is happening.

Da Wallach (33:41)

Well, it looks like nothing's happening. And, you know, the job and, you know, everyone can be forgiven for feeling like, wow, nothing's happening. Because what is happening is a bunch of experiments, typically, that generate a lot of data that to the untrained eye, is very hard to make sense of. And, you know, that's where we get back to this point about why do specialists get paid in this field. Our job is to look at a body of evidence from mouse experiments and make an assessment as to whether those are convincing results. And, you know, if we're right about that, then we'll double down on an investment. If we're wrong about that, you know, we can make errors. Right. And if you don't know how to look at that information, you know, it's just a total coin toss.

Matt Zigler (34:32)

I say that partly in jest, in the sense of just because the price isn't moving doesn't mean it's the ultimate value investor epithet. It's the ultimate buffet look through earnings. It's the ultimate. Any of these cases where you go, there's things happening below the surface that price isn't communicating to you.

Da Wallach (34:49)

That's right.

Matt Zigler (34:49)

And the way that you packaged up the entire story around and the belief in what's going on that has to get built over time, like that can't be flighty in the generalist sense.

Da Wallach (35:01)

That's right.

Matt Zigler (35:02)

How did you come to understand that role? Moving from the tech space into the biotech space, where you saw how much longer it had to take for that narrative to sort of gel that you go, oh, this is the commitment. This is the way we look at progress, because it is a very different ecosystem.

Da Wallach (35:20)

Sure. You know, it took me several years of looking at these companies, and I'm, of course, still learning every day. It's a very deep. It's a very deep craft, I would say. Right. And people who have been investing in biotech for decades have, through that experience, learned a lot of lessons about the nuances of both the narrative side of this and the substantive side of it. And so all I can tell you is that both dimensions are really important. And I think, you know, that's something we can talk about more broadly in investing, this interplay between reality, facts, and narrative. But that combination and getting it right is absolutely integral to building these companies. You know, maybe more so than any other types of businesses I've ever looked at

Matt Zigler (36:15)

this is sort of AI adjacent on this question too. I want to talk about number one, I wonder with some of the generalists looking at this stuff too. It's like, well, AI can teach me how to do anything. So now I can read some of these clinical trials or I can read some of this stuff and maybe that helps draw them back in. But also I look at an industry like this and I wonder, do people feel like, like we're already drowning in ideas, there's more trials that we can come up with than we could ever imagine running. Is any of this stuff actually going to help get more of those ideas into test mode faster and farther? Is there any there there for AI as you see it for the portfolio companies?

Da Wallach (36:55)

Yeah, absolutely. I think we're all across the economy right now going through this experience of learning how to use these tools and finding ways that they can augment our abilities and our existing processes. And biotech's no different. So there is sort of a superficial story that you can tell again in any sector about AI is going to change everything. And that may over the long run be true. But what matters is what are the ways in which that transformation are investable. And when we look at biotech and we kind of explode out all of the things that need to happen to get a drug from idea to the market. We're no longer thinking of this as what does AI do to drug discovery writ large? We're thinking about a thousand component parts of the drug discovery life cycle. And we're asking is there anything AI can do for each of these that makes it better, faster, cheaper, more predictive? And in some of those areas the answer is going to be yes. In some of those areas, the answer is going to be no. What's exciting right now is everyone has a lot of incentive to do that analysis. And so you're starting to see companies that have a different character, they have more computer sciencey people in the mix and they are asking these questions in a very thoughtful way and you know, by their own report, some of them are harvesting major efficiency gains as a result. So you hear that when you listen to the pharmaceutical companies talk about what they're doing internally, you hear it when you talk to smaller startups and obviously they can be very creative and agile and. But I think it's an incremental thing and I think it only plays out over a longer time horizon.

Matt Zigler (39:12)

Any, any changes with that you could see coming with success rates or with will it actually ways it could actually help the clinical trial process or, or Even from the drug companies, looking downstream at companies they might want to acquire sooner.

Da Wallach (39:27)

Sure, yeah. You would hope that ultimately we will see success rates go up. And part of what circumscribes just the size of this sector. This is a sector I obviously believe is very important to civilization. And I wish that there were more money in it, meaning I wish more capital were flowing into it. But investors are simple. I mean, the money goes where the returns are. Right. And so what has sort of capped returns in this market, or at least what has capped the scale of returns has been these low probabilities of success. And there are a lot of different theories about why those success rates are so low. I'll just give you one, and I'm not endorsing it, but people have argued, for example, that, you know, basically we, we picked all the low hanging fruit over the past hundred years. Like all of the diseases that were easy to cure with a drug, we figured out how to address with a drug. What is that left us with? Well, all of the hardest, most stubborn diseases. You know, obviously the invention of penicillin was like a game changer for, for human history. But you know, we figured out how to, how to kill bacteria with a drug. And that was kind of a solved problem by and large. Well, now curing pancreatic cancer, you know, is a much more complicated problem. So it's like on the one hand, yeah, our tech keeps getting better and that should bring down our failure rate. But at the same time, everything we solve leaves us with harder things remaining to be solved, and that may work in the opposite direction. So anyways, at the end of it all, my hope is that better technology leads to higher rates of success, therefore to higher returns in this sector and therefore to more capital going into this sector. And that's the optimistic vision of the future.

Matt Zigler (41:42)

I'm curious in your own process, how something comes together, how an idea finds you, how you find an idea and private market. I want like actual day in the life type stuff. How does something even get on your radar? How does a conversation even start? How do you even start the process of. We might want to write a check and get involved with this. This idea?

Da Wallach (42:06)

Yeah, it's. Well, the first thing is, for all the reasons we just talked about, this is a capital constrained industry. In other words, you know, there are more good ideas looking for money than there is money looking for good ideas. And that favors folks in the business we're in because it means that, you know, without a lot of proactive effort, we hear from a ton of people who are trying to raise capital. So I often think about investing as sort of like offense and defense. I love playing offense, meaning I love reading a book that gives me a divergent idea. And then I go and I try to find companies in that space. And I, I feel like when I do that, I'm going to end up doing things that other investors won't do. And you can have an ability to differentiate. But also, we are just inundated with people trying to raise money. And there are a lot of these little biotech companies out there running around trying to scrounge up the cash that is required to take their thing to the next phase. And like going back to the beginning of our conversation, these companies have room for a lot of creativity in the weeds, but they're relatively templatized. I mean, if you've got a little concept for a new drug in the preclinical phase, it's very clear what your goal is. Like your goal is do a bunch of preclinical work. If it's good, raise enough money to get into your first clinical study. If that data is good, raise enough money to do your second clinical study and so forth. And so everyone kind of knows what they're trying to accomplish. And what we are attempting to assess are all of the variables that, that we've talked about earlier in the conversation. What do we think the probability of success is? How strong an idea do we believe this is? What is the scientific rationale for this mechanism of a drug potentially solving a big problem that patients have? And ultimately we want to understand how do physicians out there in the real world think about treating a particular set of patients? And can this company give them something innovative for their toolkit? That's going to be game changing for those doctors and for those patients. And at the end of it, all we want to do is back companies that we think have a high likelihood of succeeding in that way.

Matt Zigler (44:39)

How do you think about the portfolio construction element? You write a check, you write a check, you write a check. How does that come together?

Da Wallach (44:45)

Well, I think it's essential because you know, again, these are sort of low probability stories, meaning you know every individual company.

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Da Wallach (45:43)

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Da Wallach (46:25)

We hope they're all going to work and just zoom out to venture capital broadly. I mean, everyone knows that you're going to have a high failure rate. Fred Wilson from Union Square, you know, he as a rule of thumb would say a third of your companies are going to be zeros, a third of them are going to return capital, a third of them are going to make money, and all your returns are of course going to come from that last group. In biotech, the distribution of success and failure is probably a little bit different, I would say. My impression is that there are fewer thousand baggers, but people's hit rate is maybe a little bit higher in biotech, meaning specialist investors, because they are underwriting these companies in a pretty rigorous and probabilistic way from the beginning, are largely building a portfolio to overcome the intrinsic uncertainty that each project carries and that everyone appreciates each project carries. So the key is to size your bets appropriately and have enough of them that you overcome those low individual odds for each individual company. In our case as private Venture investors, we have sized our portfolio around 20, so sort of like 20 bets we have viewed as roughly the right balance between diversification and then having enough upside on any individual company.

Matt Zigler (48:03)

20 bets per fund, or is it

Da Wallach (48:05)

evergreen like 20 bets per fund.

Matt Zigler (48:07)

Okay, inside of that 20 bets per fund, which is. We all know the portfolio math, but how do you guys think about volatility variance? I guess define it first inside of a fund and then tell me how you think about it in portfolio construction.

Da Wallach (48:22)

Yeah, so I mean look, I'll be the first to admit private strategies in general are of course guilty of this, you know, so called volatility laundering, to use Cliff Asus's term. But you also have to distinguish what of that is, let's call it disingenuous versus inevitable.

Matt Zigler (48:45)

I want to give you the room to actually explain the practitioner version of it, not accuse you of volunt of volatility laundering for.

Da Wallach (48:52)

So you know, like the cliff Asness argument is you've got these private credit funds or these private equity firms and they own a bunch of companies that are doing hundreds of millions in revenue. And not only that, these investors who work at Blackstone or Paul or whatever, as Asnis has pointed out, these are some of the most sophisticated people at private market valuation that have ever existed. I mean if, if these guys don't know how to put a price today on one of these companies, nobody does. So if they are carrying portfolio companies at marks, valuation marks that are not tethered to the day to day business realities on the ground, they are effectively masking the volatility that their investors should assume is being realized by these portfolios. So it's like, you know, if you had a mutual fund that owned 20 public SaaS companies, of course every day you would see the prices go up and down for all those underlying companies. But in some private equity fund that owns a very comparable 20 software companies, the reporting to limited partners is going to suggest that basically there's no volatility. You know, they're all worth this month what they were worth last month or maybe a little bit more. So I think in, in that critique the suggestion is that these investment firms should be more honest about what their underlying holdings are worth and they should mark those much more dynamically so that their customers have a more honest picture of the true volatility of what they own. Now in our world, again, these are really hard businesses to price. A preclinical biotech company is in fact only priced when it raises money. I mean that is when you find out what the market thinks it's worth. And we, as an investor in a company, can do our best to kind of guesstimate that, but it's nothing like the precision that you would expect from Blackstone valuing some company that sells textbooks or whatever. And so the convention in our space with a private venture fund is that we, we basically mark companies when they raise capital. We view those as the pricing events and the price at which a company is able to sell new issuance is what we would mark our holding to. And, you know, we try to do it in as objective and transparent a way as we possibly can, and we try to capture the volatility that certainly does exist in our portfolio. But again, the resolution of that volatility is just inevitably masked by the fact that these companies don't price daily.

Matt Zigler (51:48)

Do you think about. How do you guys think about diversification when you're putting together a fund?

Da Wallach (51:54)

We, I think, largely view these risks as independent of each other. Certainly there are some shared risks. Like in the past few years, what we talked about. I mean, if all the money rushes out of the biotech sector, obviously that is a shared risk that our companies face. But we basically just try to have diversification across as many dimensions as we can. So, you know, in a portfolio of 20 companies, we're not going to have 20 Alzheimer's companies. We're going to have companies working in different disease areas. We're going to have companies working with different drug technologies, so different modalities, as people in our market would say. So small molecules, biologics, cell therapies, peptides, you know, different fundamental technologies. We have some regional diversification. You know, we have companies in the U.S. we have companies in Europe, we have a company in Australia. And, you know, it's no different from how I kind of think about my personal portfolio, which is like on that, you know, on the pie chart, I just want a lot of colors. You know, I want a lot of different colors and I don't want any one color to be too big where if. If it blew up, it would. It would destroy me. And it's the same thing here.

Matt Zigler (53:27)

Let's talk a little bit about China. Thinking about this on a global scale, you've had some really interesting stuff in this direction. We keep hearing China is going to be the big story. That's between the manufacturing, between the stuff, between what we learned about COVID and putting the. Some of the vaccines together. Give us an update. How are you thinking about China? Are you investing there? Are you avoiding what's the lay of the land.

Da Wallach (53:51)

Yeah, we're invested in one US based company that so far is going to do its clinical studies in China, its first human clinical studies, and there will probably be more of that across our portfolio. That is basically what has happened in the past year or two that everyone's talking about, which is that people have come to believe that China is a very good place to do clinical studies and in particular to do your first human clinical studies. There are a few reasons for this. One, excellent scientists available in China to do this work to a very large population and in many ways lower regulatory hurdles to enrolling patients in trials. So in biotech, time is money. When you're running a clinical trial, you really want it to happen as quickly as possible. The rate limiter there is often enrolling patients who qualify for the, for the trial enrollment criteria. And China's proven to be capable of recruiting and enrolling patients much more rapidly than here. So what this means for small biotech companies is if they're considering whether they do their first study in China or in Europe or the US it is now in many cases going to be more attractive to do it in China because it's going to be cheaper, faster and the quality is going to be very high.

Matt Zigler (55:16)

The historic issues we hear on all the other stuff in every other industry and everything else, you're not supposed to trust stuff in China. You're all these things. It doesn't feel like when you're talking about it that you think any of that applies. It's like a good US Company with the right partners has. It's just the population size, the access, all the things you just laid out. This is a clear and obvious thing to pursue.

Da Wallach (55:41)

Yeah, well, I don't think it's monolithic. Right. I mean, there are a lot of vendors, there are a lot of different vendors in China. There are a lot of different clinical trial sites in China. They're not all high quality and they're not all high quality here either, by the way, or in Europe. So the question is, if you're working with the cream of the crop in China, are you going to be getting something that's inferior to what you'd get in the US and the answer to that has become no. Now, I'm talking about this in a completely apolitical way. There are, of course, totally reasonable arguments to be had about the geopolitics of this and whether it's strategically risky for the United States to be yielding some of these activities to China. And regulators in the US are having a pretty Robust debate right now about whether or not we need to change some of the ways we do things to remain competitive for these parts of drug development. The other thing that US has really going for it is ethnic diversity. So for the FDA to approve drugs for large populations of patients, they want to see that the drug has been tested across a quite heterogeneous patient population. That's of course, much harder to come by in China. And it's one of the great benefits of doing work in the U.S. do

Matt Zigler (56:58)

you think in specifically for like U.S. biotech investors, public or private, how aware should they be of thinking about this globally versus thinking of this just inside

Da Wallach (57:11)

the U.S. i think it's imperative to think about it globally. And you know, it's not unlike being a manufacturer of some thing in the 80s in the US or whatever. Right? I mean, there's this massive outsourcing that is taking place to China. Companies that engage in it are probably going to have a significant cost advantage. So it's to any entrepreneur's peril to not be aware of what's going on and to consider the options. And, you know, same same goes for investors. So again, it's a, it's a, it's a moving target. Things may change, public policy may change. You know, we could get into a war with China. That would obviously change things. But the other point I would just make is that the large pharmaceutical companies are multinationals. And so, you know, in many cases they're based in Switzerland or something or in Japan or in the U.S. they're, they're going to go where the best drugs are originating. And they don't care, you know, whether a drug was invented in China or invented in Missouri. They want the best drugs. They want to buy them at the cheapest price they can get them at and they want the best clinical data that they can generate. And so it is a global industry and China is becoming increasingly important to that global marketplace.

Matt Zigler (58:32)

All right, let's zoom out. I'm gonna take you very, very high level some of our favorite closing questions. If there was one thing you could teach the average investor, and I'll. You decide which level you wanna answer this on. If you wanna think about it from the biotech place, go there. If you wanna just think about your own experience and now getting involved with the highly risky and speculative aspect of direct private investments and raising these funds. What's one lesson you teach the average investor?

Da Wallach (58:59)

I kind of pride myself on

Matt Zigler (59:05)

over

Da Wallach (59:05)

time trying to become a ambidextrous investor. And what I mean by that is that I often find that investment wisdom, commentary, conversation typically bifurcates people along, to put it crudely, sort of a value versus growth mindset. And my experience as an investor, largely in private markets, but increasingly in public markets, has been that different things work at different times and it is to one's detriment to join a particular ideology and define yourself by that ideology. And there's an interesting thing that kind of happens. I'm going to characterize it in a very vague way here, but if you just imagine this oscillation in the markets between value and growth, and I know those aren't perfect descriptions, but you know value, think Warren Buffett. I want to buy high quality stuff cheap and growth. I want to chase the latest exciting thing and buy things that are going up. You never know when it is going to switch in terms of what behavior, what strategy is dominating positive returns at a given moment. But it does switch back and forth. And the irony is that it can last in one regime for long enough that partisans on either side of this divide only ever become convinced that they're right. In other words, if you're the grumpy, crotchety value investor who hates how expensive Nvidia is for the past several years, it's like at some point things will revert and a bunch of people who own that are going to lose a bunch of money and you're going to take from that the lesson that you were right all along. Look at all those pigs getting slaughtered. I'm so smart. What idiots. But you've missed out on the returns for the decade or whatever, the two decades that they were making money. And so the duration of these cycles is such that very few investors actually learn that the right answer is to not be partisan. The right answer is to have an open mind and to try to understand in what environment you're presently living and to try to have the mental flexibility to apply the right toolkit to that particular environment. You can't choose what the market is wanting to do at any given moment. You can't choose where the world's going. You don't get to choose whether AI is overhyped or under hyped or whether it's going to deliver or not. And in fact, we don't know, nobody knows what's going to happen. So the best that you can ever do is try to unemotionally assess what the current conditions are and make a good judgment about how you should take risk in that environment. And that sort of flexibility and agnosticism is the thing I would recommend to myself and to all other investors.

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Matt Zigler (63:45)

Follow up to that then. What's one thing that one of your peers in this space would disagree with you on?

Da Wallach (63:55)

Hmm. Well, I am naturally inclined to systematizing things, and so I'm quite biased towards systematic and quantitative investing broadly. And I think particularly in biotech, most of my peers are biased against that because as we discussed, making sense of these companies and putting prices on them is a very delicate handicraft. And so anyone who lives and breathes that craft is very familiar with all the nuance that it entails and therefore is naturally predisposed to think that it will never be done by computers. And the same goes for venture capital. But when I just zoom out and look at what I believe is the long history of markets and professional investment strategies, what I see is that we are inevitably just going to keep getting more and more and more systematic over time. And if you look at active investing 10 years from now, it's going to have a higher share of quant than it had today. And obviously if you look today, it has a higher share of quant than it had 10 years ago. I think that is the big, you know, 50 to 100 year story of our industry. And so I always want to be on the side of more technology, more systemization, more science applied to investing. Of course, the risk of that is to overestimate our ability to be scientific in a domain that is non stationary, where markets change over time and when in fact the way that we adapt to changing markets further changes those markets. So there are a lot of reasons to be humble about systematic approaches, but if I had a kind of bias myself, it would be very much in favor of more and More systemization.

Matt Zigler (66:25)

Okay, I have one more bonus question for you before I let you go. And this is because I won't forgive myself if I don't ask you at least one music adjacent question. So if, if Venture biotech was a style of music, a scene, if you will take it wherever you want to go, like, is it K pop, is it CBGB's in the 70s? Is it hyper pop? Is it like.

Da Wallach (66:46)

That's a great question. It's. Well, you know, I, I don't want to pat ourselves on the back too much, but as we've talked about, I think it's highly skilled. Okay, so go on. So, so now we're sort of like, you know, jazz, math, rock, classical. It's. It's definitely, it's definitely not.

Matt Zigler (67:08)

Take that, Don Cab.

Da Wallach (67:10)

It's not cbg.

Matt Zigler (67:12)

Okay, we're not.

Da Wallach (67:13)

Right.

Matt Zigler (67:13)

Yeah.

Da Wallach (67:13)

So it's like. But I don't think it's. I think it's, I think it's like free jazz because there's a lot of. It's people who like risk, right? I mean, it's really, it's crazy. People who have a huge appetite for risk. It's people. This is another nice parallel. It's people who are not mainly in it for the money. That's one nice thing about being a biotech investor. Most of the people in biotech are not in it for the money because if, if that's what they cared about, they wouldn't be doing this. They'd be doing, they'd be doing something else in the investment world because it's not the best place to make money. And, and third, like as we're talking about, it's highly specialized, it's very craft oriented. And so I think it, I think it is filled with people who love the practice, they love the science. Right? And, and so that's another nice thing about this biotech environment is most of the people I'm interacting with on a daily basis, you know, they didn't start as investors, they started as PhDs or physicians. Their North Star in life is to try and help people who are suffering from unfortunate medical issues. And then what makes it so interesting is that the science itself is so fascinating and so endless.

Matt Zigler (68:45)

I'm taking that answer, I'm asking for comments on it. I want feedback from some people who are going to care about this, you know, who you are, or coming to debate this to a town near you and a podcast discussion panel. Da. If people want to find out more about you, read about your firm, bug you on the Internet. Where should we send them?

Da Wallach (69:01)

Sure. I'm on X. My handle is Da Wallach. D A W A L L A C H. I've got a website which is just Dawach.com I occasionally write blogs on Substack, which I. It's, you know, whatever their URL is./dawallock and and I'm dawallock.com so this was

Matt Zigler (69:23)

enormously educational, really fun to talk through on all these levels because there's just not a lot of you out there in the world doing this kind of thing. So thank you so much for the time. That's probably a good thing. You're watching Excess Returns. That's Da Wallach. I'm Matt Zigler. Like Comment subscribe all the things below. We are out. Thank you for tuning in to this episode.

Da Wallach (69:43)

If you found this discussion interesting and valuable, please subscribe on your favorite audio platform or on YouTube. You can also follow all the podcasts in the Excess returns network@excess returnspod.com. if you have any feedback or questions, you can contact us at Excess returnspod.

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Matt Zigler (70:02)

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Da Wallach (70:07)

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