Adam May 谈生物科技投资：$NKTR、$ABVX

Adam, how’s it going?

Going great. Glad to be here. Thanks for having me on.

I’m super excited. I’ll tell everyone why in a second, but before we get there, quick disclaimer. Remind everyone nothing on this podcast is investing advice. There’s a full disclaimer at the end of the podcast. There’s a legal disclaimer in the show notes. You can see that. Adam, I’m excited to have you on because I feel like I’m talking to a biotech celebrity, a FinTwit celebrity. I said you were coming on, and I don’t think I’ve ever gotten this many inbound questions from people asking about everything about you, everything about life, the meaning of life—just everything. But I’m really excited to dive into it today.

Well, that’s flattering, but I’m excited to get started, too.

You’ve got a little bit of a different background from most of the people I talk to. Maybe we could start with a couple of quick minutes on your background, what you do, and how you got into the biotech FinTwit scene.

By training and by profession, I’m a physician. I’m still practicing as a dermatologist, which I’ve only done for not quite a year, actually. By training, I’m an MD. I’ve been investing in small- to mid-cap biotech for almost a decade now, and I got interested in it back in the early medical-school days, when I realized that I might be able to learn something that could give me some edge or alpha in the markets.

With the few thousand dollars I could scrape together as a broke medical student, I started messing around in small-cap biotechs. From there, the path got a little more interesting. I had performed well on my own over the course of a few years during medical school, and I had a very close friend who was also joining me on some of these biotech investments and trades.

He was about to go out to Stanford Graduate School of Business, and I was about to go into residency after graduating medical school. He came to me and said, “Hey, I’m going to make a lot of connections with people out at Stanford. Do you want to start recording our thesis and our track record more formally, so that if I make some connections out west, we could maybe parlay that into something professional in the investing space?”

So we started to do that: document our thesis and track our performance. This was around 2020 and early 2021, and we looked great. We did great once we started tracking the formal record. It was a low-interest-rate environment, and biotech did fantastic. Over 18 months or so, we had returned about 1,400%—a lot of beta in there, maybe a little bit of alpha.

That got our foot in the door for a few more high-profile meetings than we probably would have expected, based on the kind of return we could show people. Eventually, we started talking to Alex Robertson from Tiger Management—Julian Robertson’s son, who now manages Tiger Management, which I’m sure a lot of your listeners know well.

Historically, Tiger was a hedge fund, and it eventually evolved into a fund of funds, so to speak, or really a fund that provides seed capital to people starting new hedge funds. We thought we were talking to Alex just for advice. We kept having meetings with him, and eventually he proposed to us, “Hey, I know you guys don’t want to quit. Adam, you don’t want to quit your residency, and Joe, you don’t want to quit your Stanford MBA. But we could give you a couple million dollars, and you could raise a friends-and-family round and start running something somewhat formal but also somewhat informal—basically, part-time—a very small hedge fund in small-cap biotech.”

That’s what we did. It was called Rare Life Capital. We got up to an AUM of maybe $12 million, so pretty small in the grand scheme of things. I basically ran that in what would be my spare time as a medical resident: 80-hour weeks in the hospital during the peak of the COVID pandemic, coming home from a 24-hour shift and trying to diligence biotech stocks.

Anybody who followed the biotech market over that period would know that we launched in the second quarter of 2021, right at the peak. We had ridden the peak and gotten that momentum to launch, and then the XBI, which was the main index that, at that time, tracked our portfolio, drew down about 55% peak to trough over the next roughly 1 year.

We closed down the fund at the 1-year anniversary of its launch with almost the same 50% drawdown as the index. We finished our education, and since then I’ve done a little bit of consulting for some small biotech hedge funds and basically just invested my own capital. In the last few years, things have gone really well on that front, so it’s something I’ll probably be doing full-time here soon.

That’s a fascinating background. I’m really glad I asked, because I only know you through Twitter, and I knew you were practicing as a derm and all that sort of stuff. As soon as you said you launched in the second quarter of 2021, I thought, “Oh, I know what’s coming next: the real bear market.”

I have so many questions for you, and we’ll talk about the successes, failures, and current stuff. But let me ask you one question. I think you’re being a little humble when you say the 1,400% or 1,500% from 2020 to 2021 was a lot of beta. But it’s not lost on me exactly what you said.

The XBI—I’ve had some big wins, and I know you’ve had some huge wins in the biotech space since the bottom in March and April of 2025, when RFK was coming in and people were freaking out, and then the tariffs hit and everything just blew up. How much do you think alpha in the biotech space, in general, is driven by the wave of beta starting to go up?

Then the big pharmas, Merck and Pfizer, start throwing out big checks to buy things, and everything’s going up, versus the idea that it should technically be kind of uncorrelated? Even when everything’s drawing down, your ABVX reports good numbers and the stock should go up no matter what. How do you think about that? Am I just riding hyper-beta versus the alpha of beta?

If you zoom way out, yes, this is probably the most, if not one of the most, uncorrelated sectors to the broader market. That’s for sure. Honestly, biotech would probably be pretty pleased with a recession, because we get interest-rate cuts and interest rates go down.

Small-cap biotech is often doing the inverse of what the broader markets do. But I would put a caveat on that, because it swings so far in each direction with sentiment that, even when things are looking really bad, very obviously positive readouts can still lead to negative stock moves.

When I say “readout,” I mean a data readout for a company, like a drug showing clinical-trial data. I can think of examples in the last year, as you said, in March and April 2025, where things were very clearly positive and stocks would go down 30% to 40% just because there was a liquidity event.

The inverse is also true: an obvious scam can put out a phony press release whenever there’s ZIRP in the background and go up 300% in 1 day. There is a lot of beta in this industry, for sure.

Okay. Let me ask you about edge. Edge in the meta-game of investing is something I think about a lot. You’ve done great work, and I want to talk especially about the ABVX stuff because I thought that was so unique last year, but I just want to ask you about it.

You said something about going into an obviously very positive readout, right? I always think about that because this is competitive. Even if you’re talking about a $100 million biotech, if it has a positive readout, these things can go up 10 or 15x. Anyone can change their life on this type of stuff. They’re very competitive.

I’ll hear people say, “This readout is a slam dunk,” and I’ll think, “Well, yeah, but the market’s competitive.” If a readout is 95% likely to be positive, these are priced accordingly. So how do you think about the edge in the meta-game? I’d love to hear all of your thoughts on that.

The other thing I think about is UniQure. I’ve got no huge dog in that fight, but I know some people would accuse—and I’m sure the FDA would accuse—UniQure of presenting their data in a very favorable light. When you’re reading this, you’re often reading how management is presenting the data to you and painting it in the best light. So you’re thinking, “It’s 95%,” but that’s coming from management’s side. I threw a lot out there, but I’d just love to get your thoughts on that.

To go toward the question of alpha and edge, I think that if you think you have a read on something being positive or negative—if you’re short, you’ve got to have an equally good explanation for what other people are missing about that. A lot of that comes from perhaps talking to people and understanding what the misconceptions or concerns are.

ABVX is the example that you mentioned. I had a lot of medical data that I thought indicated it was going to be a successful drug readout, but a lot of people were not interested in the stock for a few reasons, and I thought none of them really mattered in the grand scheme.

The biggest one was that people did not know—and, frankly, still do not know—what the true mechanism of action of that drug was or is. Fundamental biotech investors want to know how a drug works. They want to know, down to the very nitty-gritty, what this drug does, what it’s hitting in the body, and how that’s going to make it work.

This drug, obefazimod, from Abivax, still doesn’t really have a mechanism of action that we truly understand. What we knew, or what I thought I could tell, was that it was going to work in ulcerative colitis. But everybody I talked to was like, “Yeah, that’s some weird drug from this tiny French company.” They weren’t even listed in the U.S.; they were trading on Euronext for the longest time.

People wrote off that drug because they didn’t know how it worked. For this 1 example of a drug with a mysterious mechanism of action that ended up working, we can give you 100 others where shady management teams were doing a hand-waving motion to tell you how the drug worked, and those did not turn out. So, in some ways, it’s fair.

But in this particular example, I had enough data to tell me that the drug was actually working. I didn’t care about the mechanism. I didn’t care about the main concern that most people had against it, which prevented them from investing in it.

So there are really 2 parts to finding alpha in biotech. You have to think that you’ve figured out what’s going to happen in a trial, or at least approximate what you think is going to happen in a trial. And you have to have a reason to explain why other people don’t think that.

I guess zooming out is kind of a simplistic thing, but I do think it’s overlooked sometimes. No, it’s fascinating, because the other one I kind of know you from is Nektar Therapeutics, NKTR, which I’m sure we’ll talk about.

I remember I read your work and a few other people’s work. There, the answer was, “Hey, it was Eli Lilly who was partnered with them,” right? So you would write bullishly, and I’d think, “Man, I think he’s got a good read on this,” but Eli Lilly is a half a hundred million dollar company, and they handed the drug back.

Yeah. Eli Lilly was partnered with them, and they handed the drug back and said, “This trial doesn’t work.”

A bit different. Yeah, yeah.

That’s an even more convoluted story as to why it was so overlooked. There are a few different reasons, but we can get into that if it’s of interest.

But it’s all of interest. On ABVX, what do you think we don’t know? I remember people saying—and I had some other friends who had done work on this, too—why don’t we know the mechanism of action there?

That’s a good question. It’s a repurposed drug, so it was discovered quite a long time ago and was originally studied in HIV. It was studied in AIDS patients a long time ago.

The purported mechanism of action is that it enhances what’s called a microRNA. miR-124 is the name of it. It makes your body produce more of this anti-inflammatory molecule, basically. That’s the thought process.

But that was put forth as the hypothesis, and perhaps somewhat shoddily validated as the mechanism of action, by a very small Parisian biotech company. If that molecule had been brought forth in a higher-profile pharma pipeline, maybe the results would have been different.

They had a drug and some signs that it was doing something in the body. They picked something. That’s the way I think it most likely played out: you can give somebody a molecule, measure 100 different things, see what goes up and see what goes down. They saw that this one thing, miR-124, went up and said, “Okay, that’s what this drug does. That’s how it works.”

It’s hard to actually run studies to validate what these teeny-tiny molecules are doing inside the human body. To really prove exactly what it does is difficult. In medicine, historically, there are a lot of drugs that we don’t actually know how they work. Most of those are drugs that we’ve been using for 50 or 60 years.

In the modern era, it’s atypical to have a drug where you have not completely hashed out what it does. But it just goes to show that it is difficult to find that out. There are more recent hypotheses that are fairly well validated about how it might be working.

Basically, what the company says the drug does, a lot of investors don’t think that’s what it does. But what matters is that it works.

It’s just everything you’re saying. We’re living in the age of AI taking over and everything. I know people are really worried about whether it’s CROs or on-the-market drugs, and people are really worried about AI discovering drugs, or however you want to do it.

Then you talk to people who’ve actually done drug discovery, and they’re like, “Yeah, I think we’re going to be okay for another 20 or 30 years.”

They will laugh out loud at you if you tell them that AI is going to replace drug discovery. It can augment it, for sure, but you’ve got to put a molecule in a human body. You have to put a molecule in thousands of human bodies to know what it actually does.

Last thing, and then maybe we’ll hop into Nektar or ABVX, whichever you want to start with. Sorry, but you described it—it sounds like you’re looking for companies with drugs that have some hair on them, where investors are debating whether the drug works. You can get an edge by figuring out whether the drug works or not.

How are you sourcing them? You’re practicing derm, you’ve got a full-time job, and I know you’re at the center of venture. How do you source these, and how do you read through the material and say, “Hey, I’ve got an edge here,” or, “I’ve got a route to finding an edge here”? You’ve got some background as a doctor, but how do you read through it and figure that out?

It’s got to be high-throughput. For me, that’s the only way. I run a very concentrated portfolio, so at any given time I may have only 5 or maybe 10 names. But to get to that, I’ve probably looked at several hundred biotech companies.

Some of that can be pretty cursory. I can look at a company whose ticker I’ve seen, look at the corporate presentation for 15 minutes, and say, “Oh, that’s relatively fairly valued.”

Out of looking through 300 names, you might find 50 where, if what the corporate presentation is telling you is legitimate, the company could be worth a lot more than it is right now. Then the diligence gets to a second, third, or fourth round, and eventually you narrow it down to just a few that you actually spend a lot of time on.

At that point, what you’re usually doing is looking at other people’s data. That’s a mistake that probably a lot of people make: they rely on what comes from a company to try to diligence a biotech.

If you’re really going to go long something or really get high conviction in aggregate, you need to spend more time diligencing other drugs, other competitors, and other parts of the market than the drug that the company is developing or the data that they’ve developed for that drug.

There’s a lot of competition, and you can’t expect the company, unfortunately, to give you an unbiased view of what their competition actually looks like.

So I scan for names regularly, even just on X. I have a very concentrated follow list on X consisting almost exclusively of small-cap biotech investors, so I see names come up there a lot. I keep a running list of names in the sector that I’ll go back to and run through quickly every so often, maybe quarterly. Sell-side puts out a lot of catalyst calendars, too, so when trial readouts are happening each quarter, you can have a good idea: “Oh, I need to catch back up on XYZ because they’re going to have data soon.” That’s the 20,000-foot view of the process, as well as how names come up, basically.

No, it’s just because I’m a complete mathlete when it comes to science. Most of the time when I’m doing biotech, I’m just like, “Hey, this drug failed, but there’s $10 of cash on the balance sheet and it’s trading at $5. Let’s go liquidate this thing.” But I love following it and learning more about it.

Okay. Actually, one more, and then we’ll hit Nektar and Abivax. This will be a nice transition, and we can talk about the whole story and everything, but I do want to ask you about this. You were long these before both of them reported great results, and the stocks have gone up a lot. I believe you can disclose that you’re still long them.

When I see that, I say, “Hey, he was long on the thesis that—I’m just going to say simply—the Phase 3 worked, right?” He was long on the thesis that Phase 3 worked; Phase 3 worked, and now he’s still long them.

So I guess, how do you think about it when you’re running this concentrated portfolio and you were long on a thesis that Phase 3 worked, it worked, and you’re still holding it? Because now you’re playing a different game. For Abivax, anyone who follows biotech knows that people are waiting for maintenance data in June or July, or whenever, and then they think the company’s going to sell, right? But it is very much a different game. So how do you think about morphing that position?

I think that, for me, having a small, concentrated portfolio means that I don’t want everything in there to be an impending catalyst all the time. I need some stuff that’s post-data and still mispriced, or sometimes a commercial name—like a drug that is launching—where I think either the market has not appreciated how well the launch is going, or I think the launch of the drug is going to go better than the market thinks. The most high-profile stuff is always going to be the thing that people are interested in: “Hey, there’s a clinical trial readout coming up. The stock’s going to be down 90% or up 500%.” But you don’t want 100% of your portfolio to be in names like that.

So when a stock graduates from the unvalidated $100 million market-cap phase into a $500 million validated phase, that’s not necessarily a reason for me to ditch it. Obviously, there are tax considerations and things like that that matter for the bottom line, but part of it is keeping that balance of an impending catalyst with huge upside and downside mixed with some more moderate stuff that is validated. It should not crash. ABBVX is never going to zero, whereas my catalyst longs could.

But the other thing is, especially recently in biotech, a lot of people probably do not appreciate how absolutely bombed out small-cap biotech was this time last year. I mean, absolutely biblical levels. I did a post on it: The index was down more than the S&P, and the financial indexes were at levels seen in the Great Financial Crisis. It was so bombed out. You were buying these things for 50% of cash, and this is why I got so interested.

It didn’t even matter if the science worked. With hindsight being 20/20, it was better to buy ones with good, hot science that were trading at 80% of cash than the shittiest ones that were trading at 50% of cash. It all kind of worked, but I wish I’d been a little bit higher quality there.

I can talk a long time about how bombed out it was, but we’re talking about more than a decade’s worth of negative returns as of one year ago today. Just absurd levels of a crash during a secular bull market otherwise. So that’s an aside. My point there was to say the sector got so bombed out that you could have good data like Nektar or transformatively amazing data like Abivax had, and the stock would go up 500%, which it did.

You can sit there and say, “Wait, this should double again. It’s very obviously not up enough, basically.” What was the cause of that? Was it that the sector was so weak? Was it that the specialist money had shrunk so much because some specialist biotech funds had been forced to close due to redemptions during that time span? Whatever that inefficiency was, it was very obvious to me that even after the rise on those positive readouts for both Nektar and Abivax, they had not appreciated even remotely enough.

Nektar traded to about $25 a share after the positive readout, and now it’s at $75. That was one year ago, or not even a year ago. Abivax was in the low $60s on the first day or two, if I remember correctly, and today it’s around $120. So you have a 3x for Nektar and a 2x for Abivax, and I was just sitting on the stuff that was up 2 or 3-fold already. The opportunity was there, as well as that diverse portfolio.

Nektar had positive maintenance data since then, and Abivax had 15 different articles from French newspapers saying that it was going to get sold to basically every big pharma at this point. So, yeah, that has not hurt.

Let’s transition to Nektar. We can talk about it from here, and we can talk about it historically. I’d love to talk about just how you got involved in Nektar and what you see in the story from here.

Everybody in the biotech space has been involved with Nektar in some way over the course of its lifespan. It’s been around for decades. It was really high-profile maybe 8 years ago or so when they had a big cancer drug that got partnered with Bristol Myers Squibb, and that failed, and a bunch of other drugs for Nektar failed. So it has had this really bad reputation, actually, due to serial failures of its drug candidates.

The drug that I was invested in and am invested in is called rezpeg for short. It’s a drug to treat eczema—atopic dermatitis—which is one of the biggest indications in the immunology field in medicine. It probably is going to be a $40 billion market in the next few years. Huge market.

Like you had mentioned earlier, Nektar had partnered this drug, rezpeg, with Eli Lilly, a huge pharmaceutical company, to develop it in a few conditions: lupus, psoriasis, and atopic dermatitis, or eczema. Several years ago, Lilly presented data from the eczema trial, and it looked awful. It looked like it maybe did something, but the data were not competitive at all with what was on the market. So it looked dead, and Nektar stock basically crashed on that data.

Almost a year later, Eli Lilly still had not forfeited rights to this drug. Nektar demanded it back and issued a press release saying that Eli Lilly had botched the data analysis, basically.

Yep. The correct analysis showed that the drug was actually much more active than Eli Lilly had said—enough to actually be competitive.

We could get into the nitty-gritty of what the response criteria are and what the numbers are. I’d put it this way: The name of the endpoint is the easy 75, and the delta versus placebo—how many more patients achieve that response versus placebo—is what really matters. The benchmark in the market was probably about 30%.

Let’s just say that Nektar wanted that 30% response delta mark. The botched data that Eli Lilly had presented showed that it was at 9%. Awful. You could never take that drug to market. The reanalysis showed low 20s, which is actually competitive for what this drug is meant to do, which is be a second-line therapy for people who don’t succeed with what’s available to them already.

A lot of people just didn’t believe them, but I knew how that endpoint was calculated. That’s what I do in dermatology, and I knew that what Nektar was saying was correct. A lot of investors, I think, don’t believe them, maybe because of the reputation, or just didn’t believe that Eli Lilly could have messed that up so badly.

I did not believe it. I was like, “There’s just no way this giant company with the potential billion-dollar-plus drug could botch the data this badly.” I just couldn’t believe that it could have happened.

And eventually, you could dig up some public legal documents that showed that this was an undisputed fact of the lawsuit they’re engaged in now. I left that out, but Nektar is suing Lilly over this, understandably, claiming damages for losing a couple of years of development time for this drug.

You actually could know that. I still talk to a lot of investors from back then, and they were like, “Nah, this is bogus.” But the legal documents literally said that Eli Lilly did not dispute that the data set was misanalyzed.

So that is one point of dispersion from what the market believed, and I’m like, “This is definitely legit,” even though the market doesn’t think so. Another thing was that the market probably didn’t think there was a need for this drug because there’s a very famous drug called Dupixent, which is a huge drug in atopic dermatitis, and it has this really great image.

People basically had the perception that Dupixent is good enough and we don’t need other drugs for eczema. But that’s absolutely not the case, and that’s something that I could see as a dermatologist because I see it all the time.

Again, though, you could look at the clinical trial data and see that only about half of patients respond to Dupixent in the first place. Only about 50% of the patients who enrolled in those trials ever responded to it. But everybody you talk to would say, “Oh, Dupixent’s great. There’s no need.” Well, half of the market fails the drug that everybody’s using. So what does the other half of the market do?

Can I ask you a dumb question? I drool out of my mouth when I look at science, but I follow a lot of this, especially the cancer stuff. I’ll see the cancer stuff, and they’ll be like, “35% of the people who we put on this drug responded,” and they’ll be incredible. You just mentioned Dupixent: 50% of people. Why doesn’t it work a lot more?

I get that everybody’s biology is different, but it seems weird to me. Again, I’m just a dum-dum, but you put a radioactive chemical into someone’s bloodstream, and only 35% of them respond. Dupixent is a coin flip. Why doesn’t it work a lot more?

Yeah, well, if you really boil it down, it’s hard to say, but I think that we grouped clusters of different diseases into 1 kind of name-brand disease, like atopic dermatitis.

Got you.

Really, there are probably a bunch of different pathways that drive it, which is why big immunosuppressant drugs like JAK inhibitors—dangerous immune-suppressing drugs—work really well for these conditions. It’s actually probably 20 different conditions that we put under this umbrella of atopic dermatitis.

Makes total sense, yep.

Yeah, so people didn’t believe the data were real, and people didn’t believe there was a need. I could see that the reanalysis was real. I could see that there absolutely was a need from my experience as a dermatologist, and a huge one at that.

I could see that there’s this other drug called nemolizumab that has a different mechanism of action from Dupixent, but is very inefficacious. People are using it because we need another mechanism of action. I could see that happening.

When I said that Nektar’s 9% delta was not anywhere close to being good enough, nemolizumab’s is 13%, versus Dupixent’s a little over 30%. But that’s going to be almost a $4 billion-per-year peak drug because there’s just nothing else, other than unsafe immunosuppressive drugs, that we can use if you’re part of the half of the population that fails the first-line treatment of Dupixent or this other medication called Adbry. But they have the same mechanism of action, so they get lumped together.

Then there was a third thing that I felt like I had discovered—something that probably most people wouldn’t realize. The phase 1 data that we’re referring to, the data that Lilly initially misanalyzed and that went from that 9% response level to the low 20s when it was analyzed properly, was a 12-week readout. They treated the patients for 12 weeks and looked at the responses at 12 weeks.

You could look at this 1 slide in Nektar’s corporate deck, and they weren’t advertising this at all. I still don’t know why they didn’t advertise this issue, because to me it made a huge part of the thesis come together. You could look near the bottom, almost in the footnotes, and see that the responses at weeks 6, 8, and 10 were really high. Then, at week 12, they went back down, and at week 14 they went back up.

The primary endpoint that everybody’s talking about was at week 12, so they got unlucky that the response went down right there at week 12. You could also see that the placebo response was low, low, low, low, then went up exactly at week 12 and back down. It really compressed that delta badly.

For 1 thing, they measured efficacy 18 times over the trial. Out of those 18 measurements, there was only 1 week with 2 placebo responders—only 1—and it was when the primary efficacy endpoint was assessed at week 12. All the others were 0 or 1. That’s a big deal, because that’s what you use to calculate the delta.

The other thing was that dip in the efficacy of the drug. If you look at the footnotes, you can see the number of patients who were assessed at each week, and that number went down by 1 patient just at week 12, then back up. To me, that meant that the efficacy went down not because the drug wasn’t working; somebody missed an appointment.

Somebody just didn’t show up at week 12 who was in response. They showed up at week 10, they were measured as a response, they didn’t show up at week 12, and then they showed up again at week 14. The efficacy went like this. The placebo went up, the efficacy went down, and both of them were just bad luck.

I’m so angry because I remember reading your paper on this, and as you say that, I’m like, “This is incredible. I want to go buy this stock right now.” Then I’m like, “No, it’s already gone up 10×, Andrew. You can’t go buy it.”

If they had presented that data to the FDA, it would be like you and I sitting down and saying, “Hey, look at week 10. Look at week 14. The delta’s different.” But if the primary endpoint was week 12 and they had presented it that way, would the FDA reject or accept based on that?

Would they be willing to modify it and say, “Hey, we saw it in week 10, and we see it in week 14, but you missed week 12 even though you hit the other 2”? Or would the FDA be rigid and say, “No, sorry, you missed it—the endpoint was week 12”?

Yeah, it’s kind of a moot question, because what you’re talking about is an FDA interaction that would happen after phase 3, where they’re saying, “This is the efficacy analysis we want to present and put in the marketing documents. This is the number we want to tell people.”

Yep, yep.

That would be a trial with thousands of patients. If this was a phase 3 trial, yeah, great point. But phase 2 trials are smaller, and then they get bigger and bigger. This is where I think alpha comes in for a small-cap investor: you can look at these tiny, minute details. In this case, 1 patient missing an appointment had a huge impact on how good these data looked.

That took the 9% from the Lilly misanalysis—that was the number everybody had had for years in the back of their mind. That’s how efficacious Nektar’s drug is: 9%, a terrible number. The reanalysis says low 20s. If you exclude that 1 extra outlier placebo responder, then it’s in the 30s. If you add back in the patient who missed their appointment, all of a sudden the delta would have been around 43%.

And now we’ve got a blockbuster.

Yeah, that’d be blowing efficacy out of the water. That was the biggest source of alpha for that trade, probably, in addition to understanding that there was a need that people didn’t see and believing that the reanalysis was actually legitimate—not a small microcap making things up against a big-cap pharma company.

Nektar was trading at less than half of its cash going into that readout. They had done a reverse split a few weeks before the data were to come out, and that spooked everybody.

People were spooked by the reverse split. I remember that, and I was kind of with them, too. I was like, “They’re going to do a reverse split before they release the data? Why not just—if the data are good, report the data and your stock is up 5×?”

The chief medical officer left the company a few weeks before the data, and that was for totally personal reasons. I think she might have been sick. Everybody was just spooked out of their minds. It traded as low as 0.36× its cash on hand, so it couldn’t possibly have been more negative than that.

Going into the readout, I was actually surprised that it didn’t go up more than it did. The phase 2 trial reported, taking the response delta to about 27%, and the stock went up almost 200%, then settled back down after an offering.

Since then—and this is what brings us to today—the stock has risen quite a bit more, and I still think it’s actually the most asymmetric upside in my book. It would still be Nektar. It’s at about $70–$75 now. It was roughly $25 after the data.

Really, 2 main things have happened that have improved the narrative and brought the stock up to the $0.70s. One is what you mentioned earlier: the induction data that they presented back in the summer of last year. That means you start people on the drug and see how many respond over the course of 4 months. Then you treat them for a full year and want to see how many patients maintain their response.

The induction data were good. They were a little bit less effective than the market leader, Dupixent, but that’s okay because the idea for the drug is to be for patients who have failed Dupixent. The maintenance data, though, were exceptionally strong—stronger than I had probably even hoped.

Basically, a higher percentage of patients maintained their response on respeg, Nektar’s drug, than on Dupixent. Not only that, they tested 2 different dosing intervals for the drug. It’s an injection, and they tested injections once every 4 weeks and once every 12 weeks.

That once-every-12-weeks regimen—4 shots a year—did just as well as the once-every-4-weeks injection, which is a huge marketing benefit for any drug. The biggest drugs in dermatology include drugs like Skyrizi that are given that sparsely. Patients love that.

Dupixent is given once every 2 weeks, so that’s 26 injections a year versus 4. That’s a huge deal for Nektar. That’s 1 thing that made it go up, but I think the more important thing that made it go up over the last several months is that there was 1 other mechanism of action, 1 other type of drug, that was going to get to market before Nektar and compete for this post-Dupixent, second-line atopic dermatitis market share.

And that was a drug class called OX40—OX40. Big pharma was already in on this one. Amgen had a drug, brodalumab, that targeted it, and Sanofi has a drug called amlitelimab that targets it. Both of them had multibillion-dollar net present values assigned to them because the market was acknowledging that there’s a huge unmet need in atopic dermatitis.

These drugs were going to be a very big deal. Basically, over the course of the last few months, several phase 3 trials have read out, and their efficacy just fell off a cliff. In phase 2, they looked promising, and in phase 3, their efficacy was much worse. So you’ve got Nektar now in phase 2 at about 27% on this delta number that we’re talking about. They had thought that OX40 might be in the high 20s as well, but now we’re talking mid-teens, like 16% or so.

But it’s not just that. They started seeing a form of cancer appear in patients who were treated with these drugs called Kaposi’s sarcoma. It is caused by the drug because people who have a mutation in their OX40 gene, which is what this drug targets, develop this type of cancer. So there’s no doubt in my mind, at least, that it’s being caused by the drug.

Amgen has already canceled its drug. They’re saying, “We’re not even going to take this market.” Sanofi is still being stubborn about it and saying they’re going to continue. I think another case or two of Kaposi’s sarcoma and they’re going to can it as well.

This created a massive vacuum for Nektar to take up huge market share. Sanofi is actually still saying that it projects $3 billion to $5 billion in peak sales for amlitelimab, even after these cases of cancer and after the efficacy went down. Nektar has not shown any sort of safety risk like that, and Nektar’s efficacy so far is better.

If somebody believed that Nektar was a $3 billion peak-sales drug right now, its market cap would probably be about 3x what it is. We could argue about what sort of multiplier you want to put on it, but I think it’s still not getting anywhere close to the amount of credit that it deserves as the next-to-market new mechanism of action in atopic dermatitis.

Two questions on Nektar. First question: You and a lot of people were really convinced about the maintenance data that read out in early February. What were you seeing that made you so convinced about the maintenance-data readout?

Yeah, you actually go back to the phase 1 data—the phase 1 data we were talking about that Lilly had analyzed, messed up, and sent back to Nektar.

That data set was really unique. They dosed patients for only 12 weeks, a really short treatment period, but then they watched them for a year after that. They watched them for an extra 40 weeks without ever treating a patient.

In most eczema patients, when you stop whatever drug you’re taking, the disease comes back. There’s no cure. None of these things are blocking molecular pathways of inflammation. Most drugs for eczema just turn down inflammation; they don’t do anything to rewire your body or, more or less, try to cure you of the disease.

Nektar’s drug respeg is a very unique mechanism of action. It makes your body create an anti-inflammatory type of cell called T-regs. These cells live in your body after they’ve been made for the long term. So it’s not blocking inflammation. The drug is creating an anti-inflammatory population of cells that then live in your body.

Mechanistically, there was some rationale to say, “Hey, even after you come off the drug, those T-reg cells that the drug made you create are still there, turning down inflammation.” But the bigger argument probably was the data from that phase 1 data set, where they stopped treating the patients for 40 weeks and they all kept their responses.

Nobody was getting treatment with any drug—no topical steroids, no more doses—and they stayed in response for almost a year, which is really atypical. It could have been luck or noise, but it looks like there may be some of what they call remittive potential with this drug, meaning that it actually rewires your immune system a little bit and you can take it for a while, perhaps come off of it, and still have a response. That would give me some confidence in the maintenance readout.

Last question on Nektar. I mean, this is the classic question with any biotech. Do you think this is a sale candidate at some point, or do you think these guys actually want to go and commercialize?

I would prefer that they sell, probably. I think that’s the answer for anyone that doesn’t have a commercial sales force, but I think they might want to go the other way.

Yeah, they might. They very well might. In the past, their big, high-profile drug was a cancer drug that we touched on earlier. They made that partnership with Bristol Myers Squibb with multibillion-dollar—what we in the small-cap biotech investing space would call—biobucks.

Biobucks, yeah.

Yeah, biobucks, meaning Bristol Myers paid them about $1 billion upfront and promised them maybe $1.5 billion more in milestone payments, as well as Nektar keeping over half of the revenue of that drug if it were ever to be commercialized.

So Nektar actually made a really good deal for that drug back in the day. That’s another option. And I think if they do choose to go it alone, a partnership would be almost mandatory, given the size of the market that they’re trying to address.

A buyout is certainly possible, going it alone is certainly possible, but there is a middle ground of a partnership where there could be a lot of upside. They could team up with a big pharma company and still have some of the benefits of that big partnership, without all the risk of going it alone as a small-cap company.

Cool. Unless you want to talk about anything else on Nektar, that was fascinating. Again, as you were saying, I was like, “Goddamn, I saw all the writings. Why wasn’t I huge in this last year?”

I think there’s one more important thing to talk about in the present day, which is just a few weeks from now. There’s going to be a readout for alopecia areata. This drug is being used in a second indication, a type of autoimmune hair loss called alopecia areata. It’s actually a pretty big market.

Right now, there’s only one class of drug approved to treat it: JAK inhibitors. If you spend much time in biotech or pharma, you know these are really strong, very effective drugs, but they’re dangerous. They have black-box warnings placed by the FDA for lymphoma, blood clots, heart attacks, and severe, potentially fatal infections. And that’s all we have to treat this alopecia areata disease today.

Dupixent has been tried for it, but it didn’t work. Lots of safe drugs have been tried. None of them have worked. Nektar has some early data that, to me, clearly show that the drug is active in alopecia areata. But the market does not seem to agree that it’s encouraging. Actually, in December, when they presented this data, the stock traded down over 50% because the market was apparently disappointed with the alopecia areata data.

What the market is missing now is, first, the need for a safe drug. A lot of people are comparing the efficacy of rezpegaldesleukin so far, which is admittedly pretty low, to the JAK inhibitor class. But I can tell you, as somebody who would literally be prescribing this drug, we dermatologists would use a safe, less efficacious drug 9 times out of 10, if not 10 times out of 10, before we went to a JAK inhibitor.

It’s just that nothing else has ever worked except for JAK inhibitors for alopecia areata. So if you sit down and look at the numbers on paper and say, “Yeah, Nektar’s data so far don’t look great compared to JAK inhibitors. This drug is dead,” then I think that’s what has happened. They’ve thrown the baby out with the bathwater there.

But we have a perfect analog, which is atopic dermatitis, or eczema. Dupixent is this multimega-blockbuster drug that’s doing probably $10 billion in sales in eczema alone. It’s half as efficacious as JAK inhibitors in atopic dermatitis. That shows you what the bar for efficacy relative to a JAK inhibitor is. You just have to be half as good, and you will dominate the market because it’s safe.

You don’t have to tell somebody, “Hey, I know your hair is falling out. Here’s a drug that could cause lymphoma, lung cancer, severe, fatal infections, blood clots, et cetera.” People don’t want to do that. So that’s one thing that the market is missing.

So far, the efficacy data that Nektar has shown indicates that it’s about half as effective as the JAK inhibitors. But there were some interesting issues with this trial that distracted investors and, I think, have led people to think that the alopecia areata opportunity is not viable.

I think the biggest issue is that Nektar’s drug works slowly. JAK inhibitors work really fast. If you’re going to respond to them, you know. When you look at case studies from Nektar’s data in alopecia areata so far, most patients who responded did not start responding until about 30 weeks into the study.

Well, 40% of the patients in the drug arm discontinued before 36 weeks. They stopped. They dropped out of the trial—not because of side effects, probably because they saw they weren’t getting better. This drug had never been studied in alopecia areata before, so we had no idea whether or not it worked.

They see they’ve been on this drug for over half a year and nothing’s happened.

I’m done with going to these trial visits every week. But for the few patients who stayed on, responses usually started after 20 to 30 weeks. So, if you look at the efficacy now, it doesn’t look great because not that many patients responded when you look at the overall sample size for the patients who started, but almost half of them quit the trial before they should have had efficacy.

Interesting. So, what’s going to happen in the next couple of weeks is they’re going to have maintenance data, just like the atopic dermatitis readout had maintenance data after induction. It’s a shorter maintenance period, so it’s only 16 extra weeks.

But what I think we need to see is that just a couple of patients had deepening of response after that 36-week cutoff. Because it just goes further to show that this is a slow-onset drug. Patients will know that in the phase 3 trial. Dropout rates in phase 3 trials are much lower for various reasons that we could spend time on.

Their phase 3 trial is going to be longer. This was only a 36-week primary induction study; in phase 3, they’re going to run it for a full year. So, in phase 3, in my opinion, it’s going to be over half as effective as a JAK inhibitor. It will be the obvious first-line treatment for alopecia areata.

Alopecia areata is a potentially multibillion-dollar indication. Four JAK inhibitors have all been launched by different pharma companies because the market is that big. But it’s at 0 in the NPV right now, according to the market, as far as I can tell.

How big would it be if people were truly convinced that it was going to hit in phase 3?

The NPV could be $3 billion to $5 billion for the market cap, potentially. Peak sales could very easily be $2 billion in alopecia areata alone. We have pretty good validation from another drug on the market, nemolizumab, which I talked about as not being effective in eczema. It has a secondary indication called prurigo nodularis that is maybe one-third as big as alopecia areata. It’s also a dermatology indication, and that’s going to be a $4 billion peak drug, including eczema and prurigo nodularis.

So, really, if it is a first-line treatment for respeg in alopecia areata, a $2 billion peak might be conservative. It would also expand the market because so many people don’t get treatment at all when the only option we have is dangerous. That is why I think Nektar has the most asymmetric upside on my book right now. I think the alopecia areata opportunity was written off to absolute zero.

The atopic dermatitis opportunity probably isn’t appreciated as much as it should be, but the skew here on this alopecia areata setup is totally off. We didn’t even talk about the other thing. I don’t know how much it is, but I think Eli Lilly is going to be paying them a pretty penny from the legal lawsuit at some point.

Let’s put that aside because we’re running long, and I’m having so much fun and learning so much. I want to ask you about ABIVAX. This would have to be the most popular. I do events, I do biotech, I do a little bit of everything. Every event person thinks this is getting taken out. Every biotech person thinks this is getting taken out. The French press certainly thinks it’s going to get taken out, but maybe we can quickly go through your background here because, again, you nailed it.

I remember the screenshot of the slide where you said, “This is the killer slide.” I remember it so well. Maybe we can go through the background and then talk about the opportunity today.

Yep. So, it was a small Parisian biotech with a repurposed drug. Nobody knew how it worked.

Red flag, red flag, red flag, red flag.

Management had burned tons of cash. This is old management, not current management. They replaced management when they did the U.S. IPO to get a Nasdaq listing. They’re still on Euronext, but I’m not dissing the current management if you’re listening.

[sighs]

But huge red flags. They had burned tons of cash they should have been spending on this ulcerative colitis study to study the same drug in COVID at some point, which made no sense to anybody. So, people hated this stock. Most biotech investors actually knew about it, so it wasn’t something that was undiscovered. Everybody had heard of it, and most people had written it off.

There were definitely a few people who were on top of it and believed in it, but it was a small minority. They had this mysterious drug that nobody knew how worked. They had some phase 2 data in ulcerative colitis, which is another massive indication. There’s huge pharma interest in buying out companies with effective drugs in ulcerative colitis.

The phase 2 data looked okay, but there was a lot of hair on it on top of all that other stuff we just rattled off. The biggest issue in the phase 2 data set was the clinical remission delta. It wasn’t the primary endpoint in the study, actually, by trial design, but it was the endpoint everybody cared about. A lot of the secondary endpoints in the trial looked really good and really competitive, but the one that was most important turned out, just unluckily, to be a lot lower.

Not only that, there was what was called an inverse dose response in that study, which biotech investors hate, especially when they don’t know how the drug works. The 3-milligram dose worked better than the 6-milligram dose for some reason.

Right. So, you give somebody a bunch of the drug and it doesn’t work, and then you give them a little bit of the drug and it does. It’s possible that’s statistical noise, but if it’s statistical noise, then is the evidence of efficacy just statistical noise?

Yes, investors hate inverse dose response. When you combine that with a crummy French company with an unknown mechanism of action, it’s like a death knell. So, the stock traded at an absolute pittance for the rest of the evidence that they had. If you hadn’t seen that, you would have been like, “Why is this thing so cheap?”

We had that phase 2 data for years. Their phase 3 trials were enrolling super slowly. It was hard to get patients to enroll. It was this kind of sleepy European company. Were they managing it right? For years, I was looking at this data set saying, “Man, I really think this is real.”

There were a lot of reasons I thought the data were real. One was that all those secondary endpoints looked really good. Another was that I could ignore the inverse dose response if you pooled all those dosing arms together. The data looked really good that way, so you get your higher sample size and that delta looked good.

But bigger things than that, if you paid attention to how severe the patients were in this trial, it was off the charts. They were the most severe patients in terms of their disease characteristics. They had the most severe ulcerative colitis of any trial I could find, ever. So, to see evidence of efficacy in such severe patients meant a lot.

The really big thing was the maintenance data. That came out a little bit later. The induction, just like we’re talking about with Nektar, is the initial treatment period, which comes out first. They keep running the trial longer and show you maintenance data. The maintenance data looked incredible. The response rates were really high, and people stayed on the drug, which was really interesting.

That was something I thought maybe one of my edges was in this analysis. I looked at other trials of oral therapies, so pills, including FDA-approved drugs for ulcerative colitis, and saw how many patients stayed on the drug at 1 year, 2 years, and 3 years for a real active drug—a drug we know works because it’s FDA-approved and on the market. At all of these time points, you could look at ABIVAX’s drug in maintenance and say, “A higher percentage of patients are staying on this unapproved drug nobody knows how works.”

Why? Well, it’s not because these extremely severe patients are having random placebo responses for 5 years. It’s because the drug is active. So, I was already pretty convinced that the drug was active.

But you mentioned this killer-slide thing. I was already planning on taking a pretty concentrated bet on this readout. The thing that I discovered, kind of like we talked about with the eureka discovery with Nektar— noticing that a patient missed their visit—was a nuance in the ABIVAX trial. It’s this way with most ulcerative colitis trials: only patients who respond to treatment during induction can enroll into maintenance.

During those first few weeks they treat you, if you’re not a responder, you do not continue. Only people who are responding to the drug go into the maintenance phase of the trial. The company and everybody else are blinded to the response rate in these studies, meaning that from the beginning to the very end, nobody knows what the response rate is.

But they knew how many patients enrolled in their maintenance trial, so they knew what the enrollment rate was. If only responders enroll in maintenance, you actually know the pooled response rate, meaning some of those responses are placebo patients who responded, but some of them are drug patients who responded. If you have a really high enrollment rate into the maintenance phase, then you can break those data down and get a general idea of what the response rate—and, more importantly, the remission rate—is going to be.

So, they actually published that data in their corporate deck. They were doing no meetings. They had not done a fireside chat in over a year, but one lonely slide near the very end of their corporate deck said, “Hey, we’re 80% of the way through the trial, and by the way, 600 patients have enrolled into the maintenance phase.” I remember reading that.

I’m so mad because I saw your post and bought some, even though I drool out of my mouth at times. As you explain it to me, I’m like, “I get why it wasn’t. It’s so good.” I sent it to a couple of people and was like, “Hey, I think I found some material public information here. This is absurd.” And it’s just sitting there on the corporate deck.

Taking that the next step, you could look at it and say, “Yeah, it looks like that’s a really high pooled response rate.”

But what I did was take all of the phase 3 trials of once-a-day pills and look at what their pooled response rates were. For an FDA-approved drug, what’s the pooled response rate for these drugs? What was it in their phase 3 trials? Then I looked at what the placebo rate was in those trials. You take those data sets and get what you expect a pill’s placebo response rate to be.

You can say that whatever the difference is, on average, between what ABIVAX is seeing so far and that placebo rate is probably what ABIVAX’s drug is producing as a response rate. But that’s not the primary endpoint. The primary endpoint is remission, not response: complete disappearance of disease, not reduction in disease.

The next step is to look at that pooled data set of other phase 3 trials and say, for every patient on drug in response, how many patients were in remission? That’s the response-to-remission conversion. You could do that for ABIVAX and say, “Okay, after I subtract the placebo rate out, I can impute the response rate, and then I can impute the remission rate using this response-to-remission conversion ratio that you typically see from pills.”

So I did all that math, and at the end I was looking at a number that was going to be 1,000% upside if it was real. But it was extremely robust, and it was based on actual data from the clinical trial that was going to read out. At that point, I had already been very bullish on the stock, but I had what I considered basically mathematical proof that the trial was going to succeed.

From there, I did a few other imputations. I put in the absolute worst-case placebo response that’s ever been seen in a phase 3 trial and the absolute lowest response-to-remission conversion ratio that’s ever been seen in a trial. I could see that even if the absolute worst luck ever happened in this clinical trial for ABIVAX, it was probably still going to hit. A statistically significant hit at all was at least 100% upside.

Ultimately, it was right in the ballpark of what my math told me it was going to be. It was up like 600% the next day, and since then it’s up another 100%, so 1,400%–1,500% in, I don’t know, 8 months—something along those lines.

Let’s talk about ABIVAX, then. I keep joking—this is probably the 4th time I’ve made the joke—but there’s a French press article that, if you believe them, comes out every week. Or, if you believe there’s some very weird tracking of jets on Twitter and stuff, everyone thinks they’re going to sell.

They’ve got maintenance data coming up, and I can’t remember if it’s June or July. I mean, it’s June. They haven’t hired a commercial sales force, so you can kind of put 2 and 2 together on what the end game here is, but you’ve got the maintenance data. There’s other stuff going on. Where do we sit in the ABIVAX story right now?

I don’t want to talk your portfolio for you, but I believe you continue to hold the stock. How are you viewing the edge and the alpha in the setup these days?

In my opinion, it’s the most obvious buyout candidate of any stock I’ve seen. This was a big part of the thesis from the beginning, actually, because every successful ulcerative colitis trial in biotech has led to a buyout so far. We’re talking about drugs that have multiple competitors with the same mechanism of action, worse efficacy, and safety risks—all of them huge, multibillion-dollar buyouts from pharma. Most of them were after phase 2. This is after phase 3.

I think they should hire a commercial sales force. I think they will. To me, I know you get the degenerate gambler community involved in something like this. You talk about tracking jets and going off all these articles in the press—

Would you like me to tell you what their options volatility is right now? Because you want to talk to a degenerate gambler, yeah.

Yeah. And what those people want to see is that they never hire a chief commercial officer, because the thesis there is that it could get bought out tomorrow. They could get bought out tomorrow. They haven’t hired a chief commercial officer. The day that they hire a CCO, the next day it’s not going to get bought out, okay? Probably not the next week, either.

I still think they should. I personally believe that the company very likely has been approached, or at least has had conversations, with big pharma companies about what an acquisition would look like. I don’t have any idea how far those could have gone. I would be hard-pressed to believe the conversations have not started.

If I’m in ABIVAX’s shoes, and we’re talking about what could be, at this point, a $15 billion to maybe, in the best case, a $20 billion buyout, you want to have the illusion that you can go it alone for your bargaining power, right? So you hire a CCO and pay him $1 million. If you move the bargaining power of a $15 billion buyout by 1% by saying, “Hey, we’ve got our commercial sales force going,” that’s $150 million.

So it’s just the math to me—the whatever game theory you want to call it. I think they should hire a CCO. I personally think that they probably should have done it already, but who knows what’s going on behind the scenes.

I don’t disagree, but the pushback to that would be, “Hey, this is not a scenario where you’re talking about 1 best buyer.” There are 4 different megafirms that could be buyers. If it’s 1 best buyer, then you really have to go to them and say, “Hey, we will commercialize this on our own unless you pay us top dollar.” But when you’ve got 4 people who could buy this, you just say, “Okay, we’re for sale. Jump ball. Bids are due in 4 weeks.”

Yeah, that’s a really good point, and it actually speaks to a little bit about what’s unique for Abivax: just about anybody could buy them and put this in their portfolio, which is not typical. I think the only one that probably couldn’t is AbbVie, because that might become an FTC concern because of how many—

They’ve been rumored by the French press, though, if I remember correctly.

Yeah, they may have been. But otherwise, just about any pharma company could put this in, and the reason behind that is 2-fold, really.

One is that it’s super effective and safe and going to be a big-market drug for something that a lot of companies have a drug for already. But the second is that it is a totally unique, complementary mechanism-of-action drug. A lot of companies have 1 of any number of mechanisms of action to treat ulcerative colitis. If you already have, let’s just say, an IL-23 drug, you’re not going to buy another IL-23 drug or a drug that works in that pathway.

Abivax is the only company with a drug with this mechanism of action because, again, we don’t even really know what the mechanism of action is. So it’s hard to copy. That is incredibly unique in today’s age of pharma.

The example that probably drives this home the best is the biggest ulcerative colitis buyout so far: Prometheus Biosciences (RXDX), bought out by Merck several years ago for almost $11 billion after Phase 2, over 3 years behind where Abivax is right now, with arguably worse data. There are a dozen other drugs coming to market soon with the exact same mechanism of action, TL1A inhibition.

If you look at Abivax’s later-stage, post-Phase 3 position—not post-Phase 2—and this unique mechanism of action, it’s a very big deal. It could fit with anybody. Going back to the point you were making, maybe they don’t have to push the “Hey, we could launch this drug on our own” angle if they have multiple bidders. If there ever was a company that was going to have multiple bidders, this one makes a lot of sense.

And then maybe one last thing: the CEO was brought out of retirement to run this thing. He sold his last 2 companies. He was already retired after selling his last company to AstraZeneca, and they were like, “Hey, do you want to come run this thing?” I think he looked at the data in a similar way to how I did and was like, “Yeah, I think I actually might want to come out of retirement to run this.” So I’d be surprised if he wants to take it to commercialization.

I will not name specific names, but people can press Bloomberg terminals and see the top, let’s call it, 15 shareholders here. There are some very good funds with some very concentrated positions, and that includes both biotech specialist funds and funds that specialize in betting on people getting bought out. I can promise you none of them are here to say, “Hey, let’s go commercialize this ourselves.”

When you’re that concentrated, you’re saying, “We’re shifting all that commercial risk to Merck, Amgen, or whoever you want to say.” This has been a ton of fun. We can keep jamming for a few more minutes if you want. Abivax maintenance—

Yeah, I mean, we should probably touch on the Abivax maintenance data because, assuming they don’t get bought out tomorrow or whatever, that’s going to be the next catalyst.

Tomorrow would be funny because we're recording this on Thursday—what is it? March 19. Tomorrow is options expiration, so there would be some people on Twitter who are very happy.

I'd be thrilled to be wrong about this, but I've been saying all along that I think they should sell after the maintenance data. That's probably going to be in June.

I have a high degree of confidence: no drug that's ever done well in induction has failed in maintenance. Abivax didn't just do well in induction; they did exceptionally well in their Phase 3 induction. They're probably—you could argue—the 3rd-most efficacious drug that's ever been studied in this indication. Again, the ones that are more effective are dangerous drugs like JAK inhibitors that have all these side effects, none of which Abivax has ever shown.

So it's extremely effective. No drug, even one much less effective in Phase 3, has failed in maintenance, so its failure just seems off the table. On top of that, as I had been talking about before, my original reason for being super bullish about this company—before I discovered that quirk about the maintenance enrollment-response math thing—was how incredibly strong the maintenance data were in Phase 2. What we saw was that induction was okay, but then when we went into maintenance, the drug was really effective over the long term.

So the cards are stacked, and the stock is priced such that we expect the maintenance data to be successful. There are levels to that: it could come in at the low end and maybe be a bit disappointing, or it could come at the high end and be a blowout. The range, I think, is probably 20% to 30% delta. If you're going to look for a number to watch, it's probably going to land somewhere in that 20% to 30% range. You made me pick a number: 25%, right in the middle.

But if it goes below 20% and it's still statistically significant, the stock could be down a little. If it goes above 30%, that would make it probably the 2nd-most efficacious drug ever, behind only one of the JAK inhibitors called Rinvoq. They could be up meaningfully. Even at 25%, it probably could be up simply because the potential downside catalyst is gone—not just from efficacy, but from safety.

We already have a report that 80% of this trial is complete. They do something called a data safety monitoring board, where an independent group of doctors will look at all the safety data and say, “Hey, are there any signals from this trial? Do we need to change anything?” They've already reported on 80% of it through the maintenance phase with no safety issues. Getting that to 100% would potentially remove a very small, at this point, overhang—but still a few percentage points.

So mostly the stock is going to trade on buyout rumors until Crohn's data later in the year, which would be something else to talk about.

But this is—yeah, look, I think we could have you back on next year. Anything else you want to talk about, or anything else on your mind we should be chatting about?

Nothing major. There's probably a dozen things I could talk about.

Well, I'll have to have you back on to talk about them. This is our first time chatting, aside from me just working on your Twitter. This was awesome. I really learned a lot, and I really appreciate you coming on. Anytime you want to come on and talk biotech stocks, we'll do this. Adam, this has been great.