Arcus Biosciences, Inc. (RCUS) Earnings Call Transcript & Summary

Good afternoon, everyone. Welcome to the 43rd Annual J.P. Morgan Healthcare Conference. My name is Grace Cho, and I'm an associate on the J.P. Morgan Healthcare Investment Banking team. Our next presenting company is Arcus Biosciences. And speaking on behalf of the company, we're pleased to have Dr. Terry Rosen.

Thank you very much. So I'd also like to thank you. This is actually the first time we've ever presented at J.P. Morgan. So we're thrilled to be here, and we appreciate you and anyone else, who's listening in, and I'll just jump right in. I'm going to start just elevating a bit and talking about where Arcus stands. I know oftentimes, they say you should suggest 3 things that people should keep in mind since J.P. Morgan and I think maybe it's a little smarter audience, we're going to scope for 4 and figure we could do 33% better. So I'm going to start with the first 2, what we would say are near-term value drivers. And one of those is casdatifan, which is a best-in-class HIF-2 inhibitor; and the second is domvanalimab, our Fc-silent anti-TIGIT, which we're combining with our anti-PD-1 zimberelimab. That's in 3 late Phase III studies, and we're going to talk about all of these later. The final 2 points I would emphasize that I think are somewhat differentiated from a lot of biotech companies is that we have a very strong R&D engine. So we have substantial resources devoted to the internal discovery. In fact, that expertise is primarily in the area of small molecules, and we're focused on oncology and I&I. And finally, another differentiating factor is that we're well capitalized with over $1 billion in cash. And everything we're going to talk about today, all of those plans were funded into 2027. So building on that a bit, we've had pretty incredible partnerships on all respects. And one thing I would emphasize just on the various things that those partnerships bring -- to date, our partner-related funding that's flowed into Arcus over $2 billion. So I think a lot of companies when they do a collaboration, they struggle to come up with $2 billion in bio bucks, but we actually have a steady stream of fuel supporting our programs. And that's why we can have a deep, broad portfolio and like what are pretty competitive, some of the biggest markets in oncology and do it in a very efficient way. Beyond that capital, these are great partnerships. We get a lot of execution, human resources, for example, both Gilead and AstraZeneca are executing 2 of our Phase III trials. This slide is a bit of a 2024 accomplishments, and I'm not going to say much about any of these individually here because we're going to get into a little depth of data on every one of them. But in 2024, we actually had 5 presentations at medical conferences on 4 different molecules. So what I would also emphasize about those presentations is the data we generated certainly contributed to proof of concept, but all of these programs, I would sort of express that they were also graduating that we were not getting to some nodal point with proof of concept and waiting for how are we going to advance these. But in parallel, they've been moving along into later phase studies. So to just go through those really quickly. In October of last year, we presented data that we believe clearly illustrated that casdatifan, our HIF-2 inhibitor has an improved profile relative to that of belzutifan, the only other HIF-2 inhibitor, which is Merck's. We presented 2 new data sets in the context of anti-TIGIT one in lung, ARC-10, one in upper GI cancers, EDGE-Gastric that made 3 proof-of-concept studies in the last 18 months. And then finally, at the bottom, ARC-9 and ARC-8 were 2 studies with our adenosine modulating molecules. Both of them showed unprecedented overall survival in one case in the context of colorectal cancer and the other pancreatic cancer. Great data. And in fact, for quemli, we've just recently started and dosed our first patient in the Phase III registrational study that's looking at quemli, our CD73 inhibitor on top of Gem/Abraxane versus Gem/Abraxane. I think one of the important aspects about all of our programs, as you think about them is that in all cases, what we're looking at is something that we've generated a good quantity of data that shows efficacy, but on top of the standard of care, and that's actually very important for a number of reasons. The first reason is we're not looking to displace the standard of care. Second thing, from an execution standpoint from -- if you want to think about value proposition to a physician or a patient is basically you're bringing on something with a relatively benign safety profile. So the patient is either going to get the standard of care or they're going to get standard of care with something that looks like it may bring them added benefit. So this gets it a summary, I'm going to keep coming back to this slide a few times that looks at these late-stage programs, and I'm going to start off with casdatifan, our HIF-2 inhibitor and say a little bit more about that. So these data are old news. But in a sense, they also foreshadow what's going to be coming this year because it's going to be a data-rich year. So these represent data that we presented at the triple meeting in October, and I'm going to -- there's a lot of data here, and so I'm going to walk you through some of the key highlights. So what these data are looking at are 2 different cohorts, a 50-milligram cohort once a day, a 50-milligram twice a day, so 100-milligram cohort in clear cell RCC patients. They are each 30-patient data sets. So the left-hand side, where you see the waterfall plot, a couple of important aspects that you should take away. First off, you can see how the geography of that waterfall that such a vast majority of the patients are getting some benefit. They're getting tumor reduction. I think the other thing that's important is, if you see under those bars, all the forward arrows, despite the fact that this had 11 months of maturity, all those patients were still on study, which gives you a sense of the durability of effect. So now let's go to the right-hand panel, which is even more complicated, but I think we can actually break it down in a fairly simplistic way. So the first 2 columns actually get at what we're thinking about as we compare this data set, historical data from belzutifan and belzutifan's registrational study, which is called LITESPARK-005. So the first column shows that in our cohorts, we actually are enrolling a more advanced patient population than that which was in the belzutifan study. So as a matter of fact, between 25% and 30% of our patients wouldn't have even been eligible for the belzutifan trial. The second column has the median follow-up time. So we presented relatively immature data, 11 months for the one cohort in the 50-milligram cohort once a day, 8 months versus 18 months median follow-up for belzutifan. The reason that's important is for this mechanism, it's been well established that the data continue to get better over time. So with respect to our 2 cohorts that we've shared, you would expect that the 8-month median follow-up or the 50-milligram once-a-day cohort has the most probability that the data will evolve with time. The next point I would just make is whether you look at ORR, the rate of primary progression, which is important because it affects everything else, that's those patients that don't even make it to first scan or durability, and in this case, measured by disease control rate, we're looking better than belzutifan on all fronts. Median PFS hadn't been reached. So that gets me to what data will be coming. So you can see that, that primary PD rate is on the order of about half of what you were seeing with belzutifan and that variable was something that was called out from clinicians when we first got involved in this program is really the Achilles' heel of belzutifan. So what you should recognize, first off is that belzutifan was a transformational therapy. It's very safe. It's much better tolerated than TKI. So physicians love the mechanism. But the one limitation that emerged that affects all the other variables is basically you have almost 1/3 of the patients progressing before they get to that first scan. So obviously, those patients have no chance to get any benefit from the mechanism. So as I mentioned, these foreshadow what's coming. So let me say a little bit about -- and I'll talk about when, but we're going to have updated data from this at ASCO GU. So the titles were just announced. So we're basically just a month away from a very fulsome data set. And in those data, what we're going to include, you'll have updated data from the 2 cohorts here. And most importantly, for those now we'll have median PFS. So you'll get a clear measure comparing back to belzutifan's 5.6 months. I think the more unanticipated data that we're going to have is that we've fully enrolled another cohort that's looking at the tablet formulation, 100 milligrams once a day of what our go-forward dose is going to be in our registrational trial that we're looking to get up and going as fast as we can by the middle of this year. So in addition to these more mature data on these 2 cohorts, we're going to have the early ORR data set for the -- that 100-milligram dose. I think what's important is by the time you get out of that meeting, a lot of people that saw our data say, like, yes, this looks better than belzutifan. We want to see more. Not only are you going to see more durability, but you're basically going to have 3 independent cohorts of 3 different experiments that on 3 different variables, durability, response rate and primary progression look better than belzutifan on all fronts. To me, this is the most important casdatifan data, and it's -- it hasn't been seen by everybody. There are data that on the left hand where you see the Merck data, Merck published these data in October, and we shared similar data. The reason these data are profoundly important is if you look at these -- when you think of coming as a scientist -- so you've got these clinical data. And the question when you have clinical data is always, are you sure they're real? How do you explain them? And so, what to me always is most compelling is if you can associate some molecular properties, some molecular feature that makes sense that explains those data. And you're never going to see 2 different data sets that more differentiate molecules. So let me walk you through these a bit. So HIF-2 alpha is a transfusion factor, and it's involved in the regulation of probably hundreds of genes. But one of those is erythropoietin production, so EPO production. And that EPO production is also involved in its one on mechanism side effect, which is anemia. But that erythropoietin production is the gold standard, as a biomarker for HIF-2 inhibition in a human. So anyone who's going to take a HIF-2 inhibitor into a human is going to measure its effect on suppression of that production of erythropoietin. And what you can see is a dramatic difference, where with the Merck molecule that this shows the time course and you can see that between -- somewhere between 9 months and 13 months, it's basically losing that pharmacokinetic effect -- pharmacodynamic effect. And what you can see for the Arcus molecule casdatifan is that clearly, even at 36 weeks, it's maintained that effect. So if there's anything that you want to see that supports that the clinical data are driven by something, it's this change in pharmacodynamics that you see between the 2 molecules. Now let me sort of summarize and finish on casdatifan by thinking where we're going from a development strategy because that's also very different than Merck. So our first Phase III study follows that same theme that I talked about, the standard of care in this field is cabo. And what our study is, is a very simple study. It's cabo plus casdatifan versus cabo. So very attractive to clinicians, very attractive to patients. It's a great opportunity, and we're looking to get that up by the middle of this year. The second trial that we're going to be starting is a collaboration that we're doing together with AstraZeneca, and that involves combining casdatifan with their CTLA-4 PD-1 bispecific antibody, volru, which they have reason to believe is best-in-class. And what that takes us into is a frontline setting. And one of the reasons that's so exciting to the investigator community is it's a TKI-sparing regimen. So physicians would love to do as much as they can where they can treat these clear cell RCC patients with a regimen that avoids the pretty nasty effects of TKIs until as late as possible. So just those 2 settings alone are $5 billion-plus market opportunity. I think a lot of people don't realize RCC is like the sixth largest oncology market. So it's big. A couple of other things to keep in mind. Every patient in this -- their lifetime that get this disease is going to get an anti-PD-1, they're going to get a TKI. And in fact, the TKI market is pretty fragmented. Even though our cabo sells like $2 billion. There are 7 of these TKIs. There's only going to be 2 HIF-2 inhibitors, 2 horse race, us and Merck. And we actually believe that's the strongest mechanism in this field. It's also the most benign from a safety profile. So from a vision standpoint, we actually think that every patient in their life cycle of treatment should get a HIF-2 inhibitor, and we think that, that HIF-2 inhibitor should be casdatifan. And what you're going to see as the year goes along beyond these 2 studies, we'll be adding some additional cohorts to our [ platform ] study in the setting that's called ARC-20 that further look to how we'll be expanding that development opportunity. Now let me turn to our anti-TIGIT, domvanalimab that we're looking at in both non-small cell lung cancer, as well as upper GI cancers. I think the market opportunity, they are well established. I don't think we really need to say much about it. If these are successful drugs, they're huge. And in fact, in the lung setting, you're really going at the underbelly of KEYTRUDA in terms of the opportunity there. What I think is important is when you think about 2024, if you follow oncology, whether you like it or not, you followed TIGIT. And I think what 2024 really firmly cemented is something that's been talked about for some time, but there were a lot of data. There were data from Genentech. There were data from Merck. There were data from AstraZeneca. There were data from us. And what it made very clear is that the 2 configurations of antibodies, Fc-silent, which we have and AstraZeneca have versus the others, which are Fc enabled, you should almost think of them as 2 different classes of drug. And that's well understood because the Fc-enabled anti-TIGITs in this particular case for that antibody, they target cells that bear TIGIT, and it's been well shown that they target T regulatory cells. And what that targeting does is it leads to immune AEs. There was no place, where this was more evident than in the Merck studies because what Merck was doing was they were using a co-formulation of pembro plus nivo, their Fc-enabled anti-TIGIT. So what that does is it leads to immune AEs that lead to treatment discontinuation, which leads to loss of efficacy. Now what you saw with the Arcus molecule, as well as the AstraZeneca molecule, they have a bispecific, where their anti-TIGIT arm is Fc-silent is positive data from us, positive data from them, and I'll comment on a few of those, but data that looked very similar. So we think the field has really been divided into those 2 and that actually you're going to see more continuous data, where that Fc-silent anti-TIGIT becomes the dominant player in the field. And in fact, Merck is out of it. So the place, where I think that's most important is those AEs that we were just talking about are amplified in the context of chemotherapy. We've already shown in our studies that you can add domvanalimab on top of anti-PD-1 and chemo, you get essentially the same safety profile as just with anti-PD-1 chemo alone. So that's what lets us really feel confident about the biggest market of all, the PD-L1 all-comer frontline non-small cell lung population, where you're going to be looking at dom, zim, chemo. So these are a couple of the data sets that I referred to on the earlier slide that we presented last year. So our registrational trial in upper GI cancers is called STAR-221, and I'll speak to the trial itself on the next slide, but we shared data from the Phase II [indiscernible] last year, and what we're looking at there is exactly the same population with exactly the same regimen. And what you could see is we saw roughly a 12-month, 13-month median PFS in that setting. Now if you look at the right-hand side, that gives you a sense of where does that stack up. So CheckMate 649, CM-649 is the registrational study for nivo chemo that was run by BMS. The KEYNOTE study next to that, the RATIONALE study next to that, those reflect similar approval data sets for pembro chemo, as well as [indiscernible] chemo. And what you can see is very similar, very consistent PFS on the order of 7 months. So you can see we compare quite favorably with almost double that, and we think that bodes quite well for the registrational study. What I'll comment is that AstraZeneca at ESMO with their bispecific same study that we ran, very similar PSF -- PFS within a month or so. So we feel we have 2 independent data sets, 2 different companies that are pointing to the same story. This slide summarizes the design of that registrational study that I just talked about. The important thing to take away from this slide, there's 2. So the first thing is it was really well powered. So it was fully enrolled, as of June of last year with over 1,000 patients, 1,046. The second thing is that it has dual primary endpoints, the ITT, the intent-to-treat population, as well as the high PD-L1 patient population. So in fact, there's 2 ways to win if you win on either of those endpoints. This brings me to a data set that we reported at SITC last year that gets to the lung cancer component of this, and that's the ARC-10 data set. This is really probably one of the best data sets, randomized and overall survival with greater than 24 months of follow-up in the anti-TIGIT field. And what you can see is a number of things looking at the curves on the right, Kaplan-Meier curve, the first thing that you can see is that the hazard ratio in this you're looking at dom, zim, the anti-PD-1 anti-TIGIT versus zim, the anti-PD-1, the hazard ratio is 0.64. So quite a difference there. The second thing is in an absolute sense, the overall survival for zimberelimab alone was over 24 months. So very similar, perhaps slightly better than pembro in KEYNOTE-42. So any differences between zim or pembro that people might have thought about or talked about before, clearly put to rest here. Probably the most important component of this data set is looking at that upper line in that curve, which is dom, zim is looking at the tail. So the biology of anti-TIGIT tells you that what anti-TIGIT does is turn anti-PD-1 into super anti-PD-1 and that's exactly what you're seeing. You're seeing that amplification of the tail, which is what immunotherapy brings. So that these data look very consistent with the biology. The second thing that's worth noting is that in the past, we presented a Phase II randomized data set, ARC-7, similar situation, in this case, talking about PFS. PFS was the primary endpoint there. Again, we're seeing very similar data with a hazard ratio for PFS on the order of 0.65, 0.67. So 2 data sets that firmly point to their proof of concept that give us great confidence in our registrational trial, STAR-121 that's in the PD-L1 all-comer non-small cell lung cancer setting. So this slide wraps up. I started with the slide that showed what did we disclose in 2024. This is the data flow for 2025 and there's a lot. The first thing is, as I mentioned, in next month, February 15th, we'll have those updated data from casdatifan. I think what you're going to see are 3 different cohorts that have blinking lights on them that show all 3 of them collectively better than belzutifan. Mid-2025, I mentioned our first registrational trial is going to be a combination study with cabo. We already have over 25 patients enrolled on the combination. It's primarily for safety purposes. We'll disclose those data in the middle of the year. Not only we will have safety, we'll have early efficacy data. But what we can already say now is that we're not seeing anything surprising when you think about these orthogonal mechanisms from a safety standpoint. So it looks like they combine quite well, as would be expected. The third data set, second half of this year, I mentioned EDGE-Gastric, the PFS data. As I said, we showed 13 months PFS. 13 months is the OS roughly that those other molecules were approved upon. So we're going to actually have OS data later this year. And what I can tell you is that we have said publicly in 18 months of median follow-up, we have well over 50% of the patients still on study. So we think this is going to be another strong data set supporting the outcome of that STAR-221. We'll continue to report on casdatifan. This wasn't sort of a one cohort, one-off study. We're going to be in casdatifan. If you think about the evolution of Arcus, the centerpiece of our development is going to switch as these anti-TIGIT programs go into the later phases of moving towards data, registration, commercialization. Casdatifan is going to become the center of our program. And so, we're going to be sharing data on a pretty continuous basis. And finally, we're guiding to read out from that STAR-221 that I showed you that had the 1,050 patients or so into -- that, that will come in 2026. We're excited about that. We and Gilead are working very closely together, basically preparing for that data readout, as well as commercialization. So let me just finish by circling back to those 4, 33% more than 3 points that we wanted you to remember. Hopefully, we gave a lot of more granular points on each of them. 2 near-term value drivers, casdatifan with the evolving development program, we think that's just going to be huge in clear cell RCC even as we contemplate moving into other settings. Domvanalimab, these 3 late-stage programs, getting towards data, getting towards commercialization. That sustainable drug discovery effort because that's how we've built Arcus from scratch. So [ it's not one ] of these companies, where we're going to bolt on research afterwards. That's really the secret sauce of the company. As the year goes along, we'll actually start to share more about the I&I component of what we're doing in addition to the oncology. And as I mentioned, we continue to be well funded. So all of these plans we've talked about today are taken into 2027 with the current capitalization. So I'll stop there and happy to take your questions or any other questions that might come in.

Great. As a reminder, please wave your hand if you have a question and we'll pass the mic around. I can get us started here. What makes the Arcus investment thesis different from other biotechs? And what do you think investors are missing about the Arcus story?

So I don't think they're missing much. I think there's a lot of differentiation and really flows from what we talked about today. So first off, you've got the breadth of programs. I think the other component is not only do we have broad, but within each, they're deep, and we're in some of the biggest oncology markets with innovative new drugs. And so, we're competing against Merck, we're competing against AstraZeneca. We're competing against Genentech in some of the biggest markets. And those readouts are either around the corner or in the case of casdatifan, you basically have a very unusual confluence of circumstances. You have a molecule that's validated the target, as close to 100% probability of technical success as you can get. You're going to have a strong group of data that support that you have a better molecule, and there's going to be limited competition because of difficulty to target. So there's going to be a 2-horse race. We're going to have a very broad development strategy. And then I think the third component beyond that sustainability, I think these days, you don't see many companies that build an R&D engine in a bonafide way is that we're capitalized in a way and have been capitalized in a way to enable us to execute on our programs.

Can you talk about your portfolio approach and overall strategy? How do you prioritize your programs and evaluate potential partnerships? And are you considering more BD in the future?

So absolutely, we consider more in the future, and it reflects that same strategy. So from a prioritization standpoint, I think we're always looking to be in something, where we can be first and/or best. We tend to lean toward small molecules as differentiation because we have a real strength there and it's something that's been fading in the industry. You don't see as much of that even at the larger companies. We do look to play in large areas. From a business development strategy, what we've talked about today, I think, reflects the way we think mostly about our near term, and it's things that give us an advantage to come up with a best of class combination and get assistance in execution, and so, we get that capital in human, and those are not independent variables, efficiency. So for example, AstraZeneca, I didn't talk at all about our Stage III lung trial that's well along, as a Phase III study. So AstraZeneca has a standard of care there, that's durva. Durva sells over $2 billion just in that market alone. So we're combining durva with domvanalimab, AstraZeneca is executing that study under very favorable economics. So who would you rather have anywhere on the planet than the company that owns the Stage III lung market, has the expertise, has the connections, knows what they're doing to execute that trial on your behalf. So that's an example. Second collaboration, where we're combining with volru, very similar, where they have a potential best-in-class, think about it, their bispecific molecule that hits CTLA-4 and anti-PD-1. It's very much a synergistic concept. Combining that with casdatifan that can bring something on top of what's probably 1/3 of that clear cell frontline therapy, where the deficiency can be that you have that higher rate of primary progression that we can actually bring to the table and address with casdatifan. And again, they're going to be executing that trial. So we're often looking for complementary mechanisms with real partners that can execute and actually enable us to do something that makes it easier than if we were to just do it alone.