We're officially, okay, good afternoon. It's past noon. My name is Akash Shawari. I head our farm and biotech efforts on the research side here at Jefferies. We are in beautiful Times Square, and this is day one of our public portion of our health care conference. We have the SPIRE management team. Cam, why don't I hand it off to you for some intro remarks, and we'll get started.
So thanks for having us. It's always a great conference. The background for SPIRE is that we're working on a portfolio of therapies that we hope will elevate the standard of care in autoimmune disease. Our first initial focus is on inflammatory bowel disease, where we're working on what we believe are optimized antibodies against the best biologic targets in IBD, alpha-4, beta-7, TL1A, and IL-23. And we're developing them not only as monotherapies, which we think would provide substantially improved convenience and potentially better efficacy on some of these targets than the first-generation molecules, but perhaps more excitingly testing them as combination therapies, which we think have the prospects of dramatically improving the standard of care in terms of efficacy in this space. Outside of IBD, we're evaluating a different TL1A asset, a second TL1A antibody, and a basket of rheumatic diseases. That's rheumatoid arthritis, psoriatic arthritis, and axial spondyloarthritis. We think TL1A has great evidence in those indications, and we'll have a first and potentially best-in-class molecule in those indications as well. Cumulatively, we think it's, you know, one of the more exciting portfolios in INI, certainly. We'll have five more phase two readouts this year, and then the combo data to come next year. So I think it's a really exciting time for the company. Understood.
And I really appreciate it. And yeah, look, I think it's funny. You know, the discussions you and I had like last year, Duet was this overhang and we're waiting for it to come out. And, you know, there's a lot of, you know, I want to talk about your read on the Duet data. And then also you get this happy, you know, randomly on a call validation of your combination approach. I think it certainly accelerated the potential of your common strategies in GI, but I actually do want to hit on DUET, because I think there is kind of room to chop in terms of how you look at that data versus maybe that initial read, well, hey, it only worked in this kind of refractory subset of patients, and Spire's talking to us about frontline combination regimens and going for a broader population. Why is that possibility still open from you looking at the DUET trial? Yes, I mean, fundamentally, we started focusing on combinations after the J&J read out their
Vega results, right? So if we look at the totality of the J&J development program, they read out the Vega results a little over three years ago now, and then just recently the Duet results. And if we look across kind of lines of therapy and how that combination performed, the results in the frontline setting in the Vega study was very impressive. More than a 20-point delta on clinical remission compared to both monotherapy components in that study. And then when they moved to the Duet populations, now it's 100% refractory population, and then we saw in the data set they reported a few weeks ago on the ulcerative colitis side is about 70 percent had failed the prior TNF and on the Crohn's disease side is more like 90 percent of the population had failed the prior TNF and then J&J's combination is Tremphia is one of the components an excellent IL-23 inhibitor and their other component is glimumab or symphony which I think it's fair to say within the TNF class is not the most effective of the TNFs and so after these these populations had 70 to 90% TNF refractory, the galimumab or symphony arm added very little. So we saw the monotherapy arms in the duet studies had, you know, mid to low single digit remission rates alone. Yes, and so the delta over tremphia looked promising, particularly in the late line patients, but it was clear that that one galimumab component added very little. Right. So when we look at the totality of it, I think it's fair to say that, you know, what your components are matter, and having better components, which I think is our premise here, is having the best possible components of our combinations. That matters a lot. And two, the population you study it in matters as well. And so that's why in the design of our skyline study, we have half of the trial is a naive set of population. I think that should look like the Vega results did. And then our other half that is a refractory population, I don't think it's fair to say that it's likely to look like the duet result, because we're not going to have 70 to 90 percent having failed one of our mechanisms. We're capping the number that have failed our mechanisms at a relatively low rate. So it'll be a minority that have actually seen our mechanisms. And I think that bodes well overall for how our combos we expect to perform across the totality of the population.
So in contrast, I think DUET was like 90% TNF failures. When you say minority, is there a ballpark range? Yeah.
We expect it could be single-digit patients in our study on each of the arms having failed the prior agents. So I think it's very likely to show a different type of result, both because the agents themselves, I think, are likely to be superior to galimumab, but then the trial population, I think, is also set up for a different type of result. And then, you know, to your initial point about them now advancing that agent in the third line plus population in the phase three studies, you know, I'm hopeful that won't have to be our development plan for our agents. I think what we know about IBD from the profile study and others is that top-down therapy is the best for patients in this space, And what that means is put patients on the best drugs first, and that leads to the best long-term outcomes for patients. And not only the outcomes for the patients, I think there's actually good health economic data from those studies as well, showing that it's not just better for patients, it's actually better for health systems as well, given that the cost of care for IBD is so large. So what we're hopeful is we can deliver these combination therapies that substantially improve efficacy, don't have safety downsides, as we didn't see for a TNF combo in the J&J trials, and then we can deliver them at a reasonable price point as a co-formulated product, And I think that product overall has, you know, very few qualities that don't make it best in indication.
Now, I find it interesting, too, you're not stratifying necessarily by, you know, two prior lines of therapy, right? Which I think you look at the DUAD data, like, okay, well, it's enriched there. If I look historically in some of these trials, that's usually about 25%, 30% of patients. I would say, oh, well, you know, you guys can enrich for that and make it 40%, 50% for this subgroup of patients who are refractory. You're not saying that, though, necessarily. It's more about prior treatment rather than prior lines of therapy. But how are you thinking about getting what percentage of those refractory patients are you targeting for your skyline trials?
Yes. So overall, naive refractory, about 50-50 in terms of the demographics. Now, for stratification in a phase two study, you can't stratify for too many things. So we can only stratify for two features here, which is severity of disease at baseline and then naive versus refractory. So those are stratification factors. We think those have the best evidence for mattering in terms of impacting response rates in IBD, and I think that sets us up well to have a reasonably balanced set of cohorts across the trial.
Understood. Now, when we think about kind of contribution of components, what's also kind of interesting to me is, look, when I look at your indications, there's somewhere I feel like there's a dose response, right? And I think you can see that with your Intivio. There could be other targets where maybe not so much. tl1a i think signs of a dose response but it's more tbd you get into this kind of interesting question of hey i need to show contribution of components in phase three when i think about that contribution of components do i take two monotherapy arms maybe one that's under dose and then when i go to my combo i might be able to take the high doses in in combination compared to, let's say, a mid-dose on my mono arm. Is that regulatory flexibility exists? I mean, you look at the FDA guidance, it's almost purposely vague. But to me, there seems like there's some shades of gray here. How are you guys thinking about that?
Yeah, I think in IBD, we're learning, right? These are the first combinations that are advancing the J&J combos, the first one going to phase three. And so I think that is the most helpful precedent to understand what's required from a regulatory perspective. And, you know, outside in, reading through the lines of their phase three design, so on the back of the Vega study, both duet trials, and they ran an affinity study in psoriatic arthritis as well. Technically, none of those four phase two studies hit their primary endpoint of the monotherapies, both beating placebo and then the combo beating both of the monotherapy components. And yet what we see in the phase three design is a relatively straightforward phase three. It's a two-arm study comparing just the combination to tromphaea alone. And I think what's helpful there is it implies some amount of you can solve contribution of components in parts, meaning in the phase two studies, they showed that the monotherapies have beaten placebo, and then they showed that the combination beat glimumab alone. And now in phase three, the only comparison that they need to show is the combination against tromphaia, which they have not shown on a primary endpoint to be successful. So, you know, in our study, you know, the intent of this phase two is to solve contribution of components. I think it's a robust, well-designed study where we have placebo, monotherapies and combinations in one study. Our high doses of our monotherapies are the doses that we're studying in our combination dose. And so I think if successful, I think we could have said we've achieved contribution of components with this phase two study. I think that would enable quite a bit of flexibility in terms of what we choose to advance in phase three. Understood. And
I mean, given the dose response in that, because you also have to think about what you can kind of co-formulate in your phase three in these IBD indications, if you were to pick an ideal kind of monotherapy comparator arm within your own subpopulation, which one would
that be right now? Yes, I mean I think it is critical in terms of combination therapies about how you think about the ultimate product profile of what you're able to do, and I think we're uniquely able in that we have long-acting versions of each of these where we pick the antibodies ensuring that they were able to co-formulate with the others at high concentration. That was a unique background. I mean if we just think everyone in this space saw the Vega results and said let's start making combos and combine basically what they had or tried to gobble together different combinations and you see that with some of the other combinations in development where you're seeing mixtures of different dosing intervals even orals and injectables together and that is very challenging from both a convenience and adherence perspective but even a pricing and access perspective it's challenging if you can't administer these as a single product so I think we're uniquely able to do that with kind of you know long-acting versions of the best biologics and I think that sets us up very nicely here in terms of which one the winner is that's why we're testing them all head to head against each other i would say a few months ago most of our advisors would have told us that the alpha 4 beta 7 combos may not work so well in crohn's disease and so your tl1a il 23 combo might be the overall winner i've always been a little bit skeptical because i think intibios is still a big drug in crohn's disease their data if you don't look at the week six endpoint but if you look later at week 12 and 14 where some of the others use their primary end points, I think it looks quite good. And it's always seemed elegant to me that in a combination one of your agents is gut selective and very well tolerated if the other is a systemic immune suppressant. So, you know, given that the AVI data suggests that an alpha 4 beta 7 IL-23 combo shows additivity in Crohn's, you know, I feel pretty good about all of our agents across both UC and Crohn's. And we'll, you know, we'll see the data head to head across the three different combinations and then decide maybe not what the winner is, but at least what our favorite is to go first, and then maybe second and third, depending on how good they each look.
Understood. My question is a bit weirder, which is, in some sense, you want that comparator arm to not have as much of a dose response, right? So the question is really, because again, to your point, no pharma company yet has shown contribution to components. There's a lot of positive trends, not yet a positive phase-free trial. So when you think about, hey, if I'm think the regimen that I want to compare to that I feel most confident I'm going to be showing a contribution that might be that there's additive synergy right like it you're testing three different combos here what's the comparator arm that you think will set you up the most to show
that contribution yeah I know it's a tricky question I don't think we're going to be able to take a lower dose of our monotherapy as a mono and compare that to a higher dose in the combination, that'd be a little disingenuous. And I think in general, one of our core hypotheses here is that the better components will translate to better combinations. I actually think the J&J data supports that. When you had a relatively ineffective symphony arm as a monotherapy, the combination didn't add that much on top of TREM-phia. And so I think the fact that we're seeing what we think are excellent efficacy with our initial readout on alpha 4, I think it's reasonable to believe that that will translate to greater efficacy for the combos as well that include that component may make the mono harder to beat but in the end I think ultimately physicians aren't going to look at the delta of your combo versus your components they're going to look at the label of your combination product against the label of other combination products in the space and ultimately you just want that to show the greatest efficacy possible with the fewest safety warnings and the best convenience and I think I think having the best mono therapies is likely
to lead to that understood um that totally makes sense now i think maybe stepping back i'd love to get also your take on you know that api data set which again very provocative because these are exactly the combinations you're looking at you see a doubling in terms of response rates but then it's also it's hard because you look at even the monotherapy efficacy that you're seeing and it's not comparable to some other historical trials with either of those um targets so you know the This kind of signal-noise question is tricky, I think, for us and I think for investors to really interpret. How does Spire think about that?
Yeah, I mean, the challenge is we really don't have a total data release from that. We got one data point from a two-thirds enrolled study at a different time point than we've seen for others as well. So I'm encouraged to see this proof of concept that Alpha 4 provides additivity on top of IL-23. I might have assumed that anyways. I mean, I think these are very orthogonal mechanisms, and it makes sense to me that they could work well together. But, you know, it's very encouraging. That's that I think it's really hard to know without seeing more than just one endpoint at kind of a not not a complete disclosure of the results.
OK, understood. Now, maybe kind of just stepping back, there's this kind of question. You have two additional monotherapy data sets that are coming out. And, you know, the question I often get from investors is, oh, is that going to be a big catalyst? And I personally am a little more, I think, tempered, where I feel like when I look at TL1A, when I look at AL23, you've already seen some of those, you know, dose exploration trials done by your peers, where you're dosing IV, you're really hammering these targets. So I'm not necessarily sure we're going to see a clear dose response in the same way that we saw with your Intivio with these other targets. Is that the right framework? How should we think about those two data sets?
No, I think that's right. I mean, in contrast, I mean, alpha-4, beta-7, as we've talked about, we see both in the Gemini studies and in the real world that they have this very striking exposure response and a limited, you know, exploration of higher doses, even, you know, in the BLA, FDA suggested they should test a higher dose, and that never happened. In contrast, you know, in the TL1A case, we've seen three first-generation molecules. Some of them dose, frankly, an extraordinary amount of drug in the induction setting. You know, if 8 grams of antibody isn't enough to saturate the target, I think, you know, that'd be a surprise to me. So I think we're likely at the plateau in terms of induction efficacy for TL1A with what we've seen in the first-generation molecules that I think look comparable on a placebo-adjusted basis. And so I would expect our molecule to be able to do that with a lot less drug, given the improvements in the molecule from a bioavailability, immunogenicity, potency, and half-life perspective. And similar for IL-23. Again, three first-generation P19 inhibitors. The deltas and efficacy are pretty small between them. The most likely place that lands on a dose or exposure response curve is at the plateau. It'd be weird if they were all at the same place on that curve if it's not at the plateau.
Understood. And maybe to that point, I know there's limited you can say about the dose and exposure you're taking often for competitive reasons here. But when we think about, let's say, the high dose of Teva with their TL1A trials, are you testing doses that get meaningfully higher exposure than the highest dose that Teva looked at?
I mean, the Teva one is particularly hard to comp against because the peak to trough ratio is huge given the short half-life of the molecule. So on average, yes, I think we'll have at least the same, if not better, target exposure, but we're nowhere near the C-max levels of the antibody. And I think that's one of the advantages. I mean, you know, again, coming back to what do we think would these combo products look like, there's a big advantage of having highly potent, long-acting, co-formulatable antibodies and that we can actually get to reasonable doses of sub-Q co-formulations. If even one of your components requires grams and grams of drug, very difficult to imagine how that becomes a very convenient format. And it's not just kind of that one TL1A that we're discussing. Some of the IL-23s are dosed in terms of grams and grams of antibody. Hard to imagine how you could ever get to a sub-Q induction, whereas I think with our profile, I think sub-Q induction is doable, even with two agents together. And that's only a handful of monotherapies are able to do that.
By the way, I thought of this question right now, so I apologize if it's a bit unpolished. But there is, I think, I remember reading some clinical papers that there is this kind of thesis that in TL1A, we've talked a lot about ADAs, we've talked a lot about potency and half-life, but there's also competitive binding. And I think there's a hypothesis that, you know, when we look at the Teva-Sanofi data, part of the reason it was so good was actually that it was a non-competitive binder. And it wasn't about the ADAs, it wasn't about the potency. How much do you ascribe to that theory? Can you kind of give investors a bit of background on what that competitive binding dynamic is and then apply it to your programs as well?
Yeah, I think when the TL1As were all running their proof-of-concept studies, there was a lot of debate around a few things about the epitopes they're binding to. Is it the trimers versus the monomers that you're blocking? Is it DR3 versus DCR3, the decoy receptor as well? And I think there's been a number of publications from some of these sponsors either claiming it matters or claiming it doesn't matter in both directions. I tend to look at the phase 2 data on a placebo-adjusted basis that, you know, in my interpretation are within low single digits of each other in terms of their efficacy and think, I'm not sure it made much difference in terms of the efficacy of this and that you block the target one way or the other and you lead to a very similar efficacy safety profile of the molecules. So it's hard for me to ascribe much to any of those mechanistic differences until we actually see some separation in terms of their impact clinically.
Understood. Maybe just on TL1A and ADAs, and again, debatable if they've had any impact at all, but I know your team and the Paragon team, when they think about designing molecules, why not optimize when you can? Can you talk about, A, do you feel like there is any evidence ADAs are having an impact on clinical advocacy, maybe in certain indications or maybe in maintenance? And then number two, how did you design your molecules to avoid that, some of the dynamics we've seen with the Roche molecule?
Yeah, so the evidence that it matters, I think, is scant right now in terms of knowing that you're seeing a decline in efficacy due to immunogenicity. I don't think we have that yet, and I expect we'll continue seeing data from Roche and others suggesting that they may not be seeing an impact from it. The ones where I think it's clear that you do see an impact, actually, we have two TL1A bispecifics where the immunogenicity is yet higher again than the monoclonals are, and there you're not just, you are seeing clear impacts on PK and other effects that tell you that those ADAs are having an impact. I'm not sure we've seen that yet for any of the monoclonal TL1As yet, and so it's hard to say that we're going to see a major impact in, you know, due to lower immunogenicity rate. In terms of picking our molecules, you know, one of our funnel criteria, there's kind of a handful of in vitro assays that you can use to look at the formation of immune complexes between your antibody and your target called an sec malls assessment that you can do and so we looked at that for all of our antibodies and really what you're trying to avoid is the formation of these large complexes where your antibodies are cross-linking the target and multiple of the target to form these large complexes that's exactly the problem that was described for the amgen tl1a bispecific was the formation of these very large immune complexes so we certainly selected molecules that didn't have that that effect i think in our in our phase one studies, we've not seen kind of the impact of PK on any of, you know, the impact of ADAs on PK, PD, anything like that. So I think we were successful in that we haven't seen an impact.
Understood. Now, maybe kind of a secondary question. I do feel like in maintenance, and we've seen this with Sumi and Al-13, where you do see, you know, there's not necessarily a trade-off that a company like yours would have to make in terms of dose and then also target engagement. And maybe we could see continued improvements in terms, because again, you're healing the body and it just takes longer time. So help us frame, we have multiple maintenance data sets with TL1A coming out. Do you feel like we're going to start to see differentiation with some of these products in the maintenance setting where they are giving up too much on their dosing profile and you're going to see efficacy start to wane and is there a pitch internally that you might actually see the curves continue to go up given the engagement that you
have with longer duration yeah i as much as you know what i said for induction is true that i think we're at the plateau of efficacy for the target i think i'm not convinced yet we're there for maintenance for tl1a in some ways the overall maintenance data haven't lived up quite to the hype of the induction is some of the best induction in the space. I think for each of the first generation molecules there's different reasons why you might not be getting full target engagement whether it's the immunogenicity that we talked about or bioavailability, half-life relative to dosing interval I think in some cases a challenging and potency in other cases. You just may not be having enough target engagement during the entire dosing interval for any of those three. I think our molecules you know have excellent potency, long half-lives, low immunogenicity. You know I I think we'll be able to test whether that is the maximum maintenance efficacy. You know, when we look at the curves of responses, I know we've only shown the first one so far for alpha 4 beta 7, I mean week 12 is a bit of an arbitrary time point to pick in terms of efficacy. And you know, we see in our data that, you know, those curves haven't plateaued in terms of efficacy there. You're still seeing patients improve when you get there. Now, if you wait to week 14, I bet we would have gotten, you know, even nicer data with the alpha 4 beta 7. It wouldn't surprise me if we see something similar for TL1A and AL23 as well, that, you week 12 endpoint is pretty standard, but some people look at 14, some people look, you know, six I think was too early. So, but I think week 12 is a reasonable time and aligns well with our
Q12 week dosing. Okay, understood. All right, again, kind of random question that I just thought of right now. In terms of contribution to components, it seems like, okay, you have to show contribution to components within arms, but what if you went to the FDA and said, look, look, we have a combo that we're very confident is going to have best-in-class efficacy, and we think this is just kind of silly that we need to show contribution of components. Why not let us run a trial against the best biologic out there, right? Like, you know, run a trial head-to-head against Humira, run a trial head-to-head against Sky Rizzy, and if we're able to show an improvement on an active comparator, what are we doing here, right? I mean, I know that hasn't been talked about in the past, but again, this could be a different FDA. Is that even a thought process with your team?
Look, I think we're better off the more of contribution of components we show in this study gives us the most flexibility possible. So best case scenario, and look, we have three shots at this, right? We have three combos that I think all could provide the additivity that we're talking about. I think if at least one of them shows the contribution of components, that would maybe help us prioritize which agents are best to go first. You know, if you have that clean contribution of components in this study, I think we will have a lot of choices about what we want to use as a comparator for phase three. You know, I think historically you've seen placebos required for phase three development in IBD until very recently on the first combo phase three where it's not. It's an active comparator. And so I think, you know, we may have some flexibility here in terms of what we choose. I think, you know, our monotherapies, these classes have beaten the two biosimilars before. Alpha-4 beat TNF head-to-head. The P19s beat the P40s head-to-head, so we would feel confident in our monotherapies beating the biosimilars by a clinically meaningful difference, which is about 10 percentage points. If our combos beat our monos, we could choose just about anything as the active comparator for our combos, and there is a trade-off between nothing. Very few other things can be dosed on our dosing interval, and so it's some amount of operational trade-off versus what do we want to beat from a pricing and access perspective.
Understood. Now you mentioned you have three phase three combo studies readout next year. I know the street and we're personally quite excited about those readouts. But I also have to say, you see the pharma companies miss on the phase threes showing contribution to components. The expectation that you'll show a stat sig difference in phase two, to me feels, you know, is that misaligned? Have you designed these trials so that your phase twos should be able to show contribution to components? Or is the right perspective, we're going to be looking for trends. And, you know, an eight-point difference in, you know, a phase two trial is easily designed. You know, we can easily design a phase three to hit that bar. So should we expect statsing contribution to components with these phase two readouts?
Yeah, I mean, I think the more of that we show, the easier it will be for pivotal design in terms of our end of phase two discussion about what we have left to show in phase three. So, you know, I think this study is reasonably designed to show our monotherapies beat placebo. We know roughly what to expect for each of those. I think no one knows exactly how much the delta is between what our combos and our monotherapies are. And by the sizing of the study, you can tell that they're about the same size of the combination cohorts as the monos. and therefore we need to see roughly a similar delta between the combos and the monos. I think that's reasonable. That's roughly what we're seeing in the Vega study in terms of rough additivity. I don't think we need to see that larger result to have a stat-sig difference. The more we see, the better. Things we don't see, we could solve in phase three.
Now, again, you have a unique problem. Let's say that you do have a clear signal with all three. Part of me thinks, why not develop all three? I mean, really. They all could be best-in-class profiles, but patients want a different choice. I know in the past, the last time we had this discussion in Miami, you were kind of saying, look, I'd rather go with, let's say, an Intivio AL-23 backbone because I don't have to worry about long-term safety with TL1A, which is still going to play out. Do you still have that same view? I mean, what do you think about if you have similar data sets with all three combos in terms of which ones would you move forward with?
Yeah, I mean, the rate-limiting step for development in IBD is recruitment. I mean, it takes a while to enroll IBD studies, and if you tried to enroll three big Phase 3s at the same time, they would all take a long time. So in contrast, what we expect to do here is not necessarily pick the winner from the Skyline study, but think about which one comes first to the Phase 3 study. You know, there's 500, 600 good sites in the world. I think we would start enrolling what we believe is the most valuable product first, and then if we believe the next one was justified in terms of the peak sales potential justifies the cost of the phase three, then we would do that one and so on until we got to a product that we didn't think could return the cost of the phase three studies. Now, I think what's helpful is this is a huge $30 billion plus market. The largest drugs in IBD do high single digit billions each. I think it's reasonable that the best combinations in development could be in that range and that would be well more than enough to justify advancing those programs to phase three. terms of how we would pick between them, yeah, I have some slight bias towards the alpha-4, beta-7, IL-23 combo, knowing that we have tens of thousands of patients that have been on those drugs for years, and we have, you know, very few safety signals from those individually. And so, yeah, if we had identical data with that one as the TL1A combos, I would probably pick the alpha-4, IL-23 combo, but it's hard to ignore TL1A as a monotherapy agent as, you know, one of the best in the space. So I think it's plausible that we'll see greater efficacy with that, and we'll have
to make that trade-off. Understood. Now, RA study coming up. And I think most people appropriately look at this as, you know, a shot on goal, but not something that I've never felt for your team you had a ton of conviction on. You're like, we're going to test the scientific hypothesis. Let's see what plays out. But we are seeing, I mean, you saw with the FCRN data that there is investor excitement potentially in a refractory RA market, and there could be different pricing strategies there as well. So A, what data would you have to see with your TL1A and RA to justify moving that forward? Would it be as good a standard of care or does it have to be differentiated? And how do you think about, let's say, a broader RA opportunity versus maybe we should be thinking about this more
in the refractory setting? Yeah, it was encouraging to see market appreciating. The RA is still a market. I think there was a perception for a while that after TNS went biosimilar that that didn't exist and i don't think that's true and we see north of 15 billion of annual revenue of branded drugs post tnfs going biosimilar and we think that if you have a product that is two to four shots a year that doesn't have a black box warning and has efficacy in the range of the existing commercial drugs you know i think that could be a very large product in that space and so that kind of sets our bar which is that on safety and convenience we think tl1a is perhaps advantage in the space at least so far and so if efficacy is in line with the existing commercial drugs we think we think that could be a really attractive product to advance um yeah so we'll see those data next quarter and then we'll see the the PSA and Axpaw data the following quarter and that will define kind of the totality of what we want to advance at least in the rheumatic disease we'll also see as many as four other TL1A readouts across HS, AD, SSC, ILD and MASH between Merck and Roche and you know we could decide we think we may have a superior product and that that may make sense
to advance that one as well understood but it sounds like you're not sticking your neck out making any calls. Look, this is first in class. This is the kind of normal biotech
risk. We think the evidence is great across human genetics, human tissue evidence, animal studies, mechanistic rationale. But yeah, it's first in class and so it's a, you know, a different probability of success assumption than we certainly have in IBD. Understood. And by the way, when are we getting that
top-line data? Any more specific timing? Q3. Okay, Q3. Next quarter. Perfect. Hey, thank you. Thanks. I really appreciate it as always.