GUGGENHEIM 3RD ANNUAL HEALTHCARE INNOVATION CONFERENCE - NEWAMSTERDAM PHARMA CO NV

Thank you for joining Guggenheim's 3rd Healthcare Innovation Conference. My name is Moritz. I'm part of the therapeutics team, and it's my privilege today to host Jens Amaya, CFO of New Amsterdam Pharma, and Matt Philipp, head of IHR. Thank you so much for making time for us, Jens and Matt. And to start with, perhaps let's get everybody on the same page. Can you briefly summarize the status of your ongoing PREVAIL study and your plans for the upcoming interim analysis? Yeah, I'm happy to do that. So thanks again for inviting us and hosting us this morning. So it was great to get in front of investors and share with everyone the New Amsterdam story. In October marked my three years at New Amsterdam, and just reflecting on my short time here, it's amazing to see the progress we've made as a company and how close we are to delivering on the promise of OB and OB Easy. In those three years, we've had a company that's transitioned from delivering phase two data to now having completed the phase three LDL studies with our partner, partner Manarini, launching the drug in Europe, specifically Germany, by the end of this year. So it's a commercial reality, the drug will be available to patients. As it relates to the broader clinical program, I think that's the essence of your question, By the end of next year, we would have completed the remaining cardiovascular studies for opacetrapib, and these include the Rubens trial, which is a study specifically in patients with type 2 diabetes as well as those with metabolic syndrome, but no semblance of ASCVD. So this is a population of interest because there are 20, 30 million individuals that fit that risk in terms of have elevated LDL, have not had a previous event, but would benefit from a therapy like ours. The other trial is obviously PREVAIL. So we remain on schedule to trigger the interim analysis by the end of this year. And we expect to hear back from the DSMB at some point in the first quarter of next year. So really it's been a long trial. It's a trial that we're very excited about in terms of the execution of the study and the design elements which we think will support a positive outcome. And I know the investor community is very keen to see the results. You can imagine that we are even more. So that would be the next trial to read out for us. And then after that is Rembrandt. And Rembrandт is an outcome study for the fixed-nose combination. It's an imaging trial, and there's really nothing more powerful than an image, an image of seeing your plaques stabilize or potentially seeing plaques clear. It's akin to a cancer patient being able to visualize in an MRI PET scan that their tumors have shrunk. And that's a trial that's been conducted by others in this space that resonate with clinicians, that resonate with patients, and it's a trail that we think will have important read-through and carryover to the commercial setting once that data becomes available, and that would be likely towards the end of next year. Before we get more into Prevail, which is obviously top of everyone's mind, you already touched on Rubens, and that one's perhaps maybe flown out of the radar a little bit comparatively, but maybe just touch a little bit more on the commercial importance of that, especially as it sort of relates to the differentiation versus statins and the kind of diabetes impact that those drugs have. Yeah, so it's an important reminder that our drug does more than simply reduce LDL. And one of the benefits that we've seen of the class has been, and this is of the CETP class, a reduction in the rate of new onset diabetes. We saw that with the programs that were evaluated by major pharma companies in the past. We clearly saw that in our one-year Broadway study where we showed roughly a 15% reduction or in the rate of nuance of diabetes, and I can't emphasize this enough, there's a population at risk that has diabetes, that has elevated LDL, and if those patients were put on high-intensity doses of statins, their risk of converting from P-diabetes to diabetes increases upwards of 36%. So when you look at our Broadway study data, where the majority of the patients were on high-intensity statin for us to be able to offset that risk and reduce the rate of nuisance of diabetes. It's a benefit and an aspect of our profile that we think will resonate with patients and clinicians and provides an important point of differentiation versus the established class. So that's the statins, the ezetimide, as we look at the PCSK9s, where the benefit is really limited to just LDL. Makes sense. So now moving on to Prevail, and perhaps very topically, we just had AHA this weekend. One of the key readouts there was the Horizon study, which overall was neutral. But if you actually dig into the supplements of the New England Journal of Medicine paper, one of the subgroups that are shown is in the patients with more than 100 milligrams per deciliter of LDL-C at baseline, which is perhaps the population that's most similar to PREVAIL. Those patients actually did see a hazard ratio of 0.83, although with error bars that did overlap one, but still there appears to be some trend perhaps. So overall, what do you think the HORIZON data means for prevail and where do you see the impact of LP little a lowering of Obesetra Pivotal? Yeah, I think that's a good way to frame it. It was a silver lining of what otherwise was a very somber presentation. Since I didn't attend the meeting, I decided to spend time with family celebrating Diwali. I know Matt, you were there, maybe you can speak to it in more detail. Yeah I mean I think you know it is obviously a kind of a disappointment for the LP little a class, but I think if you looked at it, a lot of the concerns that we had were echoed, you know, by the presenters, by The Discussants at AHA is, you now, maybe they lowered LDL-C too much. You know, maybe, you, know, too many patients came off drug. So, it continues to be the question, was Pella-Carson the right drug to answer the question of lp little a i think as as those who attended saw you know there really was nothing there across every subgroup they looked at except for ldlc where they started showing a trend you know i think what was interesting is one of the discussions clearly laid out that if you look at lp a versus ldc and then you know kind of highlight the risk associated with as both those climb what you clearly saw is that as ld lc goes down you almost eliminate the lp little a risk but as lp little a goes down there is still risk left over and obviously lowering both together showed the greatest benefit so i think that that's interesting and as you noted as well you know as l p little a wins up the trend was for a better mace benefit and i think for us that that is encouraging as well but i think we all want to take a step back and remember at the end of the day prevail is just based on ldlc i think we did clearly hear from physicians that LP little a is still a risk factor and still a risk factor that their patients want something for. You know you may be able to tell your patient you know let's just focus on your LDL not worry about your LP little A but it's so ingrained that LP little is a genetic risk factor. That you know those patients seem to want therapy and I think being able to offer them something we'll see when the future studies come out you know how they replicate it are we able to gain more information but I think there's still a lot of unanswered questions that hopefully, you know, the next group of LP little a drugs are able to address. Yeah. And this is a trend that we also observed coming out of Broadway and Brooklyn. So when we published the analysis of the MACE trends in Jack last year, those patients that had higher LP little a, had higher baseline LDLs, those are the patients that benefited the most on OB. And what we don't know today is whether LP little A has a threshold effect. Is there a magic number that you need LPLA to get below for a patient to realize benefit from that treatment? And those are some of the questions that will get answered in the future with some of The Other Programs that continue. But to Matt, emphasizing Matt's point, the community is not getting away from LPLA. There was a focus, a heightened focus on continuing to monitor for LPLA and being aggressive with treatments. And the way these patients have been treated up until now has been to get the LDL to the lowest possible number. And what that means is a requirement, a need for branded therapies. And this is why we are launching not only OB, but the fixed dose combination with azetamide. And those two product forms allow patients to get their LDL to the lowest possible value. I think I would just add, you know, in terms of overall message or take away from AHA, I think outside of LP little a to Ian's point, there was still a renewed focus on being more aggressive on patients LDLC and getting patients to goal. And I think that's really continued from, you know, ACC last or this year where the guidelines have changed. So I think this aggressive therapy and treatment, I mean, if anything, it potentially was highlighted by Horizon that, you should be more aggressive with LDLC, even for LP little A patients, I think is you know a continuing theme and trend that we're hearing at the medical meetings. Yeah and I know you didn't ask about Zeus but I think it makes sense to spend at least a minute on Zeus. The learning and the silver lining there was if you looked at patients that did not have heart failure there was a clear trend towards benefit so and the parallels here are having the benefit of John and Michael be involved in this space and the early decision they made to exclude patients with heart failure, simply because those patients are too far along to benefit from an LDL-lowering therapy. So it's not just about the difference between an LDl study design based on the premise of LDL, which has been validated over and over again, versus LPLA, where this is the first time the question is being asked. It's also looking at how do you ensure, how doyou design a study to produce a successful outcome and that's another lesson that we need to keep in mind absolutely so let's talk a little bit about the upcoming prevail interim analysis you guided through a peak threshold of 0.01 for for mace 4. you haven't guided to a particular threshold for mace 3 but you do need to hit on both for the interim to be to be successful so can you talk a a little bit perhaps about that decision not to pinpoint the threshold for MACE3 exactly and where you see the likelihood of MACE4 and or MACE2 hitting based on the sort of blended, blinded data that you've seen to date. Yeah, yeah. I mean... Why don't you go ahead? It's okay. I would say, you know, when we look at the data, whether we look across sort of, you now, the CTT analysis, you kno, the REVEAL study, our Broadway study, our blinded data, they all point that we're heading in a very meaningful direction. And I think that really was the crux of introducing the interim. We wouldn't have introduced an interim if we didn't think there was a chance of being successful. And we've given ourselves that chance. I think from the statements we've said, and I'll reiterate here, is basically we are well-powered at the interim if we show a Broadway-like effect in both MACE 3 and MACE 4 to stop the study. I think that information there kind of tells you everything you need to know about where we could be, what our alpha is, how much we're spending. Trying to fine-tune what the exact number is doesn't really matter that much. At the end of the day, the only thing that's going to matter is, do we hit the stats at that interim? And if we do, hopefully the DSMB makes the recommendation to stop the study. But I think overall, there's not much we could give you the exact numbers, and that wouldn't change anything. I think the point is, there is always, by providing exact numbers it makes it seem like the stats are infallible. You know, there are always risks with statistics and we want to make sure people understand that because if we do get a continued decision we want help people understand you can't read too much into a continue there's a lot of reasons that the study could continue we could hit mace three you know miss mace four hit mase four miss mace 3 what we've known is we've seen several studies you know missed the interim unfortunately you know companies investors everyone kind of reads too much into that and then all of a sudden they're surprised when the end of the study comes around, and it's exactly what they were expecting. I think a lot of investors really remember Select. Some may remember Ameren. This was a very similar trend, and we've seen it through multiple other studies. So we don't want to make it seem like if you do this, you get this. All we can say is that we are well-powered with the stats that we have generated, and we're optimistic based on the data we've seeing. You've talked a lot about the trends that you're seeing in the blended blinded data, and that you've observed a slowdown relative to what you would expect. Can you talk a little bit more about that analysis, what exactly you've done, and what it means to have seen a slow down, and why that makes you comfortable? Let's start with the comparison to Broadway. And it's a good comparison because Broadway was designed to be a mini prevail, right? Nearly identical patient population. The two trials Those were enrolling patients at the same time, conducted at the at the sites. We used the same adjudication committee. So if there was a trial that provided a close comp peer to Prevail, it was Broadway. And it was by design. So what do we see in Broadway and how does that relate to Prevale? And this is something we shared with you. So when you look at the one year data and you look the MACE4 curves, you look MACE3 curves, you look individual components of it, they're nearly on top of each other, if not absolutely on top with each other. So, you know, check the box, the intended effect. We wanted Broadway to give us a roadmap to prevail and it looks like it has. We've shared, we've provided additional updates since then because Broadway was limited by time. It was a one year study. So as we look at what's happened since the one year mark out to two years, we're seeing rates continue to decline. And, you know, we can all come up with reasons why our rates could decline, and Matt, I would encourage you to go through some of those, but we do believe it's a drug effect. We believe it is a drug effect because the rates are well below what would be expected in this population when looking at contemporary studies. So it's, again, it's not a single point. It's not single data point. It's looking at all the individual components and they're all going in the right direction. But I think, Matt, you should speak to what other factors could implicate and why we don't think those apply here. Yeah, I think there's a couple of ways we've looked at that statement of the lowering rates. One, we can look at, fortunately, we're in an enviable position, sometimes to a detriment, that we have so much information about LDL-C reductions. And there have been so many cardiovascular outcome studies done in this space that you can actually build very good models about what should placebo patients do in these populations you can either look for it and say let's compare sort of the rate of placebo decay because placebo does decay over time in the outcome studies particularly from year one to year two it's more linear in the out years and it's actually more stable in MACE3 than MACE4 but overall you can look at that and say how is our placebo rate behaving or how isour blinded rate behaving relative to other studies, placebo rates. And if we see something that is below that placebo rate, then the question is, how is it there? You know, for us, and I'll go into the other two points. I mean, there's three, there're three things. It could be standard of care has improved driving down placebo rates, it could be drop ins are driving down placebo rights, or it could be effect size is driving down your blinded rate. And, you know, for us we can kind of exclude standard of Care and GLP-1, and I'll talk about that. But what we're seeing is our blinded line is trending below. Now, there's always, you know, a lot of, you have to be very careful with looking at blinded data. I'd say the best thing we have, though, is there's all those caveats to head-to-heads comparisons. And I mean, Ian highlighted it well. We have Broadway, and that's a good starting point from there. You can also look at it and say, if we adjust all these factors, you now, all these variables based on our risk profile, what would we predict our placebo curve could do? And if we do it both those ways, we see it's lower. Now, the big concerns I know a lot of people have are standard of care and drop-in rates, particularly drugs like GLP-1s. I think drop-ins are easier to explain. Our drop-end rate is around 1% a year. That level of drop-ind rate is almost inconsequential in your overall event rate. You'd have to assume that all of your drop-ends happen in the first day and they all go to placebo arm. And even still then, you know, a 1% rate in a 10,000 patient study is less than one basis point of potential impact. But we know GLP-1s from Broadway, from other studies, you're just as likely to get them in the active group as you are in the placebo group because these studies are well balanced for BMI and diabetic risk. So you're not going to preferentially go to the placebo groups. So drop-ins are not there. And we've actually seen from other studies, the drop in rates, you know, haven't really probably impacted things as much as well, especially for studies like Visalius and other LDLC studies. You know, I know Zeus highlighted it a little bit there, but you have to remember their SGLT2 drop in rate was so high because 40 plus percent of their patients had heart failure. So they were really trying to treat the heart failure and that's what was driving that a little bit. The other question is standard of care. And I think what's interesting about standard of care is it does look like event rates have gone down over time in terms of MACE, but that can almost be completely explained by your LDLC baseline. And so even, I mean, actually interesting, even Horizons baseline MACE rates on that above 100 group was in line with exactly what we would expect for that group. So it tells you, even though those companies were out there saying, like, standard of care is driving down event rates. Well, it was driving down event rates as you were driving down LDLC so much. So I think we can see now even more recent studies. I mean, Vesalius is a great point as well. You know, the recent studies, if you adjust for baseline LDLC risk, you know, MACE rates have been pretty consistent over time. And that actually goes with the anecdotal data. We know standard of care has not actually improved. We knows mortality has been increasing for the last decade. You know, PCI procedures are relatively the same. So standard of care hasn't changed. What explains your event rate is really based on your LDL-C. Makes sense. While we're talking about sort of recent studies, one that's come up also in a lot of discussions that we've had is the ACCELERATE study. If you look at just the headline number of that study, placebo-adjusted, you see a 37% decrease in LDL-C. You see a 19% change in APOB, which maps pretty closely with what ObesetraPib has shown. But it turns out the Xcelerate study was stopped soon after two years, but it was neutral. So why do you not view the Xcellerate study as a good analog for Prevail? What are the key differences that investors need to be aware of? Yeah. I mean, obviously, I encourage Matt to contribute to this. The most important is just the method that was used to measure LDL. So the direct method, which was used by Lilly in that study, did likely overstate the LDL reduction. That was sort of the true effect of the drug. And that's why the industry's moved away from the direct matter to beta-quant, which is what every other subsequent study has used and what we have used in our trial. So I think that's first and foremost. The other is the one you highlighted, which is a study that was too short in duration. It stopped at the two-year mark, and it's a question that will remain unanswered. Were the trial to be extended? Were the trials to be allowed to run longer? And you look at Reveal as a comparison, four to six year study, which ultimately showed a quite robust treatment effect, would evocetrofib or Accelerate been similarly successful? The other is there's just not a lot of details that are available from that trial. So we don't know, and this is a great question for Lily, not for us, and what else could have contributed ultimately to that trial's failure? And this is why I give Novartis a lot of credit for being as forthcoming as they were at the podium and providing not only the detail at the AHA, but also publishing it so we can all learn from that experience. Yeah, the only thing I would add is, you know, it's not uncommon for studies to take longer than two years. Improvement also took longer than two years to show separation. So I think, you know, there's probably a combination of multiple factors, you know, and it's just unfortunate. There's certain things that we can't exclude, you know, we can exclude that there is some sort of molecular difference with evacetrapib and something that the molecule was doing, because we don't have that data. We have that data for anacetapib. We don't know what their true LDL-C reduction was. The disconnect between their LDL C and their ApoB is pretty staggering. They said 37 with direct and the 18% or whatever with their ApoB. Anacetrapib said they were 41% with their direct assay and around 18% with our Apo B, but their beta quant number was actually closer to like 17, 18%. So I think it shows you can be drastically off with that, but we just unfortunately don't know the answers because we don't have the data. I think we have a lot more data of our own, a lot more data from Anacetrapib and Reveal, but I think ultimately there could be one or many factors that contribute to that difference with Anaceprapib, I mean, Evacetrepib. Makes sense. So now that we're either going to get an answer at the interim or at the final analysis, can you just remind us in either of those two scenarios what does the NDA submission timeline look like for you sure sure so the strategy is and this goes back to the reasons why the outcome studies were started at the same time as the ldl it's rare to have a company be able to deliver share results from the outcome study at the time of launch that's an important opportunity that we want to fully leverage because it does provide peer access it drives peer access and it drives ultimately adoption. So as we think about the prevail in the two timelines, the interim or the final, I think what's great is they happen in the same calendar year. And I think that's sometimes it bears reminding. So either we'll know the DSMB decision and or we'll know the decision in one queue and the trial would stop or we will have a study that concludes by the end of next year. In terms of the filing strategy, if the timelines are driven by a positive interim analysis, will obviously file for approval as soon as possible. 90% of the application in the US is the same as the one in Europe, so you can imagine a lot of that work has already been done, and we would want to wait to hear from the DSMB confirming the trial completion and be able to follow through with the filing. In terms of if the trial were to continue to the interim, sorry, to the final, that's a conversation we need to have with the FDA. whether we are able to file in advance of the trial completing, or we do it concurrent with the completion of the study. Amazing. Well, thank you both so much for taking the time to speak to us today. Looks like we're at time already. All right. Thank you, Moritz. Really appreciate this. Thanks for having us.