Hi, good afternoon. Welcome to the Jefferies London Healthcare Conference. My name is Dennis Ding, Biotech Equity Research Analyst here at Jefferies. I have the great pleasure of having NewAmsterdam Pharma here, and we have the entire team here with us. We have CEO Michael Davidson, CSO John Kastelein, and CFO Ian Somaiya here with us. Welcome. Thank you. Thank you. So before we kind of get into some of the recent developments, maybe you can just give us a background in terms of obicetrapib, the cholesterol market, and the unmet need there. Okay, I guess, yeah, I'll go first. The obicetrapib is a CETP inhibitor, and there's been a history to the class, which has been unfortunate with a number of disappointments. But we've learned a lot in the last two decades of research that it's all about LDL lowering with this class. And thanks to John Kastelein here, finding this drug at Mitsubishi, we're able to take it and move it all the way through now to the end of phase three. And what's exciting about the drug is it lowers LDL very effectively, but it's a lot more than an LDL drug. It lowers Lp(a). It lowers small dense particles almost 100%. It reduces the risk of diabetes, and it's extremely well tolerated. And so when you look at unmet need, we have a drug, obicetrapib, or obicetrapib in a fixed-dose combination with ezetimibe, which we released just yesterday, is it? Yep. Just yesterday, with 49% LDL lowering, we have a drug that can get almost everybody to goal, and so we now have statins and obicetrapib with a fixed dose combination, and you're basically done with all your lipid care that you need for your patients, and so it makes it a very simple PCP-friendly therapy, which is what we need in the field because physicians either have less effective oral therapies, which don't get the goal for most patients, or they have injectable, highly expensive therapies that require a whole amount of resources. Like I have a full-time nurse in my lipid clinic that does the injection, so it's not available for the primary care doctor. So we think obicetrapib and obicetrapib with the fixed dose combination is going to be a breakthrough, the first since statins, to really make the treatment of LDL-C elevation a lot more effective and getting most people to goal. But I would highlight just again, the attributes of this drug go well beyond LDL, and that's, I think, the exciting thing about it. And we'll have to see ultimately whether that translates into better outcome benefits, but that's our hope with a drug like this that has a lot of intriguing benefits as well. Dennis, you asked about the opportunity, so just quickly on that, 30 million individuals in the U.S. who are on treatment today with a lipid-lowering therapy, and as we've described before, 90% of them are above their LDL goals when you look at the most conservative goal, which is below 55 mg/dL. That's really what obicetrapib can do. Again, that and the combination can allow most of those patients to get to goal. Perfect. What's really interesting is that you guys have three phase 3 readouts within six months. I think that's incredible. You guys had a positive update yesterday with TANDEM, so maybe just kind of go over the data there. I know you mentioned around 50% LDL reduction with the combo, but perhaps give a little bit more color on the different arms there. Yeah, John. Yeah, so it was our phase 3 trial for the fixed-dose combination, which is 10 milligrams of obicetrapib and 10 milligrams of ezetimibe. It was a 400-patient trial where patients were basically on high-intensity statins, so they were very well treated already. And then 400 patients were randomized into four different arms: a placebo arm, an ezetimibe-only arm, a monotherapy arm for obicetrapib, and then the fixed-dose combo arm. And then you basically had to hit all statistically significant differences for the comparisons, all four. So the comparison between the fixed-dose combination and OB alone, the fixed-dose comparison versus ezetimibe, and the fixed-dose comparison versus placebo, and the comparison between OB mono and placebo. So we needed to hit four p-values, and if we would have not had one p-value statistically significant, the trial would have been a failure. And so we did hit them, and we all hit them with very statistically significant lowering. And as Michael was saying, the fixed-dose combination compared to placebo was a 49% LS mean difference, which basically tells it cuts your LDL cholesterol in half. And the other arms did exactly what they did in our previous trial program. So one of the things of this drug is its consistency. And basically, the only data I saw at Mitsubishi when I was kind of perked up was the efficacy data in phase 1. And in fact, from phase 1 through phase 2, now into two phase 3 trials, if you look at mean and medians for LDL lowering, it's extremely consistent. And then if you look at safety, so the safety for the fixed dose combination, again, if you look at total percentage of side effects, was in fact less than in placebo, which of course is not possible. So what we say is it is just as safe as placebo, which was also true for our other phase 3 trial, the BROOKLYN, and for our entire phase 1 and phase 2 program. So one very important attribute Michael was saying that for a doctor, if you have a patient on a statin that's not at goal, you can either give OB monotherapy or the fixed dose combination to get that patient to goal and forget about all other therapies. But not only that, it's extremely well tolerated and safe. I think that this is the second phase 3 trial that shows how safe the drug is. And if a doctor wants anything, it's a patient that is not calling him at 10:00 P.M. to complain about his left cough, but actually don't come back at all in terms of safety. So that, I think, is also a very important readout of this phase 3 trial. I'll just go back to the BROOKLYN data set, which we presented at a late breaker at the ACC Monday. And there you saw not only that the reduction in LDL has been obviously quite consistent, we're also seeing a similar consistency with the Lp(a). So this is a drug with a fixed dose combination that cuts LDL in half. And with mono alone, we're able to cut Lp(a) in half. And that's what makes it very attractive to patients that have multiple risk factors that go above and beyond just simply LDL. Right. And can you remind us how the TANDEM data, at least for the obicetrapib monotherapy arm, compare to BROOKLYN? And how comparable are the two LDL reductions seen in those trials? Yeah. Go ahead, please. Yeah. In fact, the reason why we highlight not only the LS mean, but also the mean and median data is because the LS mean is the primary endpoint. It is what we agree to with the FDA. It is the standard to which all lipid-lowering drugs are held, and that is what is going into the label. If you want to predict what your drug is going to do in terms of outcome or endpoints in the MACE trial, that is based on the mean difference to placebo. If you look at the mean difference to placebo for the Tandem trial, the Brooklyn trial, or our entire phase 3 program, which was four trials, it's exactly the same. It's very consistent. The LS mean uses imputation of retained dropouts. If you have a little imbalance in a small trial in terms of the number of dropouts, then the LS mean might fall a little bit below. Looking at the mean, then you see actually what the simple differences of all patients in the trial, and you see that that's very consistent. Right. I think there was a little bit of confusion yesterday, and you could also tell by the stock reaction around mean versus LS mean, if there were any differences in how you guys were communicating the data. But the bottom line is LS mean is the primary endpoint. That's what the FDA cares about. That's what goes in the label, right? And when you compare TANDEM's LS mean versus BROOKLYN's LS mean, it's actually very similar, around 35%, 36%. Right? Is that fair? But what you guys were pointing investors towards was mean, and that's important because that's the predictor of a MACE benefit. Yeah, the CTT. So the Oxford group has done what's called a CTT meta-analysis. It was a Lancet paper in 2005 and later one in 2016. And then we have the REVEAL data, the other CETP inhibitor that was published in the New England Journal. And you make a line, a meta-regression line where you have absolute LDL difference on the x-axis, and you have the MACE benefit on the y-axis. And that is based on the mean difference very often taken at year one. And so if you want to know, if you want to put your trial on that line, you have to know the mean difference in LDL cholesterol. You mentioned mean difference at year one. Did you guys disclose the 52-week or that there isn't a 52-week TANDEM? People use six months also. Six months also. Yeah, it's really the time-weighted LDL lowering. Yeah, time-weighted LDL lowering. So that's how we think about it. So then moving forward, you guys will have another phase 3 readout, BROADWAY. This is the bigger ASCVD, more relevant apples-to-apples comparison with PREVAIL, which is your cardiovascular outcomes trial. So given that you have BROOKLYN and TANDEM both positive and you got the various reductions in LDL, how do you feel about the BROADWAY data going into that? Because that's coming in Q4. I would say, first of all, the LDL lowering, if you look at means and medians, should be very similar. It's always been. LS mean, we can't predict. That imputation is so hard. If you understand how it works, it's very complicated. You do 100 different simulations, and you put a code in, and you use the retained dropout. So we don't know that part, but it should be with this larger trial, the LS means and mean and median should be pretty similar. When they have larger the trial, but more likely you get those numbers to come very close together. But I think what's exciting about BROADWAY is that it is our largest trial of high-risk patients. So it has that safety data on MACE. We had projected about 3.5% events, and that's basically what we got in the trial. We'll have events in the trial to look at, and we'll see how that looks on safety. That's going to be a really important element of that trial because it is the basis for approval. We will take that as one of the most important safety evaluations of the whole program. That's how. The only other thing I would add is given the history of the class, safety is obviously paramount, and we're talking about a patient population, which obviously is asymptomatic, so this is the definitive answer in terms of safety before we get to PREVAIL . Okay, and to remind people, this is monotherapy, obicetrapib 10 milligrams and placebo. But in a two-to-one randomization again. So we'll have twice as many patients on obicetrapib as placebo, which together with BROOKLYN will give us about, we need 1,500 years of safety for the FDA, and I think we are over 1,600 with that total database. So we actually meet all the standards of the FDA requirements for this. Yeah. Right. Okay. So then in terms of efficacy and LDL reduction, I mean, I think most people can agree that the study is probably going to be positive. It's probably going to hit stats. So the question then becomes, what is the magnitude of LDL reduction? And you feel pretty good that'll be pretty much consistent with what you guys have shown in the last few years. Yeah, mean and medians, yes. That's how I think about it. But that's a bigger trial. It's a higher risk population. I think we ran an excellent trial. You get drop-ins, you get dropouts. So you have to kind of manage that. And that's the thing that we think we did a really good job with that study doing that. That's what we have to deal with in a trial like that. The nature of studies are very hard these days, are much harder than they used to be because people are on all these other drugs. And so we just have to wait and see. But if our medians, I think, is the best to show consistency because that takes out the outliers anyway. Mean, of course, takes in all the patients and what happens to them during their trial where they go on and off other drugs and so forth. We hope to see consistency across the mean and the median across all our other trials. Brooklyn, of course, was a one-year trial, and it worked out extremely well. We have confidence that we're going to have a good study. That's what it comes down to. We'll know fairly soon. We're still analyzing the data. Yeah. And Dennis, look, we're all playing the game of connect the dots. What is the study data today? Tell us about the next one. So as we think about connecting the dots from BROADWAY, ultimately what matters is PREVAIL. And the consistency of the data we're seeing today gives us confidence in BROADWAY. And those results should give you confidence in ultimately what we'll disclose with the PREVAIL data set two years from now. But I think what is important, I think to emphasize again what Michael said, is that what we've seen in our phase three program until now, and especially in BROOKLYN, is that the drug not only lowers LDL, but it lowers very significantly Lp(a) too as well as particles, especially small particles. We've shown all those data at the American Heart Association. So the drug is much more than just an LDL-lowering drug. And then we haven't even discussed the prevention against new-onset diabetes, which is probably related to the HDL part of the drug, and that might be related to other things that we're currently investigating. So the drug is much more than just LDL. And if we forget about the outsides of the periphery, the Lp(a) we've now seen that in five trials. And in fact, the best Lp(a) numbers we see in TANDEM until now. These things, of course, the moment the HORIZON trial by Novartis reads out in the summer, then we will know the relation between Lp(a) lowering and MACE reduction. If that is an established fact, then everybody will understand that our Lp(a) lowering will also confer something that is beneficial. That will be also an important readout for us, of course. Right, right. Because when you look at the biomarker profile overall, you guys have very strong improvements in everything, right? And regarding Lp(a), you guys have around 45%-55% reduction. However, that's not necessarily for an enriched high baseline Lp(a) versus HORIZON and some of the other Lp(a) target therapies are enriching for that. So can you talk about Lp(a) specifically, your thoughts on that being a predictor of MACE possibly, and how your level of reduction in PREVAIL, what ballpark incremental impact would that have on MACE benefit? The only thing I can share with you that is published is that in a post-hoc analysis was estimated how much the Lp(a) reduction that the PCSK9 inhibitors confer, which is about 20%, how much that contributed to the outcomes in ODYSSEY OUTCOMES, which is the outcomes trial for alirocumab, the Regeneron Sanofi PCSK9 inhibitor. They estimated that out of the total event reduction, 15% was contributed by the Lp(a) lowering. Now, that Lp(a) lowering was just 20%. And so I would think that it's reasonable to assume that our Lp(a) lowering would contribute more. But of course, in order to say precisely how much more, we need the HORIZON trial to show us a regression line to show us what Lp(a) lowering translates into what event reduction. The moment we have that, then we can look at our distribution of Lp(a) in PREVAIL, and then we can apply the regression equation from HORIZON to our levels in PREVAIL, and then we can do some estimate on what the Lp(a) lowering would contribute. But at the current time, we can't do that because we still don't have the HORIZON data. But we can at least say that it's very likely to be more than 15% of the total event reduction because that's already reasonably being shown for the PCSK9 inhibitors. So 15%, do you mean like 15% of the 15% risk? No, 15% of the 100% that. So 15% of the event reduction that the PCSK9s confer. Okay. It's an incremental benefit. Incremental benefit. Okay. Interesting. So if we kind of take a step back towards BROADWAY, and Michael, you mentioned you guys will share some MACE data. How meaningful is that MACE data as far as the safety disclosures? And should investors draw any conclusions from that? I mean, if you look at the data, there's typically not much of a benefit in the first year. I mean, the modeling would suggest maybe 0.91 benefit. Anything below one would be great that proves the safety of the drug. We'll have to wait and see. It's going to be a very exciting part of our data presentation when we talk about not just the LDL, but the MACE benefit. That's kind of how we would think about it. It's not a we don't know until we see it. I mean, we'll have to find out when we get it. That's what it comes down to. Maybe to answer the second part of your question in terms of how investors should think about it, I don't think we can prevent investors from thinking about it and interpreting it. Yeah. Yeah, I'm just a little bit nervous because you're working with small N, sometimes the delta could be small, sometimes it could go the wrong way. And it doesn't mean the drug isn't working. It's just that one year is just too short for the curves to separate. Right, that's true. It's all true. That's true. That's all true. Yeah. That's why the European authorities say that you need to exclude an upper boundary of the hazard ratio of 1.8. So they acknowledge that in trials of small numbers and a lot of other things that happen, that sometimes it can fall above an odds ratio of one, but you have to exclude an odds ratio, the upper boundary of the odds ratio of 1.8. So you're absolutely right with what you're saying. So anything below one would be spectacular for us. It's also not uncommon for it to go the wrong way initially, and then it kind of flipping back towards a benefit, right? I think ezetimibe, or not ezetimibe, obicetrapib. Yeah, they had 23 deaths or something like that in their phase. Yeah, no, it was the outcome study, it was. It worked. It didn't have a death increase. I mean, so you can get some safety issues. We're hoping that doesn't happen with us. Yeah. So then obviously what a lot of people are focused on over the long term is PREVAIL, right? So can you speak a little bit around the trial design, how you designed this, some of the rationale behind the design choices, and maybe also talk about some of the event rates that you have been seeing? Are they tracking in line, below, above, just any color on that? Yeah. I mean, first of all, the event rates are tracking. It's roughly 1,000 events to be powered for this 20% reduction. We're tracking right on the line for the events. And so what we did, though, we took a lot of learnings from the past. And these are very important because what we learned is that the absolute LDL lowering drives the benefit, not the percent lowering. So if you can have start off, the big issue with the anacetrapib Merck trial started with 61 milligrams per deciliter, dropped LDL by 17%, got an 11 milligram per deciliter drop in LDL, which worked modestly. So we designed the trial to have a higher baseline LDL, to have a 35% approximately LDL lowering, and then not even considering the Lp(a) or other benefits, small particles and so forth. We also put risk enhancers in there where the anacetrapib trial worked better. It worked better in people with diabetes, metabolic syndrome, elevated Lp(a), obviously elevated LDL or ApoB, hypertension, triglyceride elevation, so we selected patients to enrich the study to those we know would respond better to this drug therapy, and then we also know that people with heart failure don't benefit from LDL lowering, so we took heart failure patients out. They have high risk, and unfortunately, the statins, so far at least, have shown no benefit, so we took those out to reduce dilution of things that were not going to have a benefit, so we believe that with knowing all the experience that we have, we're able to design the study that won't fail the trial. That won't fail the drug. The trial will not fail the drug. That's how we set it up, that we have much higher baseline LDL, 103, much greater LDL lowering than any other oral therapy so far, and going long enough too, two and a half year minimum follow-up for this very reason. It's the first year you don't get much of a benefit, so you need to go at least two and a half years, then the second year, you get the full benefit for that year, then every year after that, you get the full benefit, so we went two and a half years minimum follow-up in the trial to maximize that benefit, so greater absolute LDL lowering, longer duration, risk enhancers, and also taking out patients that don't seem to respond to lipid therapy. Hopefully, again, PREVAIL won't fail the drug. That's our key. That's our key hope, the way we designed the trial. So then what would you say in terms of MACE benefit, what would be a good outcome for you guys? Or we're powering it for a 20% difference, but we'll have to see. We're tracking it, and we're seeing how the events are playing out. And so we're able to make adjustments if necessary with the trial. If you look at the last three outcome trials, the last was CLEAR Outcomes was 13%. Then before that, ODYSSEY OUTCOMES, 15%, then FOURIER, 15%. So basically, our kind of horizon starts at 15%. Now, of course, if we do the simple math based on LDL, we'll get over the 15%. But the bar is, in that sense, quite low if you look at the last three major outcome trials. Yeah. And then there's the incremental Lp(a) benefit if that works as well too. Exactly. Okay, perfect. Well, I think that's all the time that we have here. I just want to make a shout out to Philip Scheltens in the audience. He's our Alzheimer's expert and investor, actually, in the company. He helped us get going with. So one other thing that people don't talk about, which is fine, but we have an Alzheimer's biomarker study embedded in BROADWAY. And so in the first half of this year, because we have to run the analysis now, we'll have tau and amyloid beta 40 ratios. And if we see a benefit on these biomarkers, then we can then proceed with maybe another indication for obicetrapib because our preliminary proof of concept study, we thought it was quite exciting. We saw benefits there. And so Philip's been very helpful to us on this. And listen, we see this as a huge upside for us with that information. When will we get an update on that? That'll probably be like April, May, something like that. Okay. Internally, we'll get an update April, May. So we'll have to find an appropriate conference to present that data. Okay. All right. Perfect. All right. Well, thank you guys so much. That's all the time that we have. Thank you.