Great. Welcome everyone to the next session here. It's a pleasure to be joined by the NewAmsterdam t eam. With us we have Founder and CSO John Kastelein and Head of IR and EVP, Matthew Philippe. You know, very interesting time at NewAmsterdam, so looking forward to it. Maybe John, if you wanted to just give a kind of a quick overview on NewAmsterdam, kind of where things stand with PREVAIL, and then we can dive into Q&A if that works. Definitely works. We are currently in the exciting phase when we have concluded all our pivotal, lipid-lowering registration studies: BROADWAY, BROOKLYN, and TANDEM. They're all published in outstanding American journals, I would say. Now, we are moving towards PREVAIL. PREVAIL is basically the translation of BROADWAY. As we've all seen, in BROADWAY, which is normally only meant to lipid-lower, we also saw a reduction in MACE endpoints of 21%. It's very important to kind of wonder whether there will be a good translation going from the BROADWAY trial to the PREVAIL trial. PREVAIL is currently fully enrolled. It has baseline characteristics that are almost a mirror of BROADWAY, and the event rates are going in exactly the direction that we thought they needed to go. We've stipulated that everybody needs to be in that trial at least two and a half years, which will mean that we'll have a median follow-up that's longer than the trials that have been concluded in recent years. Everything looks, in that sense, very rosy because with a 21% reduction of MACE after one year, now we have four times the number of patients in PREVAIL, and the trial is four times longer. It's like nothing can go wrong. We have very strong conviction that the results of BROADWAY will translate into a significant MACE reduction for PREVAIL. That's where we are. Next to PREVAIL, however, we are doing a lot of stuff, especially for a small company, I would say. We're doing a CT angio trial called REMBRANDT, where we have Harvard Medical School involved. We are doing a number of other studies to kind of broaden our indication and improve things for our label. That's also what's currently going on. Of course, we just presented our Alzheimer’s disease biomarker sub-study at the big Alzheimer meeting in Toronto this summer, where we showed that our drug, to the amazement of many people, also has an effect on biomarkers for Alzheimer’s disease, and that we are currently pondering how to take that further. That's where we currently are. Yeah, super helpful and a lot going on and a lot to dig into. Maybe one to just kind of level set, you know, as you mentioned, there's been a lot of data generated here, and it seems like approval itself is, you know, from my perspective, pretty de-risked at this point. You know, you filed in Europe already, I know, earlier this year. Maybe let's start with kind of your latest thinking on the timelines to filing in the U.S., kind of how that will be sequenced with PREVAIL and what all that timing looks like. I definitely want to dive into some of those specifics. Yeah, I think I can handle that one. I mean, as you alluded to, we filed and the application has been accepted. Just to clarify, there's actually been two applications. There's application for the monotherapy as well as the fixed-dose combination in Europe. Hopefully, second half of next year, we can see approvals there. Our partner Menarini will be able to launch the product. In the U.S., we've been pretty consistent. PREVAIL, there's two components. There's a time component and an event component. Really, the goal is to make sure that we're able to line up the study so that we have outcomes data available at time of launch. As of today, PREVAIL remains on track in terms of the event rate, trending in the right direction. We'll have a better idea next year of really when we'll see that final readout. We're hopeful we can get some data towards the end, or early 2026, but definitely hopefully completing the study by the end of next year or potentially, we'll see when the data actually reads out. I think overall the goal there is we want to have the outcomes data available at time of launch. We need to have that conversation with the FDA next year about when that data can read out during the approval process. Once we get into a little bit next year, we have a better idea of the event rates, we can have that conversation with the FDA. Yeah. Okay. Makes sense. Yeah, you know, obviously PREVAIL seems, you know, really obviously important for the commercial opportunity. You know, John, to your point earlier on BROADWAY, you've already seen a really, you know, large 21% MACE effect, you know, that is beyond what you would maybe just expect on LDL-C alone. I think you laid out some really interesting data at your guys' R&D day this summer. Maybe it'd be helpful to kind of recap, you know, some of those data and the other pieces of the obicetrapib story like small particles, Lp(a), and kind of your confidence that that 21% MACE signal on BROADWAY is, you know, real, I guess you could say. Yeah. So actually there's two things, two sides to that coin. The first side is that whether a MACE reduction is real, you cannot look at the numbers and say that it's real. You have to look at the Kaplan-Meier curve because the Kaplan-Meier curve is a representation of the biology of atherosclerosis. What happens when you start a lipid-lowering drug, whether that be a PCSK9 or a statin or for that matter, a CETP inhibitor, the first six months, basically nothing happens because you first need to lower the concentration of atherogenic lipoproteins. Then the plaques need to respond with stabilization. Then there's less chance of a plaque rupture and an event. You'll see that exactly in our Kaplan-Meier curve at about the six-month mark. That's exactly what happened. The first six months, the two curves were superimposed. After six months, you see the curves widening up. What is most telling is that it's the placebo arm that goes straight up. That's very intuitive because you have a certain percentage events per year, which is represented by a line. It's a straight line going up. You see the obicetrapib curve go down. They kind of go down. That is exactly what you want. The Kaplan-Meier curve is exactly what you would expect in biological terms. Second, what we've done with a number of our partners is actually to analyze all other data of trials that came before us for statins, ezetimibe, PCSK9 inhibitors, bempedoic acid, and asked ourselves the question, if you see a MACE reduction in phase III, will that translate into a MACE reduction in the outcomes trial? The answer is yes. That is now a manuscript which was submitted like three weeks ago to a major American journal. Undoubtedly, it will land somewhere, but it gives us a lot of confidence that the MACE results will translate into PREVAIL results in conjunction with the actual Kaplan-Meier curve. The third point is because we had so many events in BROADWAY. For a 12-month trial, we actually had so many events that if you add the events from BROADWAY to BROOKLYN, you're basically getting statistical significance for four-point MACE, especially if you look at the second half of the trial, the last six months. That gave us the possibility, exactly like you were referring to, to do a so-called mediation analysis that we presented at the R&D day. That made it, again, biologically highly likely. It is not only LDL cholesterol, but it's also the LDL particles and its lipoprotein(a) that together almost explained like 90% of the 21% MACE reduction that we saw. That is the third point that you are confirmed if you do, let's say, the mediation analysis doesn't show anything at all. There's no relation between the LDL lowering and the MACE. That would be very funny. That would make you kind of suspicious whether this is a real result. None of that actually, it was LDL, LDL particles, and Lp(a). That gives us the confidence that we currently have. Yeah. No, that all makes sense. It's all three really interesting buckets there. On that last piece in terms of the literature around these small LDL particles, it is really interesting. Obviously, you guys have talked about how statins may preferentially lower big ones, so a lot of the residual cardiovascular risk is specifically those small particles. Is that almost, in some ways, like some of the literature suggests these particles are almost a better determinant of MACE than LDL-C alone? Is that a right way to characterize it, and how is the field evolving to focus on that versus LDL-C, et cetera? It's a very complex area, but the first thing that I can tell you is the biology is that you cannot make a small LDL particle without CETP. High CETP activity, which is very common in diabetes, for example, drives small particle genesis, so to say. If you, like obicetrapib, basically knock out CETP activity, 97.3% inhibition or something, which is basically saying you knock the activity of CETP out, you see a dramatic decrease in small LDL particles and also in total LDL particles. In order to prove that particles give a better prediction of risk than, for example, LDL cholesterol is not that hard. Actually, many people have done that. The next question is, what is better? You enter non-HDL cholesterol and ApoB. We are currently working on that issue in a number of clinical trials where we have all three measurements. We're also working on it in the UK Biobank. We have some analyses that we've submitted to the American College of Cardiology next year. It is quite likely that when there is discordance, so when the two measures, for example, LDL and LDL particles are discordant, the LDL particles give a much better indication of risk than LDL cholesterol. That issue is kind of, as far as I'm concerned, settled. We will show that with real data and also in large databases. The next question, whether it's also better than all the rest, is very difficult because they're very correlated. We're working on that issue in a number of clinical trials. I think that I can say without any doubt that LDL particles are a much better predictor of risk than LDL cholesterol. Yes. It's exactly like you're saying, statins preferentially lower the large ones. If you're a diabetic and diabetics don't have that high LDL cholesterol and you hit them with like 40 mg of atorvastatin, you basically get rid of almost all of the large particles. What you're stuck with is a large number of small particles and they drive risk. When you have a drug like ours that lowers small particles by 90% or so in phase II, we are scientifically quite convinced that that is a very good thing. Yes. Yeah. Yeah. No, that's super helpful overview. And then, you know, the other piece of the story, obviously, you highlighted Lp(a). I think, you know, that gets a lot of investor focus and especially with the pelacarsen readout, you know, next year. I think some folks are looking at that as maybe sort of the first test of is lowering Lp(a) drive a clinical benefit. I guess maybe firstly, just like, you know, curious what your expectations are for that readout. And then two, how important do you think that is to confirming kind of that your thesis around Lp(a) driving a beneficial effect? Yeah. I'm old enough to have seen three or four major disappointments in the lipid space. I remember the phospholipase A2 inhibitors. I remember homocysteine. I remember squalene synthase inhibitors. There was another class of drugs that failed. I was involved in the development, not as an owner, but as a consultant in all of them. You can be really wrong, which I do not hope. I think that all the signs are green for lipoprotein(a). I think it would, I mean, it's always very dangerous to really predict the future. I think that it's almost impossible that there will not be a MACE reduction in HORIZON. The question is, I think that the overall thesis that lowering lipoprotein(a) by, what is it, 70% - 80% or 85% with pelacarsen would not translate into a MACE benefit is incredibly unlikely. The second question is, how big is the benefit? Of course, the trial is postponed. Why would you postpone a trial? Because the event rates are a bit disappointing. You have a pre-specified number of events, and if the event rates are lower than what you expected, you're going to have to let the trial run longer. If the event rates are disappointing, it's almost always because you have controlled the major driver of events, LDL cholesterol, too low. It's very likely that, and that is something to be applauded, the patients in HORIZON are extremely well controlled for their background risk. The downside of that is that your overall event rate will be lower than what you thought. It's a bit harder to show that your drug delivers an independent benefit on top of all the background therapy. In summary, I do think that what we will see from HORIZON is the relationship between Lp(a) lowering and MACE reduction in a very well-controlled LDL environment. What we can do then, because then we can make a relationship, we can draw a line between Lp(a) reduction and MACE reduction. Then we can translate that line for obicetrapib because we know exactly now what obicetrapib does. Obicetrapib lowers Lp(a) above the risk threshold of 15 nmol but below the threshold of 150 - 175, where all the trials are, with like 45%- 52%. We've published that and we are currently working on a manuscript for our phase III program that is very close to completion. Those are the numbers. We know exactly that in that range, what kind of nanomol absolute reduction we achieve, and we can calculate once we've seen the HORIZON exactly what that would mean for PREVAIL. Yes, I do think it's going to work. Might it be a little disappointing? That could be the case. Is it helpful for us? Yes, always. Always. I mean, I think it's also important to highlight, you know, on that last point, wherever it reads out, it doesn't change what we've already shown in our own data, the 21% at one year. What it does is change, and you know how we broke it out at the R&D day, it could change the interpretation of how much Lp(a) contributes to that 21%. All of that would mean ultimately is that particles are probably a greater representation of that above, you know, line benefit. We know where LDL -C is. The CTT line is very well established. How do you get to where we go? There are really those two levers. There's the Lp(a) and the particles. As we get more data on Lp(a), that will adjust. There are a group out there, I'd say, the investors that we speak to are kind of torn. Is Lp(a) a bigger driver or are particles a bigger driver? Some investors believe Lp(a) is a very big driver, and some are convinced that particles may explain most of the benefit. I think we'll get one piece of that with the Lp(a) studies. As John said, if they're not, if the M ACE benefit is a little bit less once you control for LDL -C, then that clearly makes the particles much more interesting for us. That's clearly something that is a good differentiator for obicetrapib. Yeah, makes sense. Obviously, the patients in PREVAIL are not like they also have LDL -C, et cetera. It's a little bit different of a patient population. Maybe one last question on some of these underlying lipid dynamics here. One question from an investor, you know, this ApoB, is that, you know, how should we think about that? Is that even maybe a better sort of like how we should be thinking about translating reductions in ApoB to MACE better versus LDL-C to MACE? How does ApoB fit into the equation here? Because the molecule, there's one ApoB molecule per particle. ApoB and LDL particles are highly correlated, so it is basically, there are different manifestations of the same thing. ApoB and total particles are very well correlated, but of course, small particles are something else because a small particle will say that you have one ApoB molecule and very little, very little cholesterol. It's a tiny particle that gets easily oxidized, can penetrate the arterial wall more easily, and therefore contributes to atherosclerosis more. It's the particle that is very prominent in diabetics, after that, et cetera, et cetera, et cetera. I think that, you know, ApoB is nice. It can be done with an ELISA. If you look at the correlation, for example, also between non-HDL. Non-HDL is for free because once you have done total cholesterol and you know your HDL, which everybody gets in a lipid panel, you can calculate LDL, which is free, and you can calculate non-HDL. That will give you like 99% of the information. ApoB is indeed, it almost looks like it's the latest fashion, but in all reality, in a vast majority of patients, it doesn't add much. If you have lowered your LDL to the new targets, you know, 55 mg or 50, yeah, 55 mg per dL, there are very few people in which ApoB is giving you more information than non-HDL or LDL particles for that matter. It will always be a little, you know, there's this kind of war of taste, and people that certainly are big believers in ApoB. For example, the Oxford group has always believed in non-HDL because that captures everything but HDL. You can also, and the correlations are like 0.98. What's there to gain, I would almost say. Yeah. Okay. That's really helpful and really interesting. You've talked about and you've generated a lot of clinical data here. I think everything makes sense. There's a lot of design elements of PREVAIL that we didn't get into, but in terms of taking learnings from other cardiovascular outcomes trials and applying them to PREVAIL, what do you see as the risk here? How closely can you track things like compliance? You talked about events are tracking well, but compliance, other things like that, what's your confidence there that the trial is kind of going well? You can track a lot, in fact. You can track patients off study drug. You can do that blinded. You can get a feel for how many patients in absolute numbers are off study drug. You know whether there is new lipid-lowering medication added to a patient or prescribed to a patient. You can actually look at informed consent. Some people have said, "I don't want to have anything to do with you anymore. I'm going to tear up my informed consent." We are doing that extremely closely. We have basically set up a whole organization across the globe for all these. This trial is running in China, in Japan, in Europe, in the United States, in Canada. What we're doing is we have a team that visits the sites, talks to the sites, shows them the phase III data. The most important thing, why a patient would leave a blinded trial, is because he's afraid of the safety of the drug. What we have is BROOKLYN, BROADWAY, and TANDEM. There is no safety issue with this drug whatsoever. If you convey that message to the principal investigator, then it's important that he or she can put that into perspective. When somebody says, "I have a terrible headache five times a week," and then you look in the BROADWAY data, is headache seen more frequently in OB and placebo? If it isn't, then you can at least have a reassuring conversation with that patient. All of that helps. I don't think I'm actually at liberty to divulge the numbers, but the matrices that we can follow look very, very good compared to other trials that have just finished. For us, this is the crown jewel, as you can imagine. This outcome trial, 4x as big as BROADWAY, four times as long, almost terrible risk, good event rates. If we have 21% reduction in BROADWAY at one year, the trials are almost like a mirror of each other. We really do everything we can to make sure that the integrity of this trial is safe. The numbers look very good. I think probably we will at the next R&D day, Matt, divulge some of the quality numbers probably. We'll see. I mean, obviously, if they're available at that point in time. I think it's important that aspect is, you know, we spent we have a lot of data here on the efficacy of obicetrapib and the safety. Really, the controlling of the study is the biggest unknown. That's where the vast majority of effort is going at this time, is to making sure patients stay on therapy, stay in the study, and, you know, continue to participate. That's where John spends a lot of his time now, is visiting sites and going to sites and making sure everyone understands that, you know, we have this safety data. If your patients are having some concern, look at their phase III data. The safety is very good. Get the patient back on study and maybe consider another alternative before you take the patient off. Yeah. Yeah. No, that all makes sense. There's a lot of data and there's a big development program that you guys run very well, which is obviously very encouraging. It all makes sense. Maybe just one last question. I know we're like a minute over, but it's something that comes up with investors and somebody raised it here in terms of, you know, obviously there's four old PCSK9 inhibitors out there. Curious, you know, your guys' thoughts on those programs, how obicetrapib kind of stacks up, and just any high-level thoughts on the broader sort of competitive landscape here. I think the important thing to understand, you know, for everyone is this is not a market that is a zero-sum game market. You know, this is a very large market that's going to need multiple players in this market to be successful. Remember, there were seven statins in the market and they were doing, you know, tens of billions of dollars of sales a year. We have to first take that into account. I think importantly for us is everything else in development or really being utilized today post-statins are PCSK9 s. We will be the only CETP drug available on the market, which is a very big positive for us. We're going to be looked at as a distinct class from, hopefully, a payer perspective. That would allow us to be on formulary because we're the only drug available versus other PCSK9s. I think we spent a lot of time talking about the overall profile of obicetrapib. If you're a patient and you have high Lp(a), if you're pre-diabetic or diabetic, if you have high particle counts, you know, and most recently now if you are an ApoE4 carrier, obicetrapib is going to become your preferred therapy. Each one of those are very large buckets. I think PCSK9 s will do very well. That's what our research shows. It just shows for the vast majority of patients, you know, to drive the broadest access possible, safety is going to be the most important thing. We have probably hoped, you know, what we've seen so far is one of the cleanest safety profiles we could hope for. I think that's ultimately going to drive broad access. If you look across efficacy, you know, with our fixed-dose combination, we're in line with the injectable PCSK9s. Once you have efficacy accounted for with all these therapies, then the question is, what else can we do for a patient? You know, that's really where obicetrapib is able to differentiate ourselves. At the end of the day, we feel everyone will be successful. You know, this is going to be a resurgence in, you know, the lipid management paradigm. Hopefully we see that and these drugs do well. Ultimately, at the end of the day, we just feel our product profile is just so differentiated, it's going to allow us a really clear space in the market. Yeah. To mate what we've just shown on the Alzheimer’s disease biomarker sub-study. Yeah. If you can lower your LDL cholesterol and at the same time have efficacy towards Alzheimer’s disease biomarkers, that's an enormous differentiator, of course. Yeah, absolutely. We obviously didn't get a chance to go into some of those other diabetes, et cetera, but you know, there's obviously a lot of interesting data you guys have generated. I think everyone's seen the tailwinds in the commercial space in terms of lipid guidelines, kind of labels changing, PCSK9s are doing well. I think everything you said there, Matt, makes total sense. We're up on time, but thanks both for joining and thanks everyone for dialing in. This was an awesome conversationf. Appreciate you guys taking the time. Thanks.