Praxis Precision Medicines, Inc. (PRAX) Earnings Call Transcript & Summary

Good afternoon, everyone. Thank you so much for joining our virtual fireside chat. My name is Yas. I'm excited to have Marcio firm Praxis here. We have a full hour for discussion. I know many of you are buried into earnings. So this morning has been very, very busy for all of you. Been very grateful that everybody is able to like during the fireside chat. And again, housekeeping rule is the same. So if you have any questions during the fireside chat just utilize the Q&A box at the bottom of your Zoom and submit your questions, I'll make sure to direct them to Marcio.

Marcio, I think that maybe a good place to start off a sort of big picture, right? Before Mondays readout, we had the Phase I data. So we weren't really sure by looking at the Phase I data, how vormatrigine would differentiate. Now we've learned quite a bit around its differentiation with the data set so versus other therapies. So maybe walk us through what have you learned from the study? And then question 2, also broad. What are some of the I guess, things and considerations that you think the Street has not appreciated into the data, and then we'll go really deep into that RADIANT?

Sounds good. I appreciate the invite, first and foremost, and I always nearly live in the future, Yas, but you just confirmed. I think it just good morning on every time zone in the U.S. So good morning, everyone, not afternoon. So like if you take a step back, I just had a big picture of vormatrigine. What we are seeing and I guess what we continue to see carrying from great preclinical evidence to the PPR. So obviously, all the safety and pharmacology and everything preclinical and clinical seen so far is a drug that really can help patients with epilepsy a lot. And that was a promise until this week. And I think that's quite important. And maybe on the -- I'm not sure if I say underappreciate it. I'm not sure if that is a need for appreciation as much as just people paying attention to on everything that's going on there on a world with very low and narrow attention spans is when we had the PPR data last year, there was a lot of clinical pressure to like say, what does that mean? What does that mean, right? You might recall, we had some conversations. And we always, I would say, rightly so, said what we know is this growth in the brain, but we know that's doing something for the [iatrogenic] formation that's happening there. We're managing this. We're happy we can't really translate to what's going to happen when we treat a focal seizure patient or generalized patient. A lot of like asks and pressure to try to translate. And I think we stay pretty serious about it because we really couldn't, right? That's where the science is despite the fact we have like 100% of the patients responding on that study. You fast forward to the place we are today, the data set we really wanted to have for multiple reasons as the first data set, of course, is raised, where we treated a significant number of patients, refractory difficulty to treat, one could even argue the most difficult patients to treat, right? They want that actually gravitate towards studies like this. And it is undeniable how active the drug is, right? So transforming from a province to a drug is a big deal, in my view. And that's kind of what we have this week. Now we can go one by one, as I'm sure you're going to go into the aspects of that and why we are so excited about it. But in summary, when we look into the actual markets, right, looking to not people like you and I or all investors on this call, but like the real people living with epilepsy, it is very, very clear, very short there. Number one, it is a massive market. So the idea that, and as we go very quickly to the 0-sun game that while there is a drug or 2 drugs or 3 drugs that are going to solve the problem for epilepsy, I think it's a little bit delusional in Ferfetch. Now are there situations where you are like looking to the market in these lives that differently and you say there are like bigger winners throughout those lives, I think so and we can talk a lot about that. But we do have 3 million, I'm rounding down patients and over 60% of them cannot tolerate our respond to the current treatment. I think we all would agree that there's a huge space here. Like looking to the history of epilepsy drug launches that were safe and efficacious and they all did really well. Now imagine one of the profile vormatrigine and then you can imagine what it can really do. And I think that, that's why we're so excited, like we went through somewhat of a promise. Of course, we're excited about it to a lot more than a promise today with helping real patients with focal seizures, reduce their seizures or resolve their seizures as you've seen a good number of time.

Marcio, let's dig really deep into many elements of RADIANT and then we'll talk about POWER1 and POWER3. So let's start like just confirm the trial side. The RADIANT when you reported out, you said you had 61 patients as of July 25, and the total is going to be targeting 75, so -- and you're going to read that out in 4Q. So is that difference of 14 patients then generalized that we're going to get at? Or are we going to get in the next 4Q a combination of those?

No. A mix, I would say, we are pushing very hard for the generalized patients to be the majority of them. Of course, that is the data set that is missing here for us to complement. But there is still -- I think we're very transparent on the disclosure while talking about the patients that were screened, meaning they finished their screening. There are, of course, patients in the screening and some of them are generalized, some of them are focal, smaller number in focal. And the patients that we dosed for more than a week, that's the 61 and between that and like multiple weeks. And then the patients has completed and that was the data set we [promised to Phase III] that we have here to discuss that was 37. It is actually -- in a sense, it's a place of privilege rights to be with so many patients number one, interested and to being able to recruit in such a fast fashion, so many patients in this study, give us a lot of safety data, gives a lot of understanding of these patients, a lot of different background therapies and things like that. So we feel for the stage of the program, running like multiple Phase IIIs in the next several months is a very good thing to have so much depth of data to learn what we can learn and you're doing a fair bit about, number one, how to recruit these patients, how to follow up and like incredible compliance to the seizure diary, for example, it's something super important, but it's never a given compliance to drug and everything else, management of AEs, as I'm sure we're going to talk about and it's a large number. This is not like 10, 15 patients as we had before. So that allows us to make a lot of extrapolation as well.

So I guess it's fair to say that when we get data in 4Q, it's going to include, obviously, generalized patients that we have not seen and maybe a few additional focal epilepsy patients that maybe had not finished 8 weeks at the time of the data cut of July 25?

Correct. Correct. You'll make a clarification here. All the difference between 37 and 61 are all focal. We only get focal numbers there. And we can expect a few more, 2 or 3 more or something like focal and then the rest generalized.

Okay. All right. Very helpful. Now I would like to spend some time on sort of walking through sort of exposure related to efficacy, safety and discontinuation because I think that's going to become really important as we think about this translation to the POWER1 study and POWER2. So I guess the first question is, can you confirm that the PK in patients was comparable in healthy volunteers?

Yes, beautiful thing. I love the fact you asked this because I don't think we discussed this enough. The number one thing we wanted to learn here, right, was exposure and safety and effectiveness. The exposure -- there were a number of questions we wanted answered. And I think we answered all of them so far. So the first one is exactly what you just asked. If the PK profile, outputs of PK comparable to our volunteers years or not. But we know that patients with epilepsy in general, but talking about seizures, particularly, you have a lot of other drugs, a lot of co-morbid conditions, things just happen, right, on these patients. They're not clinical healthy as the healthy volunteers are on the study, and it's incredibly comparable. So we're very, very happy with that. It is very reliable as well in terms of predicting. So we want to first know like can I compared with what I have for our volunteers, but the second is can I extrapolate from that...

Yes. Before you go there is I want to kind of like walk through each of them step by step, okay? So we learned PK between healthy volunteers and patients was the same check. Second check is, can you confirm that the 30 mg dose group was linear in AUC and Cmax?

Yes, there was just like we had before, right? So we were expecting -- of course, we didn't have multiple doses here, but it was comparable to what we've seen with the previous most ascending dose for 30 and the exposure spread was similar as well, which makes us believe that the way the drug is [nothing makes more] similar, steady state reach more similar that there is nothing to believe here that the dynamic that you've seen before of linearity wouldn't be kept on this.

Okay. Next question is, would you say that the level of variability as comparable?

Yes, slightly comparable, yes. Surprisingly, right, you would expect a lot more variable here. So that is another very good metric.

Okay. So I guess, for example, so you previously disclosed that the coefficient of variables of 45 milligrams in healthy volunteers was 29%, you saw something very similar in focal epilepsy patients. So check. Okay, perfect. Now I know that now with this data, you guys are going to do any -- do extensive modeling, right, and think about sort of additional data over time. I guess the question that I want to know is like almost any exploratory analysis, you could look at quartile based on AUC. And then you look at the sort of seizure reduction, right? So you can actually think about treatment response to AUC based on quartile. So would you say it's fair to assume that the top quartile could actually generate 75% reduction. Like since it is linear, and you can divide it up, is that -- am I getting over myself as you think about that? Because that's going to be important when we think about the 40 mg dose group in POWER1?

I wouldn't agree more that that's quite important. Let me take a step back, right? So we collected intense PK on day 1 and on the end of study on day 56, and then trough levels throughout the study. So we make a number of predictions here, right? We use a PK model. It's been developed based on the healthy volunteer data and then we try to put this and so on and so forth, as you know well. So we asked a number of questions to that, like how is it not only AUC, as you just mentioned. But to jump into AUC, you have to believe it's an AUC-based phenomenon. It can be both ACU and Cmax or other actings. And I think that's a combination of both here. And I can tell you that there is a dose response or concentration response because we did not dose here. That dose was just one for both Cmax and AUC in terms of response. If you split that in 4 similar groups, as you just mentioned, right, in quartiles, yes, the top group is better and better numerically. Now I always have to put a caveat right? This is not that small by study, but still -- we got to be careful once we start breaking down things into small and smaller groups. They will definitely expand from a situation at that. But it gave us confidence for 2 reasons, like without maybe getting off my skis and saying, oh, that's going to be a 7 or an 8 or 6 handle whatever it is on that number. I think there are a couple of parameters we wanted to make sure we're true for the dose of 40 to be selected for POWER2. So the first one is, yes, the number has to be bigger, right, meaning there is a reason to go there from an efficacy perspective. But that alone wouldn't allow us to go there, right? Because it's all the side effect were concentrated there or there was like a very direct relationship, then we would have to pause as well and saying then we go there in the safety profile. But it's not the case, right? So I think we have a lot more of a response in terms of efficacy than we have on safety from a concentration standpoint, possibly because there's a lot of other things influencing Phase II here and efficacy is really being influenced by the drug. So there might be why -- they might be right. It is amazing. I mean, is almost like what you always want, right? So you're giving more drugs, you get more effect, but you're not having any worse safety profile. And that was the base on why we believe that 40 would be adequate here in POWER2. So yes, when you combine a time-based effect, which we haven't just done right? So it's causing concentration like independent of time, but you have both concentration, so it's time, so it's a longer period of time. We also see like depending over time of effect and going to 40, it would not be softer or correct for me to say I don't expect that margin effect there because it wouldn't be true. So that is what we are thinking.

Marcio, maybe you noted too, right, the PK and the exposure had no effect on safety. You just noted that. Did it have an impact on discontinuation rate?

Yes, it did not. Yes.

Okay.

Do you want me to check the box or...

Yes. No, no. I think -- no, because we have so many questions, but I want to kind of like team up in a way just as we think about it. So now that we're on the topic of discontinuation, let's just kind of close the loop as investors have asked a couple of things. One is when you think about the discontinuation rates that you reported of 23%, that 23% was based on the 61 that you got at the beginning of the study. Is that correct?

That's correct.

Okay. Okay. Second question was, was there a time by which the discontinuation occurred? And what that time cadence?

Vast majority of those patients discontinue in the first 3 weeks of treatment with a little bit more towards the first and second week there. It's interesting, yes, right? Like we are -- maybe to our faults, like we're saying like we're not happy with this. And it's not that we're not happy because the data is bad. Normally like people are not happy because it's bad, like it is actually very good from its continuation rate. Well, ideally, we wouldn't have any. But you've got to understand and we said this before, right? And I think those why find a little bit ironic that people bring it up as we haven't talked about this before. . The setup of this study like attract patients that are a little bit more severe, that are a little bit more refractory. But also, they know their own drug. So they are more likely to attribute like anytime to drug and potentially discontinue. I think what we failed to maybe act a little bit faster was when we -- like we informed the physicians by the PIs and we train them and we reinforce the training with them. And I will say, it's never enough. And maybe if I'm going to call failure, maybe failure is like to just reinforce even further, because what we end up seeing was it was probably more related to certain sites than to the overall effect. Now we can't definitively say that, right? So I will keep running the studies. But if the experience on POWER1 is of any information right now and it's blinded. And of course, we got to be careful with blinded data in general. But the overall rate is significantly smaller. And I think we can overlap, the fact that certain sites that have a little bit more discontinuation or not on POWER1 and they were the ones influencing if it was a generalizable phenomena, then we would be seeing like across the board in other sites as well. So either the training or that we obviously always reinforce or the fact that there was maybe a little bit more PI dividend to some extent, and I'm not throwing anyone under the bus, right? No one patients to discontinue. It just sometimes happens, they might have unduly influenced the rates here.

And I'm not sure. So since you noted that the power discontinuation rate on a blinded basis is less than what you saw in RADIANT, can you remind us what you have said around what your assumptions were in discontinuation rate?

Yes. So we -- if you go back and look into the way we power this study, the -- all the data we had to work with was historical data, right? And you go through historical data on both drug and placebo throughout life. I'm going to call modern anti-seizure medication drugs. And you have like to you have like X-TOLE, you have like the [indiscernible] develop like 1.6 blocker and so on is looking to all of the data, which is publicly available. And it always tends to be around 20%. You go across the board and you look into that and it's like a little bit higher for the most part, but I think we can say that the central tendency there is around probably 25%, but then we are like 20%. So that was the assumption to begin that we are on the actual protocol and how we determine the power for that study. Of course, we believe that like with more intense management meaning like really just based like talking to patients, right? They talk to investigators together this morning. They're talking to all the time and they're like it's common sense to just call patients and check in on them in general, let alone clinical studies. Sometimes it's just not done that we would and we still believe that in the future we're going to have like lower rates than that. But that's how it was defined in a sense, almost every study and every disease have a base rates and the base rate for epilepsy is around 20%.

Okay. Let's pause into a couple of clarification questions since we are on discontinuation. So I guess first question from a client is asking around what discontinuation in dose reduction rates were in the 30% of patients who were on background [indiscernible] patients versus the 70% that was not. So could you maybe talk about that?

Yes, absolutely. So if you look into those 30% or so, a little bit higher in the ongoing basis, [indiscernible], right? Those -- I think the way it was portrayed to me, I don't like talking about this, but I'm going to paraphrase, it's like the worst of the worst, right? So like we would threw everything at them in general. It was no difference than the overall. And if we go and we look into 2 aspects of that, which is quite impressive in our view. One is to ask and I don't know what you hear from doctors, but when you go and pull the market and we ask which dose of [indiscernible], right? The most common number back and what claims data to the extent that [triangulation optimization] works here is around 200 milligrams per day. Those patients were around 300-plus per day. So they are way more prone to have all sorts of side effects and discontinuation, things like that. So it basically to say it's not had or anything like that is basically say, those patients who were really on the top of what they could tolerate the breakup plan. And the discontinuation was not any different, right, on this, which is, to me, it's quite positive.

I guess the one positive thing is that when we had done channel checks is that a lot of jobs docs don't really get comfortable to prescribe more than 200 mgs. So the fact that you had -- you just told me 3 -- like majority of them being on 300, really like highlight that these are really experienced docs that are part of the study because the normal doc would not feel comfortable to go there. So like maybe another nuance here, I guess, just as you're walk talking through this is sort of the integrity of the study and the quality of the site. Yes. One more thing I want to drill down to is -- and you said in the passing as we were just having the conversation that the discontinuation rates were not -- they could have been run by few sites. Can you drill down? Because, I mean, did you get a chance to look at like what the distribution was because that's another maybe aspect to keep in mind?

Yes, we did. I think this is one of the first things on an ongoing basis. Our clinical team is quite on top of that and having conversations. And they also happen to be some of the first ones to patients. So no fault of their all in a sense, they are earning a little bit about this. And -- but that was somewhat of a concentration, I would say, the -- as numbers grow, you should keep asking like is this concentration real, right, as everything else we do. . And I think now we can fairly confidently say, yes, there was somewhat of a concentration as we have a significant number of patients dosed across the program, which translates into a good thing, right? Because it is very hard when you have no idea where it is coming from. But it becomes while again, not necessarily positive overall to have anyone discontinued, but when you know it's coming from, like there are actions you can take. And I think the primary reaction here is just like a reminder, like consenting of the patient, reminding of what is the side effect. There's always going to be a random effect, right, on what happens. But I think we're trying to control the non-random effect like this one just described.

Another question that a lot of people are asking us, since majority of the discontinuations occurred between week 1 and week 3, how is that impacting the efficacy? Like how did you calculate total seizure reductions for the ones that you missed the data for, both for baseline end of treatment?

Yes, absolutely. So the most cautious way to calculate future rates, right, in epilepsy studies and maybe a little reminder there as well, I know it's obvious, but -- so we use an electronic diary where patients have to confirm their seizures are like they're off every single day. So we have like that and whether or not they took the drug as well, they confirm at a single day on the diary. . So you have a number of days and a number of seizures, right? So you can greater rates there. And that is pretty much how everyone does. It's small variations here and there on the fringes. It does not really change the overall number at the end. So you would imagine that if a patient who discontinued earlier, they tend to be, number one, less opportunity to respond like as response depends over time. And the second is that sometimes are not the best responders because like that's one of the factors on discontinuation. So that's kind of a double negative in a sense. And they are used, right? If that was the question behind the question, like this data is entirely used. So one could hypothesize while that's the proper way to analyze it, that reduce the effects, right? So when you reduce the number, you increase the effect hypothetically speaking.

Okay. Another if you could. How many total patients discontinued out of that 37 that you looked at?

Yes. So we're going to put the exact like numbers and like numbers at the IC [pulse] like 3 weeks or so. But you are similar in terms of the rates of discontinuation between 37 and the remaining that are in the 61. Numerically, a little bit more on the first 37.

Okay. That's helpful. And is it, I guess, fair to say that at the final analysis, 32 out of the 37 finished like 8 weeks of treatment then?

That would be a little bit better rates, right? So then you would make the other ones to -- no, a little bit smaller.

Okay. Got it. Okay. And then Matthew, would love to talk about -- I mean I think this picture here, if you look at other focal epilepsy studies, and I think it's in the appendix of your slide deck, comparing it to [ XEN1101 and SCN8 ] studies, they were between 23 to 27. So it's not really shocking that you ended up at 23. So that's like I think we get that. So I appreciate you answering a lot of color around it. I guess another question that has come up is when you look at I guess one of the things is the total rate -- the reduction of seizure -- total seizure reduction was 56%. But if you look at the time curve when you look at week 1 through week 8, you really see actually consistency. And you did calculate your seizure reduction from baseline through week 8, you would have ended up with 70%. And I think even at week 5, you had 100% seizure election. So maybe kind of help us think about now that you learned this about your drug and POWER1 is going to be 8 weeks, like what do you predict to see by going longer and plus sort of -- and then remind us, what is the calculation of seizure reduction, I guess, to in POWER1 versus RADIANT?

Yes, absolutely. So we do see, right, I mentioned that on the PK discussion we had, both concentration response, which because there's some accumulation, there's a patent response to it as well, but a time-dependent response. Can we get in [indiscernible]? No. So they're both, and we can look into both. Maybe then too honest there, and so we really can't [indiscernible]. But we do see over time patients get better. I think the most obvious way to look into this is the spacing of the seizures, right? They get longer and longer in between and eventually, I think we all wish they go to 0 on the majority of the patients. So just by linearity alone, you would expect that to be 4 more weeks, that's the case for POWER1, that's the case for POWER2 as well and that the number would continue to reduce. It wouldn't be farfetched if we're actually looking for our experience with vormatrigine and [indiscernible] every time we checked and vormatrigine are great data set to look into that because it's -- there's no discontinuation basically, right? So we are really looking to the same cohort of patients without much of a survivor bias, which sometimes the biggest problem on longitudinal cohorts is that you're really not looking to the same number on the long run or even a similar number on the long run. So I think when you take that learning here as well and the learning we have for the vormatrigine, yes, it should. I'll go back to do we need it before people start creating patients and it's like, oh, it's not good if. No, very clearly no, do we want it, absolutely, right? Those are completely different things. Do we want to help this patient more? Do we want ourselves or someone else to free of epilepsy, absolutely. That's why we're doing what we do. But then we need to appreciate as well that these results we have if replicated that we expect to replicate plus phenomenal to most patients. And yes, the expectation is that it's longer, it's more time to respond, it's more time to get to like levels of concentration that one would expect to be therapeutic and patients just have less seizures, the media number, of course, gets as smaller number, everyone gets happy and we move on. but the ultimate goal of this drug is to be widely used. And that is one step towards widely using, not the final step towards that.

Okay. Actually, I would love to kind of think about POWER1. One of the things that on Monday was a lot of analysts, including myself, asked around timing. But when I stepped back and started doing your math in my head and saying, okay, let's say you do finish enrollment today, right? And it's a 12-week study. So by the time that your data could be done, you will be sort of middle-ish of December, which then would mean the earliest, like would you want to put out data in the last 2 weeks of December, probably not great for anybody. So I guess, can I say that -- is it fair to say that your hesitation to answer exactly pinpointing the timing of POWER1 is just that internal -- you know what, if everything goes perfect, and it could be things going to be done in mid-December and that's also not a good time. So it could slip in 1Q. Is that fair to say that is sort of what is keeping you to just say, yes, guys, the data is coming, I don't know. December, XYZ. So I guess that is what's driving your hesitation and fear.

Absolutely.

And I think you're going to announce enrollment completion, right? So then everybody can do that math. And you feel very comfortable that very much the enrollment completion is very near term, and you feel good about it, so nothing has changed. Yes.

So I'll -- since we're doing the math, let's go on last year as well. So there were a little bit shy of 20 sites that were contributing to RADIANT. And we see what happened, right? We gave them the opportunity to enroll more. They didn't enroll 1 or 2, like we're talking about having to tell people don't enroll more patients or RADIANT because I have too many. It's not a different problem with POWER. It's the same problem. I'm calling -- the fact that I'm calling that a problem so oxymoronic, right, because it's really not an issue in terms of enrollment whatsoever. It is just a very long process, right, for these patients. it's like for 2, 8 weeks, they screening. And so any patient that entered the period is like it takes a very long time. I think we learned a lot about how to screen this patients efficiently and the site has been phenomenal on helping with that, but it still takes several weeks in that -- that's the uncertainty I would call versus fear on the final date of all of this.

Okay. So just a confirmation question from a client coming in. Can you confirm as you enrolled more than 50% of POWER1 patients?