Sage Therapeutics, Inc. (SAGE) Earnings Call Transcript & Summary

Good afternoon, everyone. I hope everyone is having a good second annual Wolfe Healthcare Conference. I know I am. I have the pleasure of hosting Sage's management team, including Steve Kanes, Chief Medical Officer; and Kimi Iguchi, Chief Financial Officer. We are going to dig into, obviously, SAGE-217, but also 718, 324, and also kind of the catalyst path going into next year. I think one thing that stands out to me is you have so many readouts even in the next 6 months that people aren't maybe paying enough attention to. So I'll leave the floor open to you both if you want to make any opening remarks, and then we'll take it from there. Thank you.

Yes. Well, why don't I kick it off? And thanks, Akash, for having us. This has been a great -- terrific day for us. Steve and I are delighted to be here and delighted to give you an update on Sage. And so we've made a lot of progress this year. So we're quite pleased. We've really progressed all the clinical programs across all 3 franchises, and that's even in the face of this COVID environment. And when you think about the environment today with COVID and the people that are affected by COVID, but it's really affecting everyone. And when you look at mental health and what's happening there, it's astounding. The rates of depression are increasing, suicide rates are increasing. So this is just making it even more important for us to do our job and really move these programs forward as rapidly as possible. So we're on track with all our programs. We're in a great financial position to advance everything, and we have a lot of catalysts over the next 12 to 18 months. So let me just quickly give you a summary of what those are. I'll start with the neurology franchise. So SAGE-324 is -- we're looking at movement disorders, and we started a Phase II trial in essential tremor. And a lot of people don't get it, but this is like the largest movement disorder out there. There's over 6 million people that are affected by essential tremor. And so -- and there's been no new medicine. So in 50 years, so since 1967, there hasn't been anything. So we need options for patients. And we have a Phase II that should readout in the first quarter of 2021. Then we have our neuropsychiatry franchise, which is led by SAGE-718 and the NMDA platform. And there, we're looking at improvements in cognition, and we're looking at executive functioning. So we have a Phase II ongoing. It's an open-label trial that will also readout in the first quarter of 2021. And then certainly, we have our depression franchise with ZULRESSO and zuranolone. Let me hit a couple of points on zuranolone. Hopefully, everyone knows that what we're looking at is an as-needed approach to depression. We've really proven and seen a lot of activity around rapid-acting durability and tolerability with so far with SAGE-217. So we have multiple programs that are ongoing. We have 3 distinct pathways that we're following. The first one is in postpartum depression. So we have the SKYLARK Study that's ongoing. It's for postpartum depression, it's -- it should readout in 2021 and will firm up the timing on that when we can. So that is the SKYLARK Study. And then we have 2 paths in major depressive disorders. There's the pathway, which is the WATERFALL Study looking at as-needed approach. That study is ongoing and should readout in the first half of 2021. That, combined with some longer-term data, either in our 302 trial that we'll talk about and/or SHORELINE would be needed for registration there. And then we also have our RRT path, the rapid response therapy, and that's looking at co-initiation with a standard antidepressant. So that's our CORAL Study, and I'm happy to say that we started dosing that study just this week. So another proof point of execution for Sage. So we have a lot of going on, multiple catalysts over the next 12 to 18 months, and we're looking forward to providing updates throughout the year.

Awesome. So maybe let's get started. And we'll start with 324, which seems like maybe your most immediate readout. I don't -- I remember like looking at this at the future path and thinking, wow, you guys really replicated allopregnanolone data with an oral molecule. But I think one thing we're seeing, even with 217, especially for these compounds of drug, SAD to MAD and then exposure and understanding how that evolves over time is incredibly important. And so can you talk about as you look at 324 and the therapeutic window, you've got some data that shows that you're showing a 50% accelerometer improvement open label. But when we think about the PK of this molecule, how confident are you that you are not going to have a buildup of drug over time, things like tactical [ access ] show up over time, or kind of a waiting of treatment effect? Like what have you seen in your preclinical and kind of clinical studies so far that makes you feel confident on that?

Well, so first of all, thanks for starting at 324. For us, it's something that we're really excited about and for all the reasons that Kimi articulated. We've been working in essential tremor now for the better part of 6 years. And one of the -- and among the things we've learned is what kind of effects we might expect, at least with acute dosing with our mechanism? What repeated dosing looks like as well as through interactions with patient advocates and other experts in the field, what patients are looking for a new medicine for essential tremor? And so initially, we saw that this mechanism has a very robust signal and that signal is related to when the drug is on board. So we know we have to have continuous coverage. With 217, we were able to pilot both the kinds of measurements we need as well as the kinds of effects we see with repeated dosing. And what we see is with repeated dosing, as you might expect, we're seeing increasing blood levels as well as increasing effects over time. So open-label studies. Likewise, those effects are replicated in 324. So right now, we're in the midst of a placebo-controlled trial. It's our first placebo-controlled trial, it’s called the KINETIC Study. This data will be available in the first quarter. And what we're looking for is again, replicating that signal in our first chronically dosed placebo-controlled trial. The questions we're asking are exactly the ones that you're asking me, and we -- obviously, we need to find out those answers. What are the effects of chronic dosing? What do we see in terms of overall improvement in effect size? Those kind of data in the first Phase II study are used for decision-making moving forward for the development of the compound. A few factors of 324 that I think are particularly important and why we selected it are that: one, it has the longest half-life of any of the drugs that we've brought into development so far. It also has the smallest peak to trough ratio, we need to have continuous coverage. Lastly, and you asked about animal models, in animal models, it also has a wider therapeutic window versus somnolence or sleepiness, which is something that we're looking to minimize in this program. So again, the first data we'll get will inform how we move forward in that program, something that we're really looking forward to talking about when we have the data.

Understood. And there's not a clear dose response, maybe in the Kinesia Score that you put out, but it does seem like in the TETRAS score, as you go from 45 to 60, we see kind of a deepening of response. So kind of twofold question. Number one, do you see the 45 mg dose having lower TETRAS reduction? Do you think, maybe if I just keep chronically dosing that patient over time, this TETRAS reduction will deepen over time? Is this something that could be a late onset effect with drug buildup? Or do you think, you know what, there's a certain threshold that 45 mg just not getting to and 60 mg would be able to achieve it? Like -- or is there even a signal at all? Like how do you think about the dose response on TETRAS between the 45 and 60 mg dose?

Well, I mean, it's easy to imagine trying to speculate too much on the data that we have to date. Right now, what we know for certain is we have a replicated signal across all molecules that are hitting these extrasynaptic GABA receptors, and that's the most important piece of this. When we go into Phase II, and we generally do this, we'll use the doses that we think we were able to adequately dose within a reasonable safety margin because we're looking to maximize that initial signal. So right now, I would say, are we seeing differences in dose response differences? It's a little premature to say that. This is a drug and a disorder that's required chronic dosing. What we've seen so far with chronic dosing in 217 is as we approach steady state. We do see ongoing improvements. I don't think we've maximized those overall improvements yet with chronic dosing. But those are the kind of things that we're looking to see in the Phase II data. What we see will absolutely guide our hand in what we need to do next, whether that's additional dose exploration or other development.

Understood. Now it is a movement disorder. And we've seen in other examples. I covered Jazz, I think about Cavion, like first of all, the FDA path to the market has kind of [indiscernible] what's the end point that the FDA really wants. And I feel like it's kind of evolving over time. And I think I also don't know how to really think about what's clinically meaningful for these patients. As you think about training physicians and thinking about designing end points for your Phase II trial, what are you doing kind of at the site of care in order to ensure that you're getting kind of a consistent grading and particularly on some of these TETRAS end points where at lower amounts, they don't have particularly good sensitivity. So what's occurring right now on your Phase II in terms of training physicians correctly?

Well, we do a few things, and I won't get into all of the details, but we know for certain that across all of our studies, we've used both accelerometry and TETRAS, which is a clinically validated scale. But the exciting part for us, and I wouldn't say it's a weird situation. It's what it looks like when you're developing new drugs for the first time in 50 years as we get to chart that path. What we've seen so far is a very high correlation between the objective of end points as measured by accelerometry as well as the physician rated scale of TETRAS. And part of the program that we've been doing and what we've been doing very systematically is understanding which measurements are the most accurate, which of them really don't have predictive value, which are responsive to our mechanism of action, which of them -- which give us the highest signal-to-noise ratio. So very similar to what we did in 217, where we included HAM-D and MADRS. We're including a variety of end points, each of which would be able to be used as a registration end point. When we have the data package together, we'll go and have those discussions with the FDA to get agreements prior to moving forward into Phase III. What I can tell you right now is there are very high correlations between objective end points in our hands as well as with a physician rating scale, as you might expect, given that those rating scales are in line clinical use.

Understood. And just briefly on the video rated versus doctor rated, some -- if you look at tardive dyskinesia, they prefer one versus the other and I feel it changes all the time. When you think about central versus doctor-rated assessments, which one do you think is more meaningfully capturing the effect of your drug, which is the one that you think is better heading into this Phase II study? And are you looking at?

Well, what I can tell you is what we're doing and what we have been doing. And that's using the rating scales performed by physicians in person. I couldn't really comment on others. We haven't really had much of experience with that. But given that something like essential tremor affects the whole body, the rating scale involves the whole body, the -- we do have a lot of confidence in the approach that we've taken using TETRAS.

Okay. Okay. So fair enough. Not going to [ meet ] that. Want to see the [ data ].

It probably is, we know what we've been doing. I really couldn't kind of [ come there ] in what they've done.

Understood. Now maybe just lastly on 324. It does seem like efficacy wanes off at a certain kind of steady state concentration. It peaks off right around 50% in terms of Acceleron reduction. Can you talk to us between your work in 217, allopregnanolone and now 324, how much do you think you understand about the therapeutic window here is, if -- when we think about 217, really, okay, 50 nanomolar concentration, it seems to be that threshold effect for your molecule there. What is the -- is there a threshold effect? Is there a threshold exposure type of phenomenon in essential tremor that you're targeting? Or do you just kind of not know at this point what type of -- what steady state you need to get at?

Yes. Here's what we know right now, which is that the major depressive disorder and essential tremor behave very differently, even though we're targeting the same GABA receptors. So in the case of essential tremor, we need coverage during the day. So what we've seen in both with brexanolone as well with 217 and 324 is while the drug is on board and when we're at the maximum exposures, we're seeing the greatest effects. That drives you to a very particular approach for the drug development program, which is to minimize fluctuations throughout the day. Hence, the drug with the longest half-life, hence understanding how best to prolong those effects. For 217, it really is about total exposures, AUC, if you will, and not so much about PK/PD relationships. We'll understand a lot more about those kinds of relationships as we go further in the program.

Got it. Got it. And I guess maybe just if one more on just essential tremor, [ how do is ] like -- what are you looking -- what would be a game changer for you. Like if you replicate your data right now and you replicate your allopregnanolone study in a larger study, what -- if I'm an investor, what am I missing? Why should I be excited about that? What's kind of the unmet need in this indication right now that 324 could kind of fill?

Yes. I mean, right now, the majority of patients with essential tremor either are not diagnosed or don't pursue treatment, mainly because the medications that are available are either hard to tolerate or very -- or not very efficacious for them. And that represents a huge opportunity for us. And since those drugs were approved, so much is developed in terms of understanding the disease, the mechanism, the underlying progression of illness and so forth. So what we've said already is somewhere between 30% and 50% reduction is important. And we know that, that has to happen in a good proportion of patients. And if we can do that, we're really going to make a difference in patients' lives because the need for new medicines is great. And most folks ultimately sort of give up on taking the medications because they don't really obtain much benefit.

Got it. Now maybe moving to 718 and I'll take one question here. The -- I think for me, and I think a lot of investors, we don't know how to contextualize. Because 718 is, I'm betting on a biomarker with 24S-HC that I don't really understand. There are indications where it's not necessarily clear whether it's going to have a benefit or not, but you guys do seem to be very excited. So as you think about the data that you first showed in healthy volunteer, then you showed a cognitive benefit even there. And now you're getting to HD patients, like what excites you the most about that biomarker, 24S-HC in Huntington's. And what validation has occurred in that population right now that makes you confident that you want to continue to invest in this program going forward?

Well, among other things, this is a target that's been of interest in cognition for quite some time. And there haven't been compounds that affect this target in the way that we've been going after it. So it's another way of saying, SAGE-718 is the first-in-class molecule. It's an allosteric modulator at the 24S-hydroxycholesterol's binding site on an NMDA. And what we've seen is by interacting with that binding site, we're having unique effects on cognition. Not simply memory or not simply attention where there are drugs that might have such effects. But on more complex behaviors, we call it executive function. It's the ability to both plan and carry out complex tasks. And what we do in our early phase trials, and we did this back with 217 when we were -- and brexanolone, even when we were first exploring the potential utility of the mechanism is we start with the first disorder where we have a strong mechanistic hypothesis. So first, we've seen in healthy volunteers that we're seeing effects on executive function. We moved to Huntington's patients for exactly that reason. It’s a biomarker that's associated with the cognitive disorders of Huntington's disease that lead us to think that this is a reasonable first step. The question we have now is, is this a fundamental mechanism for cognition? Or is it something very specific about Huntington's or other disorders that are affected by 24S-hydroxycholesterol. And the only way to get at that question is by exploring other disorders that are cognition, yes, but also executive function deficits. So as we go further from Huntington's disease first to Parkinson's disease next to Alzheimer's, we'll understand whether this is specific about those disorders that are directly related to 24S. Or can it be more fully extended into a broader impact on cognition. So this is our approach that we've always taken when we move into entirely new areas of science, which is we do exploratory work, identify those areas where we're going to have the potentially highest scientific value, but also the potential highest impact for patients and use those early phase studies to explore further. And Kimi, maybe you want to comment on this because this is very much reflective of the way that we approach our entire portfolio.

Yes. No, it's been a very capital-efficient way for us to do development. When you think about, we did it with allopregnanolone and did it with GABA, and now we're doing it again with NMDA. But that -- that's been our approach of really derisking and finding ways to really make sure that what we do now will enable us to do something more efficient going forward. So what we've learned in these smaller trials, we can then translate into how to best structure the next trials that are going to be bigger and more expensive and make sure that we have a higher probability of success on that. So that's been a key aspect of that. How we think about investing in the portfolio and across the portfolio.

Understood. Understood. And maybe to sneak in one more question for you, Kimi. Let's say, is it out of the question, let's say, 324 data looks phenomenal, and the stock is in the 100s like are you not -- is it out of the question, Sage could do an equity raise heading into the 217 readouts? Or is it like, no, we're going to wait at least for one of these 217 readouts to come out before we start thinking about capital raises.

Well, look, Akash, what I could tell you now is we have $670 million in cash. And on our last cash OpEx for the quarter, last quarter was under $90 million. So we're in a great position. And what we've talked about is the fact that by virtue of being efficient and really managing our burn, we have runway into 2022. And so we've been very careful managing the burn. We've been seeing operating efficiencies. And so I just think we're in a great position financially to execute on what we need to execute on. And that includes, if we're successful in 324 and 718.

Understood. That would answer. So maybe getting on to 217. Yes. But I'm very glad you saved me from a headache that the 50 mg dose was at least numerically higher than 30 mg. I was going to -- that was just bracing for like a 20 calls on this if it wasn't the case in SHORELINE. But to me, like the more I feel like -- I've understood and honestly, the more I hear from you guys in terms of why did not have the result it did, it seems like 50 mg, like, yes, maybe there is some modulation on extrasynaptic by going up to higher doses, maybe there isn't. But 50 mg seems more like I'm going to get a more consistent effect across different patients in a Phase III set. So let's say like 30 was the same at 50 mg in SHORELINE, would that have changed your mind on going to 50 mg in your upcoming Phase III trials? Like what have you learned from the SHORELINE data and particularly efficacy and safety performance in 50 mg that you think is actually meaningful for investors? Or do you think not -- it wasn't surprising at all, and we shouldn't really read into it.

So yes. So first of all, I'd say the SHORELINE data, we can talk about that at length is just more a proof point of the profile that we've seen in -- with 217 where we see rapid improvements in symptoms, sustained improvement. And perhaps most importantly, the first real proof point prospectively collected that supports the idea of episodic treatment. We've been talking for years about what happens after day 42 and what happens after those periods of time that we're looking. And here for the first time, a very large study -- the largest study of its kind ever conducted in a development program, we're seeing patients that have long periods, treatment-free intervals. And with 70% of the patients requiring no more than 2 treatments in a year, think about what that means, it translates to 48 weeks out of the year where patients don't necessarily need to be on therapy. That's the vision of 217. So that's the main takeaway. The data that we just recently disclosed had to do with the first dose of 30-milligram dose, and those are the ones that are the most complete. And what we've seen is some really fundamental pieces. We didn't see tachyphylaxis, meaning the patients had similar responses each time they were treated. Majority of patients require only 2 treatments over the course of a year, and we didn't see any differences in terms of the overall benefit risk profile. And that's true both for the dosing period as well as for the period into -- in between doses. So really -- assuming that we move forward and everything is approved, this really presents a vision for what this program will look like when it's approved. We've included a 50-milligram arm, and these data are still being collected. So the SHORELINE cohort was initially enrolled. So we're only talking about the very beginnings of the data set. But we were looking at it for the same reasons that you're asking. What happens with those 50-milligram patients? Are there safety changes? Are we seeing improvements overall in responses? So it's not set up to be a comparison trial that said, I understand you're trying to sort of understand what these differences mean. Let me put some context around this. One point difference is a substantial difference on HAM-D. Approved antidepressants like a Prozac or Zoloft, if you look at meta-analysis, or the difference from placebo is somewhere between 1.2 and 1.4 points on the HAM-D rating scale. I'll say that again, the difference from placebo at 8 weeks for approved antidepressants is just a little more than a point. Here, we're implicitly comparing to what we believe are efficacious doses to each other, and we're seeing that differentiation. And while it's nominal and it's not statistically powered, it is a very different discussion that is going in the right direction. So that's number one. So it's -- I would not discount that one point difference. That's very important for us. The other is -- the other place to look, and I think this allows us to compare apples-to-apples a little more effectively is look at response in our remission rates because that is the answer to your question. When you see higher rates of response and higher rates of remission, that speaks to a greater proportion of patients that are overall having those responses. And that's what really what we'd be looking for. There'll always be people that don't respond to a particular medication. But if you increase the proportion of patients that have responses or complete responses, that's what's important, both in terms of the benefit for the drug as well as our understanding of what those dose changes might be. Of course, the flip side is we haven't seen any substantial or significant changes in the overall safety profile. So those are proof points for us. I mean the study is still going on. So I just want to make sure that people understand that we're still following these patients, but really encouraging and we're really encouraged by what we saw, and we're excited to get that out into the world.

Understood. And as we think about -- like there's certain wall where I think we just have to believe that you guys are going to take care of it for Phase III, which is things like the food effect. And it seems like that is something that you guys have also kind of actively talked about. If I'm an investor and I was saying like, well, MOUNTAIN is a really important trial, like how can they take care of the food effect, they knew what it was. A, do you think 50 mg controls the food effect or no because if I'm not having the right oral bioavailability, I don't care if it's 30 mg or 50 mg, I'm not getting to my efficacy threshold. And then b, from a trial perspective, a protocol perspective, how can you emphasize that aspect more than you did maybe before, like what would make someone who is skeptical feel more confident on the food effect issue?

Yes. Are you talking about what lessons do we learn from the MOUNTAIN Study? How are we applying them into the protocol? So I mean there are a few. We talk about things like food effect and so forth. I mean I think at the end of the day, the things that are really going to move the needle for the trial are the ones that we are -- we've already talked about, which is increasing the dose, and that just increases the proportion or decreases the signal to noise, whatever you -- however you want to describe it. Also, increasing the HAM-D cutoff for inclusion. That's really important as well to allow for those larger changes from baseline and that sort of increases your likelihood of statistical demonstration of deltas. The other piece of it around things like food effect, first of all, many drugs required to be taken with food. What we've learned is to be more specific around -- taken with a meal and so forth, but that's -- I would say that is the -- it's something that you do every time you do a trial, you sort of get more and more specific, the more you learn, the more you're able to actually be specific on how to instruct the investigators to tell the patients what to do. So a drug that works is going to work in the real world. But the ones that we've talked about in terms of dose as well as in terms of HAM-D cut-off and so forth, are the things that we think are really going to move the needle for subsequent studies. Those are the things we did in MOUNTAIN -- in WATERFALL as well as in CORAL and SKYLARK, the rapid response therapy trial as well as the PPD trial.

Understood. Now on 217, I'm always fascinated when you talk about this concept of exposure and it seems like the assay that you were having in MOUNTAIN, like it was very sensitive. You were able to really monitor this, I think, into an unusual extent for a depression trial. You've talked about you've internally broken down low exposure and then high exposure patients and then seeing that those who were high exposure were [ static ] versus those who weren't. Can you give us some color, like what percent of patients in MOUNTAIN were kind of deemed low exposure? And how did you define that? Because I'm obsessed with 50 nanomolars because that's all I see in that silly SAB study that I have. You guys have more data than me. And I don't know how it changes as we go into [ SAD to MAD ]. So what is low and high exposure defined by Sage internally for MDD? And then what percent of patients were deemed low exposure in the MOUNTAIN Study?

Yes. So let me just be clear, when we were talking about patients that were not -- we weren't really referring to patients that were -- had low exposure. The patients in our -- in the treatment arms that didn't have responses had no exposure. So these are likely patients that didn't adhere to the study protocol itself. The other question that you may be asking is about our PK/PD modeling in terms of effect. And I won't get into the details of that from a technical perspective, what I'd say is the following. In the MOUNTAIN Study, we did, we had 2 treatment arms versus placebo. One was 20 milligrams, one was 30 milligrams, placebo 0 milligrams. 20 milligrams and 0 milligrams were no different from one another. 30 milligrams separated day 3, day 8, day 12, day 15. Higher doses predict, as you probably imagine, a higher overall plasma level. And it's there using those 3 data points that we're able to start to extrapolate the relationship between exposure and response. That doesn't -- and it doesn't translate, and I know this is probably the next part, which I will answer it. It doesn't translate into an individual's response, when we say, root wise response on exposure and dose. And so part of the goal of the program is to have more than one dose, of course, you want to have more than one dose and the ability to adjust doses. There's only one direction to go from 30 mg, you go up. And based on the modeling, 50 milligrams would certainly do the trick. Obviously, in SHORELINE, that's our proof point, right, because we're already seeing those -- again, I don't want to over [ call ] it to the study that's still in process, but we see nominal increases in the overall change from baseline in HAM-D scores as well as changes in response and remission. And that's what we would have predicted from our model. So you move forward based on the data, you collect the data and continue to move forward. But really, what we're seeing across the board is a very predictable and now increasingly reproducible response rate. And that gives us a lot of confidence in the profile that we're seeing with 217.

Understood. And just to be clear, like, would your assay be able to detect like this guy probably didn't take -- correct me this, right? Like would they be able to detect maybe not noncompliant in terms of just not taking the drug. But would you be able to detect patients who weren't maybe following the protocol precisely as you've laid out?

I would say this, it is a very sensitive assay. The ones that we -- the only ones we need to exclude in order for MOUNTAIN to be positive are the ones that had no detectable levels period. That is not an effect of food.

And to be clear, going into your Phase III trial, have you changed it so that noncompliant patients are not going to be considered a part of your primary analysis, that's one question. And then the second one is, like, let's say, you're on 50 mg, you got down-tritrated to 30 mg. That to me indicates, you know what, I was getting good exposure at 30 mg anyway. So are they included also in your primary analysis? Or are they kind of excluded and kind of a secondary end point?

All patients --- so all patients that are randomized and are given any dose of drug are included in our assessment, that's by rule. Of course, we do other sensitivities, analysis and so forth. And obviously, I'm not going to get into the details of this physical analysis plan. But the intent for this is a registration program is to do a very straightforward intent-to-treat analysis and use that as a primary analysis set.

Wait. So you are. Are you -- so patients who get down-tritated, they're still considered intent to treat. So they are…

Absolutely. Absolutely. Yes. Yes. Anyone -- and by the way, everybody does this. We've been including the ability to do down-titration in all of our studies. We've done it in ZULRESSO. We did it in all of our prior trials. It's a vast minority of patients. It was a handful of patients in the MOUNTAIN Study and the other 217 trials. And it doesn't change overall. Obviously, it's small numbers so we can't do any sort of exposure or response as to where we're getting at. But we would not exclude them nor do we anticipate that, that would have any effect on whether they do or don't respond overall.

Understood. I think we're near the end of the time. So I will sneak in one more question. I know -- I would love if you were to tell me the details of your statistical protocol. It is interesting, both that the mix means a statistical analysis you did give. I mean it did give even more leeway than I think a lot of investors understood. And to be fair, a lot of people forget that 2-point HAM-D is actually a 3-point matters effect. But it looked like even if you had hit something slightly below 2 at day 15 for MOUNTAIN, that was enough to be statistically significant. You've obviously increased your sample-sized through your WATERFALL Study. And now it looks like you're 90% powered or more, so very similar to MOUNTAIN. Is it unreasonable for me to think, you know what, they could have hit at 2 or a little lower than that in MOUNTAIN, that should be a similar worst-case scenario to squeeze by and still be [ static ] for the WATERFALL Study.

Just to be clear, we were adequately powered before we do anything in terms of upsizing the trial. That was only about looking -- given the fact that the velocity of enrollment has actually been quite good. Without changing guidance, we've had the opportunity to start to potentially be powered for some of the secondary end points and subgroups that we often talk about. And so we had the opportunity to do that. And so we did. And we typically do that. We've done it in many of our trials. When we have the opportunity, we do that. But we were adequately powered for a 2-arm study, recall this is a 2-arm study not a 3-arm study prior to doing that. Based on the totality of the data, we don't look just at MOUNTAIN, we look at all the studies in 217, and that's the way regulators look at it, certainly the way that we look at it for all of our data together. So again, really confident in the program that we're seeing with 217 and its profile. And the study itself can be alluded to this, has been enrolling well. We're getting rolling with the majority of our trials, including all the others in 324 and 718, and we're just looking forward to updating everybody on progress.

Got it. And just last question. Would you be -- like would you be open to say, like, hey, here’s the baseline characteristics of our enrolled population for WATERFALL, like HAM-D is 27 baseline or here's the standard deviation of HAM-D. Is that something you would be open to sharing before the data comes out or probably not?

No. With all due respect, we will reserve the data readouts for when we have the data. And that's -- and that's not to be flippant. These are registration trials. And any kind of data readouts that we have, we’ll do, when we have this data, when it's all been signed, sealed, delivered, sourced and verified and really represents the outcomes from the studies. That's particularly for placebo-controlled trials. Very important that we do that and do it properly.

No, that's fair. That's why I don't listen to crazy sell-side analysts but your actual clinical data.

No, I mean I understand why you’re asking. But we wouldn't do that. We never have. So...

Well, thank you so much. I really did enjoy the time. If you guys -- on the call, if you have any questions, please reach out to Sage management or shoot me an email, otherwise, have a good day, and have a good weekend too. I'm looking forward to it.

Thank you. Thank you very much, Akash.

Thanks, Akash. I appreciate it.