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

Hi, everyone. Thanks for joining us this afternoon for the Sage fireside chat here at Cowen's first Annual Neuropsychiatry Summit. I'm covering analyst, Ritu Baral. And joining us from Sage is CEO, Barry Greene, and long-standing CMO, Steve Kanes, who most of you know. So thanks, everyone, for joining us. E-mail me any questions as we go along or submit them in the chat.

I guess zuranolone is going to be the main focus of this conference. We've been focused on depression and PTSD all day. Steve, can you -- just as a reminder, sort of briefly take us through zuranolone mechanism. And I think we've all heard this, but one of the biggest criticisms of the mechanism and especially in terms of your most recent data was, from the investor side, how is this mechanism not just in benzo. So as you take us through the mechanism, take us through those differential points in particular.

Yes, Ritu, let me just start saying, thanks for having us. Appreciate it. Appreciate Cowen for organizing it. It's a very important meeting, a very important set of topics, and we're thrilled to participate. I want to let Steve get into zuranolone and the differentiated mechanism of action. It's very important. Before we do, I do want to remind everybody that Sage has been studying brain circuitry for about a decade and has a deep understanding, both of GABA and NMDA, and has translated that understanding, as you're well aware, with the first ever drug approved for postpartum depression. So the approach that Sage has used, in fact, one of the reasons I joined in December, it's deep understanding biology coupled with novel chemistries that are producing real medicines that help people get better fast and stay better is important to the central thesis of Sage. We believe that we're a leader in brain health, so thanks for having us at this conference, and can be a top-tier biopharmaceutical company, given even after zuranolone and the rich pipeline that we have with 324 and 718 and the rest of the pipeline. So I wanted to get into zuranolone, but I do want to remind everybody that we have an entire pipeline and we're a multiple product company, all in brain health with these novel insights.

Yes. And hopefully, we'll have at least a couple of minutes left over to touch on NMDA and how -- and your NMDA platform, too. That is super important. So let's get into the -- how is zuranolone not a benzo mechanism?

Steve, do you have to take that?

Sure. Well, we get this question a lot. There are a few key pieces here. One, we hit different receptors in benzodiazepine. So we talk about these extrasynaptic receptors. That's number one. Number two, we interact with the population of these receptors in a very unique way. And perhaps most importantly, what we see is profound and rapid effects on depression that are long-lasting, long after the drugs are -- patients have completed their course of therapy. So that's a very distinct profile from anything you would see with the benzodiazepine, and we think that's based on the underlying signs.

How -- I guess benzos KOLs have indicated have more rapid and have some effect on depressive symptoms, maybe not depression overall, but some impact on depressive symptoms. And they are considered more rapid certainly than SSRIs. But as far as elements like time course of impact on depressive symptoms, maybe not MDD overall, but depressive symptoms that are manifested and tachyphylaxis of benzos and the safety, tolerability profile, including sedation rates and somnolence rates. Can you sort of highlight the differential for the...

Sure. Yes. I think primarily for benzodiazepines, they're used as anxiolytics and sometimes as sleep aids. They are sometimes used in conjunction with SSRIs. But what's very different about what we've been seeing is a few things. One, we're not seeing tachyphylaxis, meaning the effects of these drugs over the course of treatment don't wear often, and we've shown that that's true, whether it's over the course of 2 weeks or with repeated use over time and we can get into those data. The second, and I think this is probably the most important part of it, is we're seeing true improvements in the core symptoms of depression. And that's not just sleep or anxiety, that's depressed mood, decreased interest, inability to functioning one's role, appetite, energy level and so forth. So those are the core symptoms of depression. And in study after study, we've been able to demonstrate that we're improving those core symptoms. And we're in a durable way, long after the patients have stopped taking medication. And we saw that in the WATERFALL study, perhaps most dramatically in our SHORELINE trial, which is where patients were treated for 2 weeks at a time, and we've seen that greater than 70% of patients needed no more than 2 treatments or 2 14-day course of treatments in a year. So really long, durable effects on depression, which we think is transformative for patients.

So that subscale benefit on those different subscales, is that appreciably different than the subscale benefit with benzos?

Well, I'll comment. Steve has seen this a lot more. So Ritu, if you look at the body of evidence on benzo, it's not actually clear that it's working that well for any of the depressive symptoms, including sleep and anxiety. We're seeing benefit across, as Steve said, mood, anxiety and sleep interruption. That's what you want in an antidepressant, and it works quickly.

Got it. And as far as the tolerability profile, somnolence, sedation, et cetera, like what was the profile seen in the benzo depression studies like the '90s versus what we've seen most recently?

Yes. I think you'd have to -- first of all, the evidence level is really rather thin for benzos in published trials. But yes, the primary role for benzos, particularly in the '90s, and I was in practice at that time, was actually to help with anxiety and sleep in these patients. And so yes, there are very high rates by intent, in terms of anxiolysis as well as patients getting sleepy. Many of the patients with major depression actually have sleep disruptions. And so they perceive that as a benefit, albeit with benzo, it's a very temporary one. So we can get into some of the data that we've seen in terms of durability on effect, but we know that we're having benefits, long-lasting benefits, not only in core symptoms of depression, but in anxiety as well, and we do have some early evidence that we're improving sleep and sleep architecture. So again, a very unique profile, very different from what's seen with benzodiazepines. And while sometimes people sort of confuse GABA with benzodiazepines because that's kind of what the standard treatments are, we're talking about a very different class of medicines, one that we think is very important for patients.

Got it.

I'll just add a little bit that everything Steve said is recognized by the FDA because of the breakthrough status, it would not give benzo a breakthrough designation.

Got it. That's fair. So WATERFALL top line day 14 efficacy data hit statistical significance, but the market was not happy with that delta. Again, how should we be thinking of the clinical meaningfulness of this delta? We had our regulatory consultant a couple of panels ago [indiscernible] [ MCID and Neuropsych ]. The meaningfulness is in -- it's not. And then as we think of that benefit, how should we be thinking of it in terms of the magnitude of the placebo effect that we saw in that study?

Yes. So I'll say a couple of things here. So first of all, Ritu, is that the market didn't like -- fortunately, we're treating real patients with doctors that understand these data. And as we educate the potential prescribing physicians and the KOLs, they understand that patients are getting better fast and stay better longer. When you look at the totality of the data, if you were a patient, wouldn't you want a drug that you were better after the first or second night and you slept well and you were told that potentially, you might only need 2 or 4 weeks of therapy in the course of the year. So you're not being defined by taking your depression drugs every day, which gives you a whole ratch of side effects that we don't have. So we think about this from a patient perspective. When we look back and look at all of the Phase IIIs we've run, the day 14 HAM-D reduction falls somewhere between 12 and 18 points. So 14.1 points is right in the range of what we've seen across the totality of data over 3,000 patients or subjects treated. So what that means to a patient is they get better rapidly and they stay better longer. Probably the best evidence of how well the drug works, and Steve mentioned this already, are the SHORELINE data. While SHORELINE is open label, the data we presented in the full 30-milligram dose set suggested that most patients only needed 2 or 4 weeks of therapy in the course of the year. So these are patients that are MDD patients, they know they're not on drug, I think, 15, 16, 17, 18, we check in with them frequently to make sure that they don't need another course. So they're [ hampered ], are you depressed, are you depressed? And yet, they don't report being depressed. Again, in fact, they report staying in a normal state. So when you look at those body -- the body of data, it's pretty clear that this is going to be an important drug for people with depression across the world.

So I think our KOL panels in our sort of mainstream neuropsychiatry KOL session in the middle of the day all acknowledge the -- all of the data supports activity of the GABAergic agents, the GABA-A PAMs, I should say, on this. They did note that the placebo -- like all depression studies, placebo rates make things really, really hard. And it can be hard to tease apart the magnitude of benefit or really characterize the benefit because of placebo. The placebo arms in the 6-week studies are much more shallow than the placebo arms in your study because of the placebo effect in anticipation, et cetera. So is there some way that investors should think about teasing apart what can be seen by anticipation or placebo in the -- out of that sort of gross improvement in the HAM-D as you have described it from baseline?

Yes. So I'd say a couple of things. First, our industry has been trying to figure out placebo effect on depression studies for a couple of decades, 35 to 50 years. And Steve will provide some more insight. But that -- as you said, that's a big challenge. What's important -- and obviously, when you conduct the clinical studies, you want to minimize placebo so that you tease out the drug effect. We've done that. As early as January, Steve and I were saying to everybody, "All we're looking for is a statistically significant result at day 15 and no surprise on adverse event." We've got that along with the other positive study, the totality data, we believe we have an approvable package, and we stand on that today. So if you believe that we have an approvable package, in the real world, a drug like this performs incredibly well because in clinical practice, wearing a white coat, you want patients to get better faster. It's the drug that's doing it but interfaced with their medical professional, if that helps, that's great. That's great from a patient perspective. What we're really looking for is for patients to get better and stay better and not need drug until they need it again, hence the as-needed basis.

Yes. And I would say in clinical practice, Ritu, I was doing this a few years, and I'm sure you're talking to experts in the field, like understanding what you're going to get from the medicine when you prescribe it is absolutely critical. So when I look back across all of our trials, ultimately, yes, as Barry said, you need to -- the technical question is, how big does the study need to be to separate from placebo and your primary endpoint? It's a technical question. Once you've done that, the next thing you need to understand is what kind of benefit should patients anticipate? And that speaks to what does the drug do. And when we look across all of our studies, we see a very consistent overall drop from baseline. These 15 points, 16 points drop from placebo, even in the first days before there was any expectation by us, it's exactly the way this drug has performed. And it's done it in study after study after study. And that translates into patients understanding what their potential benefit might be and also the predictability for physicians on what they'd be able to expect. And that's translating exactly into what we're seeing in WATERFALL, where that is real-world data. Patients are coming as they are. They're getting treated. They're getting better and they're staying well. And that's the reason why we did that study is we'd really be able to illustrate what does an entire new treatment paradigm look like for these patients. And the totality of data really do support that. For many patients, this approach could really be a game changer. And it's not about any individual study, it's about the entire thing in its totality.

Got it. Okay. That's helpful. And as we see the WATERFALL data presented in scientific forums, what expectations would you set for effect size, responder, remission rates? I mean I've had clients ask me for exact numbers on what I -- actually, percentage probability that your effect size hits like 0.3. Obviously, you can't tell us what the effect size is now, but that's sort of what everybody is waiting for next.

Well, we'll present those and the subscale data and patient-reported outcome data in congresses to come. Our team is rolling through those data now. But in early looks, I think as we present more and more data, I think people are going to understand even better how well the drug works across the totality of measurements, the totality of data.

Got it. Anything in this -- have you done any analysis on the subscales? Does that look appreciably different from any of the subscale analysis from previous trials for any reason given the changes in WATERFALL or COVID, et cetera?

We're working through this -- that now, but -- and thanks for mentioning that. I guess the other highlight to having a statistically significant -- the positive study here is this was done in the heat of COVID, which nobody had ever done depression studies during a time where the whole world was more anxious.

Okay. So is there any wrinkle or detail in the data that might -- that could be COVID-driven from what you're seeing? Or is that going to be part of the analysis presented?

We're doing all those analysis now, but you highlighted this earlier. The placebo effect here was about a point better than a placebo effect in all the other trials. That could be expectation by us getting greater. It also could be there's something about when someone's locked up in their home in COVID and you bring them into a medical facility at day 3, 8, 12 and 15, that medical interface might be helpful, which is what we may be also seeing in placebo. Importantly, we emphasize again, even as robust the placebo effect was, the drug effect was clear and in the range and held out to day 42.

Okay. Got it. What about the sort of decline of effect at day 42? Again, there have been discussions around the fact that this means there is no discernible effect at that time point. But what are the best metrics to tease out what benefit either responders or remitters still had at that time point? I think you guys mentioned, I think it was like 86% retention of benefit out from day 42 versus day 14. Are you talking about -- was that like a continuous variable analysis? Or was that like percentage of remitters and responders who still met those criteria at that point? Can you clarify that number?

Yes. Steve, do you want to take that?

Sure. I would just say, rather than get into the statistical analysis plan of the trial, there's 2 things. One, if people are interested in our statistics, rather than going into it here, probably the best sort of discussion of our statistics we had at the New England Journal of Medicine Paper, it lays out all of the statistics that we do for our trials, and we use the same approach across all of our studies. What we're referring to here is something that's really important conceptually, which is rather than thinking about delta from placebo at day 42, we look to see whether patients maintain their benefit. And what we said is that when you look at the overall change from baseline at the end of treatment, you carry that out through day 42 and you look at whether or not those numbers are the same. So it's 2 things we learned. One, those numbers are not statistically different. So we know that patients aren't having statistically significant changes in their overall change from baseline. The other is that if you just use the raw numbers, it's 87% of the benefit that they had seen at day 15. As we move forward, what we'll do is something more detailed, which is, are there -- is that driven by some patients having some beginnings of recurrence of symptoms coming back? What proportion of patients stayed absolutely flat? That's not really the right study to get that kind of information from. That needs to come from studies like SHORELINE, where we actually follow patients longitudinally over the course of a year. So the important part is the patients in this trial, just like in every other study, didn't have a bounce back of their symptoms at the end of treatment. That's what you worry about. You don't want to go right back to your baseline. That would be a very temporary benefit. That would be of no meaning to patients. What we saw here is patients that got better on the main, and this is -- 87% of that benefit is maintained over the course of this follow-up period, and we have much more follow-up that comes from other studies, both for MOUNTAIN as well as from SHORELINE.

And we'll have -- as we present more data, we'll have patient-reported outcomes, so we'll have data from patients at day 42 talking about how they feel. And my bet, I haven't looked at those data yet, is most of them are going to say they got normal and they stayed normal, which is what we saw from SHORELINE.

Yes.

Got it. Let's talk about safety for a second, and then I want to talk about SHORELINE and the more -- the upcoming data, additional data that SHORELINE will generate. But safety, somnolence and sedation, first of all, I think it's worth clarifying the difference between the 2. I've had this discussion with you guys, but it's been another investor conversation. And then what's acceptable as you viewed it given the 2-week dosing paradigm? And I guess what the alternate side effect profile is from other approved therapies?

Yes. So as we've been getting feedback from various KOLs, a couple of things are really there. One, as they're looking at the data, the benefit-risk here is substantial and clear, and we're getting that across the board. And what we're hearing is the safety profile is actually better than the drugs they have today because of what they're not seeing and safe -- Steve can talk through that. In terms of taking your pill at night with your meal and being tired and going to sleep and getting a good night's sleep, that's actually a benefit to patients, not a detriment. And even to the extent that a few patients may feel a little sleepy the next day, we're talking about a 2-week course of treatment. So if you have an opportunity to getting better fast and staying better, and in the rare instance where you might be sleepy for 2 weeks, I think that's a profile of a drug, if you're one of these patients, you'd accept. And I think that next-day sleepiness is actually a small portion of these patients.

Is that going to be part of the WATERFALL safety analysis going forward, some of the next-day sleepiness measures?

So we will have some information in terms of patient-reported outcomes, and Steve will talk more about this. But the adverse events are reported at any time. So when you show up at day 8 and you tell the physician, I was -- I had my dinner at 7:30, I fell asleep by 9:30. I'm really tired. That gets reported an adverse event. They're not discerning exact time points. They're at any point in the study period.

Got it. So you're not proactively asking patients at 8:00 the next morning or were you -- 2 days later, are you sleepy at 8:30 in the morning when you normally wake up at 7:00 or something like that? It's not a proactive assessment?

We'll have data in the patient-reported outcomes that help us understand that.

Got it.

Yes. There are a few things I can give as a little more granularity on this. So Barry presented at JPMorgan an analysis that we always do, which if you look at things like number of patients that drop out of our trials due to adverse events, as an example. And the number in our prior trials now, we're still integrating this data set into our overall data set, what we've seen so far is that that's equivalent to placebo and very different from other antidepressants. And that's a really good way of understanding really what's behind the question that you're asking, which is how likely is the adverse event profile to be a disincentive for someone to stay on therapy. And to date, that's been -- it's been very low. Very few people dropped out of our trials due to adverse events. So that's number one. And you asked about somnolence and sedation. So somnolence, I'll just give you the straight-up definition. Somnolence, sleepiness, we all know what somnolence is. You're watching TV, maybe it's golf. You're dozing off. Your mother calls, you wake up and you're able to talk and you're totally together and everything is fine, you've dozed off. That's somnolence, sleepiness. Sedation is a little bit different. That's if someone really is less responsive. The phone rings and they don't really or they very sluggishly respond. That's -- it's a little bit different. What we've seen primarily is mild to moderate somnolence. We do see some, obviously, sedation. It's a little nonspecific out in the real world where people are calling one versus the other. But overall, the numbers that we've seen are low. They are comparable to what we see for other drugs that are used to treat depression, not just benzos or other things to help with sleep. So the kinds of things that people drop out of antidepressant treatments for are things that are really kind of awful. And we know about them from the lay press: sexual dysfunction, dry mouth, urinary retention, GI upset, sleep disruption, abnormal dream...

Weight gain.

Weight gain. I mean there's so many things that people have as adverse events when they're taking antidepressants chronically. We're talking about SSRIs and SNRIs that we are not seeing. And usually, at this point, I'd also add that we are also not seeing in the 3,500 patients that we try to set in so far, we have not seen anything like loss of consciousness or anything more drastic.

Yes. I would always check the box.

Yes. Well -- and so that -- but these are the things that we look at. So the pertinent negatives are just as important. And now as we start to think about this, it's less about an individual study, Ritu. It's now about looking at all of the data combined, particularly on the safety part, where we'll see if there's anything else that's coming up. But to date, it's been a very clean, very safe profile. And it compares very well to drugs that are prescribed for these patients and has resulted in very few dropouts across all of our clinical trials. And we think that's going to track forward, assuming that we're approved.

Got it. Let's spend a couple of minutes on the data, the additional data and additional analyses that we should keep an eye out from SHORELINE and its continued conduct and analysis before we talk about other indications, and hopefully, get to spend a minute on your NMDA platform. So SHORELINE.

Well, so we -- as we've committed, late this year, we'll have the full 50-milligram dose or we'll have -- as we are by the end of the year. Obviously, we've expanded the study to a lot more patients to benefit by the study. So we'll take a snapshot at the end of the year. And I anticipate having a higher response rate, and we'll see is it 70% or 75% or more percent of patients require 1 to 2 weeks of drug in the course of the year. So we'll present those data at the end of the year and share those full sets analysis. Again, big unknowns here, Ritu, is while we were in COVID, there were times where everything was locked down, times were not. So it'll be really interesting to look at the temporal nature of those data as well.

Yes. Got it. Okay. And then other indications, especially as part of your partnership with Biogen. They're a little busy right now, but hopefully, you've continued to have conversations about where you could take the mechanism -- yes, where you could take zuranolone as far as other indications?

Right. So as we talked about, and Steve already mentioned this, with the data we have now, we've seen benefits in depressive mood, anxiety and sleep architecture. So there's a number of future studies in general anxieties, very seasonal anxiety as well as others that we're interested. But what we also saw, Ritu, and you saw this yourself, is we are reimagining depression and reimagining the treatment of depression, otherwise called the paradigm shift. When you're shifting a paradigm and people look at data, it's often not intuitively obvious that depression is different than they thought, and you treat it differently. So it sounds like your panel today was understanding the data. But when the data were first presented, a lot of people didn't understand the data. So we've agreed with Biogen that we need to do all we can in depression first, and all the studies we need to do depression first so that we have a solid baseline, if you will, winning in depression, then we'll get to the rest of the indications. But we will get to those other indications but as a step or part 2.

That's fair. The idea of the paradigm shift and the heavy but possible -- not impossible, lift that, that would require came up in each of our panels. Okay. And then in the last couple of minutes, let's talk about the NMDA platform and next catalyst, especially additional efficacy data around your cognition programs and then what indications it's particularly promising afterwards as well.

Look, we probably could spend the whole 30 minutes on NMDA, but let's...

You have 3.

Oh. Let's just take 718 as the example of the platform that's coming. And you may remember that in January, we were highlighting that SAGE-718 was one of the most exciting programs in the pipeline. Why? Because we're up-regulating NMDA in a unique way. I won't get into all the details now. And while early, we saw incredibly promising data in Huntington's patients in terms of executive function improvement and memory and learning. We then followed that up with data in Parkinson's patients, again, supporting what we believe in Huntington's but now in Parkinson's patients and we'll update it on Alzheimer's patients later this year. The data we saw in Huntington's and Parkinson's allowed us to declare that we're moving forward in Huntington's as our initial indication. And we've got alignment with the agency on a path forward for Huntington's indication. If all we had was a drug for Huntington's disease, that will be incredibly exciting onto itself because there's nothing out there that can help Huntington's patients maintain their independence for another 10 or 15 years before their motor skills might start giving out. So it's very -- it's early but very exciting. If we can allow neurodegenerative patients to maintain independence for another 10 or 15 years because they have their executive function, they can make a list for the store, they can go to the store, buy their groceries, come back, put them away and remember where they put them, and therefore, maintain -- as an example, maintain independence. That's going to be incredibly powerful for not just the Huntington's population, which is a rare disease, but for the millions of other neurodegenerative patients out there. I guess I'd end with from a Sage strategic perspective, if it continues to be successful, we have a pipeline and a product and something that we can globalize Sage on the back of because it is an orphan disease and a place that we could start in places outside of the United States. So very exciting for us, for our future and help us become a leading biopharmaceutical company.

Great. And when will we see the next data from 718?

We said late this year, we'll see the Alzheimer's data.

The Alzheimer's data, great. Any expectations for a differential effect in Alzheimer's versus Parkinson's versus Huntington's? I mean Huntington's is hypoactive NMDA signaling, correct? But Parkinson's is sort net normal.

Well, we started with the place, the biologic hypothesis. 24-HS was started on with a more homogeneous-type patient population. Parkinson's is a little less. And then when you get to Alzheimer, it's incredibly heterogeneous. So don't know what we see until we look at the data. But I would expect, in a more heterogeneous population, we'll see some amazing effects in some patients, maybe less on others, but we won't know until we have those data.

Got it. Great. We're 1 minute over. Thank you, Barry, thank you, Steve, for the time and all the answers. For our listeners, if you've got any other follow-up questions, please e-mail me, I'll get the answer from the management team. Thanks, everyone, for joining.

Thank you. Appreciate it.

Thank you.

Bye.

Bye.