Thanks, everyone, for joining us today. For this session, we have Edgewise Therapeutics, and for those that don't know them, on stage today, I have their CEO, Kevin, and their Chief Business Officer, Behrad with us.
Thank you.
Thanks for being here.
Yeah, thank you.
So wanted to, you know, jump right into it. You recently just read out some really intriguing data from the DUNE study. You know, in that study, it had arms focused on McArdle's, limb-girdle, but also on Becker's. And, you know, can you talk about maybe what you learned about sevasemten with respect to Becker's disorder from the DUNE study?
Yeah. So, it was a great study. I mean, it's really... I, I would call it a mechanistic study. It was run by a very well-known investigator from Copenhagen, especially in adult neurology. And what he has been known for is trying to understand the relationship between exercise and biomarker data associated with that exercise. And as you probably know, in both Duchenne and Becker, but other muscular dystrophies, they have elevated creatine kinase. So they have muscle damage associated with activity, and contraction of the muscles leads to damage. So what he's been doing is trying to quantitate that across multiple different indications. And so what we decided to do was a single-site study and evaluate patient populations where things like creatine kinase were elevated with exercise. And he's published papers on this.
So what we did was, just to describe the trial, we had the patient would come in, they would get a resting biomarker, which would be creatine kinase or troponin I-2, which is a biomarker associated specifically with fast skeletal muscle. And at rest, they would get a baseline. Then they would exercise the patient. That exercise challenge was about a 20-minute, 80% of maximal bicycle challenge, followed by a leg press challenge. So that was a fairly rigorous study and exercise challenge. The expectation is that you would see an increase in the biomarkers because of that exercise. Okay, so those are the baselines: a rest and an exercise. We then started dosing sevasemten 5506, we've just got our name for a drug, for three months. And then you repeat that experiment.
So before they do the exercise, before they take the drug, they get a baseline or resting after 3 months of drug, you give them exactly the same exercise, and you look at the effect on the exercise. And what we saw was... We did this placebo-controlled, so there were 6 patients, 6 treated patients and 3 placebos. And so what we saw was a statistically significant change in biomarkers looking at rest to rest. So basically, that validates the biomarker work that we had seen in the ARCH open-label study, and then we measured exercise to exercise. And in both cases, what we saw was about a 45 or so change in creatine kinase, which is very analogous to what we observed in ARCH, and then an 80, 80% change in TNNI2, which we also saw in ARCH.
So we saw that both at rest over a three-month period, but also with exercise. So why is that really important? So first, it's the first time we've studied patients in a placebo-controlled way, where we've demonstrated clear differentiation from placebo and benefit on the muscle damage biomarker. I think the other key is that our CANYON study. Now, CANYON is a phase II study in Becker muscular dystrophy with a defined patient population, and the primary endpoint of CANYON is CK, so the biomarker. So what we've done is actually demonstrate that, and increase the probability of success, that we will hit on the primary endpoint of our CANYON study. So that's really important because you'll hit the primary, and that's—I think that's now a higher probability of success.
But I think hitting the primary for CANYON was a requirement for going to the agency and showing them the entire data package that this drug has benefit in Becker patients. There's no standard of care in Becker patients. There's no treatment for Becker patients. The drug has been shown to be well-tolerated in the Becker population, and so these patients desperately, desperately need a drug or treatment. And so, and as we've said in the past, if we see a trend towards benefit on the North Star endpoint, which is a functional endpoint, and we see a trend in things like MRI, and patient-reported outcomes, we would go to the agency and discuss with them the opportunity for accelerated approval, for this drug.
So now we've hit. I think we have increased the probability of us going to the agency and having the discussion about how we might actually have this drug approved for accelerated approval. The other aspect, we gave an update of our various studies, is that GRAND CANYON is recruiting well. We started enrolling GRAND CANYON, which is our pivotal study, last October, and we anticipate sometime fourth quarter, first quarter of 2025 to have that fully enrolled. So when we're reading out the CANYON study, we will have essentially a follow-up study, a pivotal study, fully enrolled, that we can also to support the safety of the drug, and that we will test the clinical hypothesis.
Got it. A lot there. Maybe you wanna drill down on CANYON a little bit. So you mentioned, you know, as, as we understand, the primary endpoint there is CK, but there are a lot of focus on function. So, now, what do you think is possible to show on function on an SAA when you, when you get to the CANYON readout? Do you think you can hit stat sig? Obviously, you have some powering assumptions from how you've designed GRAND CANYON. I guess, how are you thinking about the likelihood of that occurring in CANYON itself?
Well, you know, the ARCH data was informative. Over a 2-year period, we saw an increase in function in Becker patients, and based on their natural history, we would have expected them to decline by as much as 2.4 points. So we had almost a 3-point delta at 2 years. This is a 1-year study. So, I think we would anticipate that we would see more than a point in change between placebo and treated. This study is 30 treated patients, 10 placebos. So that was the design of the study for 1 year. So I would say that we're not powered for North Star statistical significance. I think a trend would be very powerful. We saw many of the patients improve function.
So I think that that result, I think, has a reasonable probability of success in at least getting a conversation with the agency. But we are not powered for that. But I think directionally, since there is no treatment, it's certainly something we could discuss with them.
Got it.
And what's really nice about kind of the data that's there to support the North Star observation, right? It's if you look at the Duchenne space versus the Becker space, natural history in Duchenne is a little bit outdated, but it's also confounding because you look at that data, it's kids at different ages and different points in their disease trajectory with different steroid regimens, and, you know, they could be on their growth curve, or they could be on their decline curve, and it's really difficult to power a trial when you've got that much of a heterogeneous natural history. With Becker, there's a couple of things that work in your favor. One is, you've got three independent studies that have been generated in the last five years, so it's not like you're working off of old data, you're working off of current data.
You also have a patient population that doesn't have a standard of care, so there's no steroid use in these individuals, there's no drugs approved for Becker. So when you look at the natural history and you use the cutoffs that we've used to kind of select patients in Becker, which has been a limitation in this, in the Becker field, we didn't have the data to think about, is there a subpopulation that has a decline so we can power a trial? The consistency is between 5 and 32 individuals are declining 1.2 points on an annual basis. So that is current data, which helps us feel confident that going into kind of the data readouts, both CANYON and ultimately GRAND CANYON, that you've got a chance to at least see a trend with CANYON, and certainly we powered it for—overpowered it in, in GRAND CANYON.
I think the other key aspect of this is that, there's been a lot of discussion of, Well, is North Star a good measure? I think you need to think about the context of when you use North Star. Now, you think about it, a North Star in a 4- to 7-year-old population where you have 17 different activities, just think about convincing a 4-year-old to do 17 consecutive activities and how quantitative that might be with a 4-year-old. Now, think about it, and what would I do if I went to an adult? And can an adult actually perform the North Star in a meaningful way? And so I think for a, and this comes from our data of screening to baseline, that the ability to reproduce the North Star in the adult population is much higher.
In fact, even in the Duchenne populations, many of you have seen givinostat was approved by the agency. They were treating older kids, 6-15 years of age. The vast majority were in kind of the 7-9 range. Now, you have an older kid performing a 17-point scale, is gonna be easier than a four-year-old. So I don't think it has anything to do with the measure. I think it has to do with the population chosen at that time to actually do the measure. And I think also this idea of taking patients that might be a more homogeneous group in a decline, is something where you can blunt that decline and show statistical significance.
So I think we've really enhanced our confidence of the potential of seeing something meaningful in both CANYON and especially in GRAND CANYON.
Got it. On the regulatory side, with respect to Becker, you know, obviously, you guys are in the CDER division, which has historically been somewhat more conservative. I'm sure you guys read through the givinostat documents as well. There's some pushback there. I guess, how are you thinking about how amenable the agency actually is to an approval, an earlier approval of a small molecule drug like yours? I guess, can you comment on, I guess, the nature, the tone of the regulatory discussions you've had so far?
I think we've had both consultants and KOLs in with at the meeting and been surprised at the level of interest about the mechanism and the curiosity. I think it comes back to this, the first prerequisite is the safety profile. So we've shown now for two years and from our other safety databases that we have a relatively well-tolerated molecule. So that's the prerequisite for success. I think the second level of these plasma biomarkers and the utilization of this muscle damage effect we see in these diseases. I think the agency would argue that they don't disagree that muscle damage is something you would want to alleviate. They understand that muscle damage precedes loss of muscle, which precedes functional loss.
Their main issue with these surrogate markers is that can you measure them quantitatively? So what we've done and shown now that the DUNE data, you can run a placebo-controlled study and demonstrate statistical significance and not see crazy wide variability in at least the CK biomarker as well as the TNNI2 biomarker. So now the other question that they asked us was, there's an observation if you take populations. So if you take a Duchenne kid, you take five, six, seven-year-olds, they will have CKs of 20,000. If you look out after the disease has progressed, you look out when they're nine or 10 or 11 years of age, their CK has dropped. So the disease progression follows decreases in biomarker.
Now, you think about usually increases in biomarker are what people expect when the disease progresses, but you're decreasing the biomarker because they have less muscle, okay? But if you think about the Becker population over a one-year period, there should really be no decline. It's a slow progressing disease. So you should have a minimal decline in the placebo within the noise of the assay, yet we're going to have deep declines, like we showed in ARCH, with our biomarker. So that should be a stark difference between the decrease in biomarkers associated with a drug effect and not just the natural progression of the disease. So I think we can support this notion that the biomarker result and the quantitation of that biomarker result is real.
We'll support that with MRI data, and that's going to be differentiated from the natural history of the patients within our study. So all of those things together, I think, make a strong argument for—which, and this is really the argument we want to have, and the discussion with the agency we want to have is: Is blocking muscle damage good, and is it likely to predict clinical benefit? I want to have that discussion with the agency. I can't understand why decreasing muscle damage wouldn't be a good thing.
Makes sense.
Is there anything the agency cites that makes them question the validity of the biomarkers, or is it just sort of not enough data?
It's the variability, and so the variability is driven by activity. So, and there's some good papers on this, that if you have a Duchenne kid, in particular, and you have them off running on a jungle gym, you will see, you know, 2-4 hours later, you're gonna see an increase in creatine kinase. On the flip side, if you tell the patient to be quiet and don't move around and have them do that for hours, you'll have a lower CK. So the level of the biomarker can be driven by activity.
Now we've shown is that in this controlled data, you can measure that, and especially in the Duchenne studies and in the GRAND CANYON study, we have an activity monitor called a Syde device associated with these measures. We don't have this in CANYON, but the Syde device measures what's called a stride velocity 95th percentile, which is kind of the maximum stride velocity that you can see in a child or in a Becker patient. And that stride velocity 95th percentile is a primary endpoint in the EMA for Duchenne. And there's been a lot of work validating the correlation of stride velocity 95th percentile with North Star time to stand and four-stair climb.
I think there's a beginning to come up with an aggregate of data of how you quantitate both function and then tie that back to a biomarker simultaneously.
What makes you feel pretty good is, right, the ARCH two-year data. These are free-roaming Becker patients. So convention would suggest they're running around and, you know, in aggregate, they travel 190 miles to the clinical trial site. 190,000 mi, sorry, to the clinical trial site. So you would think that biomarkers would be through the roof because they're active. In fact, from the first dose cohort that we treated, which was at, I think, at 5, no, 10 mg?
10mg .
10 mg. Within a month, you knocked the biomarkers, and it stayed there. So they were active, but they weren't seeing an increase in biomarker despite being continually moving around, doing their daily activities. So that makes you feel pretty good that you're really dampening that biomarker response.
I wanted to ask on Duchenne. So you guys are continuing to dose optimize, find the right dose for the Duchenne population based on the LYNX study. So I guess, can you talk about maybe the decision to add an additional cohort, explore more doses? And then with the study now reading out year-end, I guess, what can we expect in terms of function, and, you know, maybe how many patients can the FOX trial add as well?
Yeah. So, big picture, we'll, by the end of this quarter, we'll have well over 90 patients treated with sevasemten. The decision to move with it to another cohort was—I mean, back in, back in, I think it was probably November, our, our commentary was that we were seeing changes in biomarker that were concentration-related and dose-related, but we needed to do more work. We've seen that increase in the biomarker response in the fourth cohort, and now the fifth cohort, I think I would, I would say that we're seeing a robust response. But we need to validate that response. We need to recognize how that concentration of the drug is related to the response, especially with a set of patients that are four to nine years of age.
So if you think about the weight of a four-year-old is about 15 kg, a weight of a nine-year-old could be as much as 30 kg. So you have a wide range of weights and drug exposures that we're trying to calculate. How would I get to the right dose? Perhaps the right dose is not a mg per kg or mg just a flat milligram dose, but actually a weight-based dosing. So we want to generate enough data to understand if that's the appropriate way to get to the right level of exposure for each individual patient. The second thing is, it's got to do with, I think, the competitive environment. We have, Sarepta is the label discussion's gonna occur in June.
The EMA is gonna have, you know, some discussion of whether or not it's approvable, the gene therapies in Europe. And we are running a study called FOX, which allows us to study patients who have been previously treated with gene therapy. So one of the prerequisites of running a phase III is to understand, would I include gene therapy pretreated patients into the phase III study? As well as what's the target population in which I would treat our drug just on a steroid background. My personal thoughts, and obviously the team has discussed this, is patients who are four to six years of age have a wide range of North Star results. Patients can be going down rapidly, they can actually be going up rapidly.
Choosing that subset in a clinical trial increases the variability of your being able to measure a delta from a placebo, even if you do stratify. What we want to be sure is, if we're gonna make the investment in Duchenne, we want to be confident of the functional inclusion exclusion criteria, the age or weight-based of the inclusion criteria. We want to be sure of the dose. Do we have a target concentration? Do we want to do that by a mg per kg basis, or we want to do it with a flat dose?
All those things have led us that we believe we need another cohort, which will be going somewhat higher, but we'll be validating the results we've seen so far to make sure that we're gonna select the right dose.
The other piece on function is kind of interesting as well, right? Because what's gonna happen by the end of the year is if you're... You know, the trial design, but just to kind of summarize is you dose escalate as soon as you do that for three months in a placebo-controlled way, and then everybody transitions to an open-label. So as you move by dose and you show that that dose is safe, everyone in the open-label jumps onto the kind of highest tolerable dose. So by the end of the year, we'll have at least six months of open-label functional data, both North Star and SV 95, on at least two doses that we think are within the efficacious range.
So combine that with everything that Kevin just kind of described around having the biomarker data as well as the FOX data, that and knowing where the competitive landscape is, it allows us to really think about what is the optimal phase III to run in order to drive for success.
Got it. We've got 2 minutes left, and I want to touch on 7500, which is another program that you guys have in cardiology. So I guess, you know, there's been fairly limited disclosures on what the mechanism is. So I guess, can you maybe touch on how 7500 differs from what's out there? And then, you know, maybe we can also get to what you'd like to see from the third quarter data in terms of both, ejection fraction-
Yeah, so we only have one minute 40.
It's gonna be tough, but we'll try.
Let's see. So let's start. The key aspect of this drug is, you may have seen previously the mechanism of action of the cardiac myosin inhibitors, meaning that there's the event of the contraction of the muscle is driven by what's called the lever arm and the ATPase interacting with the actin filament, and essentially walking along the actin filament and causing the contraction. Okay? Now, imagine that rate of that lever arm interacting with the actin filament, but now imagine a slower rate. So what we're adjusting is the rate in which we deliver the ATPase to the actin filament, as opposed to directly affecting the ATPase. So directly affecting the ATPase is kind of like an on/off switch.
What that leads you is that you have a direct relationship between the change of efficacy, like the gradient, and the change in ejection fraction, the contractility of the heart. What we're doing by changing the rate of that interaction of the ATPase with the actin filament, we actually slow down the contraction, and our largest effect is in the early part of the contraction, called isovolumic contraction. And it's theorized by Sherrid and others in a series of papers back 10 years ago, that the early part of the contractile element, the isovolumic contraction, part of the contraction, is what drives the gradient. So our drug can separate the gradient reduction from the ejection fraction reduction. That's how the drug works, because we have a novel mechanism still within the contractile sarcomeric element.
Okay, so what are we going to show in the coming months and actually probably in the third quarter? We're going to show the single ascending dose data in healthy volunteers, the multiple ascending dose data in healthy volunteers. And we're going to couple that with obstructive HCM data. So in a patient, we're going to dose them with a single dose. And the take home is mavacamten, what they showed with their single dose studies was about a 50%-60% decrease in gradient, but a greater than 20% decrease in ejection fraction. And what we showed preclinically is a 60% decrease in gradient, but virtually essentially a 2% change in ejection fraction.
We think that we can replicate that in humans, and we think, we're going to dose range with three different doses, with three patients per dose, and see the extent in which we see efficacy, coupled with the, whatever we see with ejection fraction. And that, that will allow us to make a decision about having a fixed dose regimen instead of having a titration with six or eight echoes. And if that comes to fruition, I believe that that will turn out to be a highly differentiated product that will have greater utilization and expand the market dramatically.
Great summary. Thank you for the time today. Unfortunately, we're out, but it's great to have you.
Thanks.
Thanks, Mitch.