Welcome to Berry's In the Interim podcast, where we explore the cutting edge of innovative clinical trial design for the pharmaceutical and medical industries, and so much more. Let's dive in.
All right. Welcome everybody to In the Interim, this is our podcast of clinical trial science, what's happening new in the world of clinical trials, and I have two wonderful guests today. We are gonna talk about the step platform and we'll talk about what that is. But my two guests today, Dr. Eva Misery, who is a, an associate professor in the Department of Neurology and Rehabilitation Medicine at the University of Cincinnati.
Welcome Eva. And we have Dr. Jordan Elm, who is a professor of biostatistics at the Medical University of South Carolina. And both of you are investigators in the step platform.
Thanks Scott.
So Eva, why don't you tell me what is the step platform? Maybe we'll talk a little bit about the platform, what it is, and then after that we can kind of go back and say, how did we get here? Uh, it's a, it's a, it's sort of interesting story. So what is the step platform?
Um, so step platform is an innovative trial. It's a platform trial. Um, the aim is to understand what are the best treatment strategies or combination of treatment strategies that are. Improve outcomes of acute stroke patients who have a visible occlusion in one of the vessels in their brain. Um, and that can include device-based therapies or medications, or just strategies, uh, of usual clinical care.
So all of those questions are fair point, um, uh, to study in the platform trial, the platform is embedded, uh, within an existing infrastructure of NIH stroke net. So just to tell you a little bit, NIH stroke net is an NIH funded infrastructure of a network of hospitals across the country, uh, that participate in, uh, phase two and phase three clinical trials. Um, again, those are NIH funded trials. Space of stroke.
Um, so this platform is embedded within that existing infrastructure, uh, but is, is is studying population of acute or sudden stroke patients who have this specific type of occlusion that's visible in their, uh, in their brain blood vessels.
Okay, so, so STEP is Stroke net Thrombectomy, endovascular platform. Uh, for, for the, the, the acronym of this. So Stroke net is a network of sites, uh, that's existed before the STEP trial. And then STEP is coming in and it's using those sites and it's a master protocol. It's a platform trial. Okay. Um, within that, we'll, we'll talk more about what that means, uh, uh, within it.
And this is NIH funded, but this is also public, private, um, uh, in the sense of the questions that get added within it, uh, in it. So what is the. The, the overriding goal of it clinically. So, so Eva, clinically, what are, what are we trying to do in step
Um, so just to kind of dive in a little bit of the history, because that is important to contextualize, um, what we're doing in the platform trial. So I wanna take you back to 2015. That was the year 20 15, 20 16, uh, when face of acute management of stroke patients really changed with this, um, therapy called Endovascular Clot Retrieval, which is a device-based therapy where a virus is inserted through an artery.
Um, to kind of suck out or, or engage and take out a large blood clot from the brain. And that really changed the face of acute stroke management. This was very, very, uh, efficacious therapy that improved lives of patients. Once these therapies were out and tested, uh, and approved, um, we then were grappling with lots of questions that surrounded this treatment. For example, how do you take care of several medical aspects surrounding this therapy?
For example, types of anesthesia given during the procedure. What is the blood pressure management? After the therapy is given, uh, we grappled with. Expanding the population that is eligible for this therapy because it was so effective, the field wanting to offer this therapy for more to more patients than were studied in the narrow, narrow clinical trials back in 2015 and 16.
Um, so from an NIH perspective, this really opened a floodgate of applications to NIH to to study various aspects surrounding. Uh, this therapy specifically in the population of stroke patients that have a vessel occlusion in their brain. Um, so that was an impetus for NIH to figure out novel and innovative ways to, uh, not just fund more questions, but also answer more questions with limited patient population that we have, uh, at our sites in the United States.
States to advance stroke care, um, um, along all of these facets, um, for stroke patients. So both time and economic efficiency was the impetus score, um, for conceptualizing, um, designing and then eventually funding the step platform. Um, it is funded through a novel mechanism at the NIH and INDS. Call other transactional authority, uh, which has been used to fund other platform trials, both at NIH as well as within the NI and DSB four.
Uh, and that allows the opportunity, what you were alluding to earlier, Scott, which is industry partnership. So, um, uh, some of our industry partners can come in and. Still go through the usual peer review process for the platform.
So this is not something kind of to just use the infrastructure is not just for somebody to come in and use, but uh, for them to apply in a similar manner as academic investigators would go through peer review process for their application and proposals for clinical clinical trial questions. It's still a single clinical trial, but, uh, but their own. Um, uh, you know, agents or assets, things like that. Um, and then once approved, uh, they can use the platform infrastructure to answer this.
So it is, it is quite novel in that sense.
So the old way of doing this might be, we have all these questions now in stroke about in whom do we use endovascular therapy? Do we use drugs? All of the, aspects around this we, the NIH might be. Stuck with funding. Four or five, completely separate questions. The patients are all different. The, databases are all different. The data coordinating center, and they can only run four.
So maybe integrating this all within a single platform, common patients, common infrastructure, maybe they can address. 8, 12, 16 questions, continual questions. So this is actually incredibly exciting and NIH feels like the right place for this kind of thing. So, Jordan, tell me a little bit about the master protocol, and as these questions come in, what does this look like?
Yes. So, uh, just to add on to what, what Eva was saying about, a little bit about the history. So back when, 2016 when, um, endovascular thrombectomy was shown to be very effective, it was shown only in some very discreet, um, populations. And so all of a sudden questions were coming to stroke net, which is stroke net is a, um.
It, it provides infrastructure, not just for the enrolling hospitals, but also for the clinical trial management, so the data management, statistical design, and the clinical coordination center. And so basically what was happening was the questions were coming in and saying, Hey, we want to look at it in this population, and, and somebody else would come in with a slightly different variation. The nice thing about the platform trial is that we're using a master protocol.
Um, and that allows everybody to come to the table and have a common framework of, of where we're starting from. Um, we can add on, uh, um, different aspects of the protocol if it, if it is important for that particular question, but it allows us to have this, um, basic kind of, um, set of. Schedule of activities, um, uh, activities that each participant would, uh, be a part of which, um, are common to many of the things that we would do in the past.
Um, we kind of try to enforce, you know, some uniformity, but it oftentimes goes out the window because you have different people. Um, running each trial and they make a strong argument for why it needs to be done this way versus that way. And so you see a lot of divergence in the way that a trial is rolled out. Um, and so the really nice thing about the master protocol in my mind is just having this uniformity, um, as a starting point.
So the I as we sit today, by the way, I, I should, I should let everybody know that I, I do work on this project. I'm part of the design team, so I've been involved in this. But, uh, and I, and I'll ask a little bit more about the structure of, of the various teams and how, how, how everybody gets along and how this works. But the first three questions, I think right now we have, sorry, we may have four questions. Uh, and a, a a within that, that we're currently working on.
Um, maybe Eva, can you give a brief description so our listeners sort of understand what these four questions and, and if I'm wrong on the four, correct me on that.
Um, I think I, it, I I think you're correct. It, it is four questions, so I'll just kinda walk you through how, how this platform can, you know. Happened over over time. Um, so we started with the design calls and Scott, you and the rest of the team at Berry were obviously very integral part of that design discussion to put together the master protocol that Jordan was referring to earlier.
And then we added the first layer, which is what we call the questions or assets to that master protocol from the get go to kinda realize this, as well. So that question was. basically if endovascular treatment, improves outcomes in two subsets of stroke patients that were not studied in the original 2015 and 2016 trials. So the first subset was those patients who have a large occlusion in their brain. But relatively milder stroke deficit.
So they have a milder stroke, but a large occlusion in their brain. And does retrieving that clot with device-based therapy improve outcomes? And the second subset of population was those patients that have clots a little bit further away. From the main branches of the vessels that were studied in the 2015 and 2016 trial, we call them distal or medium vessel occlusion. so the second subset of patients was those who have those distal and medium vessel occlusion.
So that is where we started with the first iteration from the get-go. So we. We came up with a master protocol and the first, what we call domain that included studying endovascular treatment versus medical management in a randomized fashion for these two distinct subset of patients. Um, NIH then opened, um, um, uh, publicly, um, uh, applications for further questions to be added on the platform trial we received several. In fact, we've received over.
15 to 20 applications at this point, I should say NIH, N-I-N-D-S has, um, and it's a two stage review process, um, uh, of allow or, or activating these questions on the platform, if you will. So in the first stage of review, we now have three additional questions, if you will, that are added to the platform or maybe added to the platform if they pass through the second stage of review. The first one is studying again, endovascular treatment versus medical management.
Uh, for another subset of patients, which is those who have cognitive impairment. Um, so that is one question. And then there are two other pharmaceutical partnerships, uh, of their, um, novel neuroprotective agents being studied in a phase two slash two three model for dose finding and then efficacy trials. So really exciting times. We're excited to put these forward for a second stage of review and um, hopefully we can, we can add them onto the platform.
Um, okay. so there are currently these four questions going on. So a patient. Could come in and the, EVT aspect of it is you're trying to figure out who should and should not get endovascular therapy. You've identified groups where it's incredibly effective, there's an expectation in others it might not be effective, and this is really trying to figure out who should and should not get it while simultaneously there's a medical domain.
And patients that come in who get endovascular therapy, the question is, would a neuroprotectant improve their outcomes? And so that sits there. so Jordan, I, love the statistical or the scientific aspect of this EVT expansion because it's very different than almost every trial. We do many trials. You walk in and you say, does is a better than B? And we power it to show A is better than b. But here we expect that there's it's differential in the patients.
We expect that for some that EVT might not be better and some EVT may be better within this. So what we're really trying to do is almost find the cut point or find who does and doesn't benefit. So statistically, this is a very different trial.
Yeah, I, it's been a lot of fun working on this with you guys. I have to admit, just, conceptually. This has very, been very new for me too. In terms of what is the, what baseline characteristics define, who may or may not benefit. we don't usually, design studies like this, we usually, focus in on what is the population that's most likely to benefit. We only enroll them maybe something slightly outside that range, and then we test does it work, yes or no?
And then this is just very asking a much. Different question. And it's really getting at the science because we really wanna know, we think it's gonna work for a very large population. And instead of testing these small, discrete populations one by one, over time, we're starting broad. and then we're asking the question, at what point is it no longer beneficial?
And so we have this, lovely statistical change point model that, that, Scott, your team developed, which has really been cool to be a part of, which helps to answer this question along the spectrum of the baseline covariate, which is continuous. we can find two cut points. One in which the, treatment endovascular thrombectomy is better than medical management, and then going up and then a period in the middle where maybe they're both the same and then.
We can also identify on the lower end of that continuous covariate, the point at which the medical management is, potentially better. So a very different design, somewhat of a enrichment design, but not in the way that, that reen enrichment trials are, often done.
So the adaptations in this domain, you are enrolling, I'll, call it a wide group of patients that we don't know the answer to, whether EVT is better. You're randomizing 50 50 endovascular therapy or best supportive care medical management. And as the trial goes, the adaptations could be, we've figured out it does or doesn't work in groups and we stop enrolling them. Announcements may be made. Papers may be published where we still enroll those where we don't know the answer.
So it's, been fascinating where we're simulating not the power to show EVT is better, but the power to identify who should and shouldn't, it's a whole new sort of way of the trial. So then the medical domain, Eva is, um, there are two different. Uh, uh, neuro potential neuroprotectants within this. So what does that, the domain is the medical domain. What does that trial or, uh, a sub trial look like?
Um, so since the, the endovascular treatment advent in past few years, the field of neuroprotectant, or in other words, and it's a pretty umbrella term, frankly, so I, without going into the. Neuroscience is a what, what, uh, neuroprotection means. There has been renewed interest because of the, um, the surety in the drug delivery, uh, to the target area, if you will.
If you take out the blood clot, you can be somewhat sure that the agent is going to reach the stroke area that was initially kind of blocked because these are, these drugs are usually given. Via intravenous, you know, routes. Um, so that is a renewed interest in the field to find if, if, if we can find drugs that can help with the recovery or slow down the death of brain tissue that is associated with stroke. Um, so then this iteration we have. Two pharmaceutical partners.
Each of them have their neuroprotective agent. They're both very different in terms of the mechanism and what they do. Um, both of them are supported by preclinical data, of course, in fact, one of them is supported by preclinical randomized clinical trial. Through the SPAN network, which is another NIH funded network of preclinical, uh, clinical trials for stroke models. So we're very excited to translate that directly into humans. So it's a nice pipeline, if you will.
And then another one has come up through regular, you know, industry chains. Uh, again, both are very different trials. Um, the first and foremost, they're trying to understand, uh, finding the best dose of both of these agents. Um, in the ideal world, in the pivotal stage, we would want some sort of either co-enrollment or a head to head comparison to find out the best intervention or the strategy as it comes to neuroprotective agents.
But since both of these are in kind of more phase two, uh, dose finding stage, they're not going to co-enroll or compete with each other and. Of course berries have worked with us closely to find an ideal model to be able to do that. So right now the aim is to find the best dose based on, um, either, um, you know, long-term functional outcomes or surrogate outcomes that are earlier than that.
Both trials are a little bit different, uh, but once we have found the best dose with a pretty pre-specified and robust go, no go criteria. Uh, from a dose finding or dose selection to a pivotal testing phase, um, uh, that is, that is an exciting aspect. Frankly, for me. I would have to say that, um, the number of patients available to test something like this in the United States and the number of sites that can participate.
Can sometimes limit us as clinicians in the field where then we are just competing with each other, uh, uh, to, to kind of enroll these participants in many, many trials that are going on. But the number of participants available are small, so this kind of helps with some of that. Uh, we have a lot of committed sites, um, that are, that are committed to seeing through these, uh, these trials, including phase two development.
Uh, nice. So both of these neuroprotectants, so these are not a, a, as opposed to thrombolytic agents or, or this, that, that they're. The, the potential to improve clinical outcomes, they're, that that's the goal of both. They're both doing dose ranging. Uh, and they could both stop for futility. They could both continue on to a point where they try to demonstrate clinical improvement on the, not the 90 day modified Rankin score of the, the, the, the clinical outcome.
Jordan, what does this look like for a patient that comes in to the medical domain in terms of their randomization, in terms of even having potentially shared controls? When this, what does this look like in the medical domain?
So we spend a lot of time talking about that. Um, ideally we would like a patient to be, participate in as many domains as they are eligible for.
there may be reasons scientifically, however, not to allow, patients to co-enroll in different, Different aspects of the platform, but within the medical domain, there are, some differences in the two designs in terms of the eligibility population and so in which the, space in which the patients are eligible for, both those patients will essentially, if they're randomized to the control group, they will serve as a shared control group.
if they're only eligible for one or the other, they will not, participate in that pooled, control group. So it gives us a little more, flexibility, in terms of patients essentially coming in and being eligible for more treatment groups. and so they're getting, we're having shared control, so there's not, there's a lower likelihood of them getting a control. And that's a little bit of a pro, I think as you're, thinking about enrolling in a clinical trial.
And then, we also can pull those controls. So there's the efficiency that we get from that.
Yeah, so it is in another model if each of these sponsors were running trials separately. Somebody randomized to placebo informs that trial, that one question. Now that patient randomized to placebo might be used by both pharmaceutical companies. We can enroll less placebos globally across all of our trials, which is a stunningly. Nice aspect of this, platform trial, you said randomized to other domains.
So it could eventually be that, that where here there's the medical domain does being randomized, uh, to a neuroprotectant help and they're asking that. But they could be randomized to endovascular therapy initially and asking the question, was endovascular therapy good? And then that patient's also contributing to whether the medical thing given was good. Eventually, this could be, you know, blood pressure control, rehab, uh, multiple aspects of their care as evil laid out.
The whole goal of this is to improve the, the, the whole. Aspect of the medical care this single patient contributes to multiple domains is is just incredible.
And, and I will say that's a little bit of a different idea than. Um, uh, you know, historically we think of each clinical trial. Let's control everything. And we are not gonna allow any participation in external clinical trials while we're doing this clinical trial. And this, uh, framework kind of throws that upside down and puts it on its head. And the idea being is that it would be better to randomize to something that they would have as background care. Um, anyways.
Um, than just allowing the background care. So I, and then we can control for that in the model. We can put interaction effects to kind of look at that specifically. So I think it does give us a lot more flexibility than what we would maybe traditionally do. Um, I, I.
Yeah. Yeah. Very exciting. So this is, right now, there's the four questions that they're still, this is a continual process of people applying questions to this. What does that look like? Uh, what, what, uh, Eva, what's the overall structure? Or Jordan, what's the structure of this and how does that work?
so there is a, um, a. Uh, a funding opportunity announcement, which is public. Anyone can apply to it if they have an idea for the platform. Um, the first, um, application is very simple. It's just essentially the science, um, the science justifying why it, uh, is important to be studied. They don't have to come with a design.
Um. Once the science is peer reviewed and, and essentially vetted to be appropriate for the platform, um, it comes in and, and they begin to work with the step team to develop a full design, um, to get integrated in with the master platform, um, to develop their pla uh, their protocol, um, sorry, with the master protocol, um, to get, um, their protocol appendix.
Uh, to the master drafted and, um, put together a, a full, uh, application, which then goes back to peer review, um, to approve it for, um, uh, for, to be part of this, uh, this platform. So that's, that's the general process.
I had a couple of things, which is, you know, it's good to clarify some efficiencies that we frankly, kind of think are NIDS colleagues. Um, in thinking about this, given that this is the other transactional authority mechanism. Uh, there isn't really a a, a binding timeline for review. It doesn't happen three times a year. The review can happen once there is a pile of applications.
So it's kind of an iterative process and, and potentially faster than, than a typical NIH review process that's bound to three times a year cycle. Um, even though there's two stages. Theoretically it's a, it's a faster kind of review and approval process, and again, it can be a bit iterative where reviewers raise certain concerns and you can kind of go back with, with changes and comments and, and get that reviewed pretty fast. Um. Which is exciting.
And then, um, in the same manner, the industry partnership is really interesting as well, where the ROA that Jordan was referring to earlier allows for industry partners to apply themselves. So they now don't need an attachment with, say, a university or a academic PI or anything like that. The industry partner themselves can be the leader of their question and work in partnership with.
Step, um, especially if they're bringing on in some of their own support, um, in terms of finances and things like that. There can be a joint funding model also. So there's a lot of efficiencies and, and innovative, um, things in, in terms of, uh, funding models.
Yeah, it's, it's, it's fascinating. As somebody that's sort of on the design side, we, we, I, I know this process is going on, and at some point it moves into this. Interaction with the design team about how would this fit in with everything? Can we design this section of it? And we've had four so far, and now there's word of maybe two new questions, two or three new questions coming in.
Yes. Two more questions coming in. Um, and it's just gonna be an iterative process. Hopefully we'll continue to get people that apply and get added into the platform.
So where, so the listeners may be interested in where we are on this. Have we enrolled a patient in Step?
Yes. In fact, we've enrolled 17, 18 patients in step, in that first domain that we were talking about in avascular treatment versus medical management. I'll maybe highlight one other great adaptive aspect of the platform, which is that we started with this two distinct populations. That I was talking about earlier, the low N ni h stroke, milder deficits with a large clot, and then more kind of distal and medium clots.
in after we, we released sites in both of these patient populations, if you will. We found out that there were some clinical trials that were presented and published that showed that we might have to pivot that latter patient population a little bit because the question may be answered in a subset of that population as to EVT not being better or the device-based treatment not being better.
So we paused that population, went back to the drawing board a little bit, collaborated with the trial PIs of the published trials, and then, came up with a redesign and it's Now back with the IRB for approval, to see if we can reopen a slightly modified, version of the protocol for that population. So that is a great adaptive aspect where if we have external data, we can look at it and make sure that the platform adapts to the, existing science that comes out in parallel.
So it, the, trial was designed to identify groups where we know the answer. Yes, you should. No, you should not do endovascular therapy. You're learning from other trials. Done externally answers to those questions, which then modify our trial. And, it's so critical that we, Are able to adapt to that and continue to evolve the questions based on what's known and not known within this. so it's, a huge feature of this that, that we're able to do this in another setting.
We might have to stop, shut down the trial, get new funding and all of this so that that's an incredible feature of it.
And that aspect is critical, right? When you, in the typical, typical setting, you would have to the contractual, you know, binds won't allow modifications and you might have to go through another review process and kind of, you know, reinvent the wheel and that might put back the field by years, like you said, Scott, in this setting, it's, it's, it's much more nimble.
So how does this work also, sort of academically, we have this NIH trial in it. Um, is, is Eva Mystery the first author on every result that comes out of step? How does this, how, how will publications work in the academic setting tied to all of this?
Yeah. And that's one thing I think it, it, it's a little harder, uh, with the platform because you don't have, um, uh, you know, the typical structure of having. The person who brings forth the idea kind of being the trial lead. There's a lot of leaders in this platform, but we wanna make sure that the people who come forth with the ideas are the leads for their asset papers, um, for, for the, the components of the science that they've, they're leading.
Um,
So there's a lot of us working in the background. I would say just kind of facilitating the process, um, but. The, the leadership of the papers, the, the trial author, um, the, the paper manuscript primary papers should be, um, the people who brought forth those, those questions.
Yeah, the, so it, it may be that papers just come out when results are known. And it may be that one patient that's contributing to multiple question there, they contribute and the papers published. And meanwhile, this is just a, a, a continual process to this. I, I've been struck by, um. How innovative the NIH has been on this, how forward thinking they've been on this. You, you mentioned the OTA funding of this.
I think this is an incredibly, uh, uh, you know, forward thinking way for the NIH to do this. Uh, Eva, I assume that's been your experience in the whole process of, of the creation of this, the, the, the, the working of all of this.
I think they have been incredibly creative and innovative. In fact, to tell you a little bit of their history, we started working on the design of the platform. I believe, Jordan, you can correct me, 2018 public, 2019, uh, something like that. And, uh. We did try the usual grant submission pathway first, and as you can imagine, there are so many components of the platform that don't kind of fit in the, it's like a square peg through a round hole if you try to fit it in.
So it was in fact an IND S'S idea to. Uh, put out a notice of special interest for an other transactional authority mechanism, um, to submit this first master protocol, plus a first domain concept to, to make this platform into a reality at which. State, we worked closely with you, Scott, and, and your team, um, to, to come up with a protocol and the, the entire design.
And, uh, so I would say they've been incredibly kind of innovative, forward thinking, um, including, I should say, this industry partnership and the avenues to, to, to move the science forward as fast and as cost efficiently as we can. And most ethically from a clinical standpoint, frankly, um, as a clinician, myself.
Yeah, I, I wonder if you could touch on that part. So, as, as a statistician, I always sit on the side of the design and I, I find these can be incredibly. Uh, efficient in patients contributing to multiple questions. There, there, there're a placebo for multiple arms and it just seems like this is so, uh, uh, uh, great. From that perspective, running a trial like this at a site, is it, I, I, are there benefits on that side?
Do you think that from a clinical site, from your perspective in, in this platform.
Um, I think there are multiple benefits, um, to being a sign and step platform trial. Um. Being a step site comes with, um, infrastructure support from the N-I-N-D-S, um, to we, NIDS recognizes that running something like this now add the complexity of enrolling in a hyperacute setting. Uh, a patient who has. This first medical contact with the system, actually their lives has been turned upside down. Oftentimes, they can't consent for themselves. We have to consent.
Legally authorized representatives, they're coming as transport from little hospitals two hours away, and you're trying to talk to them while their family members in the transport to talk about this, this trial that you have. So it's operationally extremely challenging to do so. When IMDS. Recognize that and, and is providing infrastructure support to the all 38 sites, uh, that are participating in the, in the platform trial. Uh, we have great support in other ways. We have robust training.
Uh, we have several PIs at least of the overall step platform trial, uh, that train sites on various aspects of operationalizing. We have something called the study hotline, which is a 24 7 hotline that is staffed by study site. Study, um, uh, multiple PIs, uh, to answer urgent enrollment, clinical questions and kind of support the sites in that process. So, so there's a lot of work, there's a lot of teamwork, I should say, uh, that goes on in, in, in, in doing a trial like this.
But there are definitely benefits. And then, like you said, these questions kind of hopefully keep coming in perpetually providing the population that the site sees. Continuous opportunity to participate in cutting edge research. And I'll say for our site, you know, participation in research is part of our clinical care. We want every patient to be considered for, for opportunities for research unless, and if we, we don't see ourselves doing appropriate clinical care.
If we don't at least think about that.
Yeah, and, and I know Jordan, we're at the early stages of. Interim analysis, uh, data management results, publications. But from your perspective, you know, the complexity of four questions simultaneously, adding new ones in, how has the, the operational aspects of all of this.
Uh, I would say initially it felt daunting, but it has become now, I think, easier than what we
Okay. Yeah.
which is, it's always good. I think, um, you know, anytime you're, you're doing something new for the first time and it's a little bit of a learning curve, but I, I think having the framework here. Of, uh, the consistency across the whole platform, uh, more uniformity with processes, um, is only gonna make things easier moving forward. So.
Yeah. Yeah. Uh, and, and we, we need to mention that there's, there's a whole sets of teams working on this, uh, from the NIH to the pharma companies, the statisticians, MUSC. Uh, tremendous work from everybody on this is, is, has been really amazing to see. Largely, uh, you know, raising everybody, working together, raises everybody, uh, within this setting has been amazing.
And this is a, this is a sentinel project, I think for the NIH and setting a, a, a really cool standard I think in, in other disease areas.
Agree. Completely agree. Yeah.
All right. So we are, we are as we as, as Eva said, we are 17 or 18 patients into this, this Odyssey, so we're not quite in the interim. But thank you for joining. In the interim,
Thank you.