WEBVTT NOTE This file was generated by Descript 00:00:00.000 --> 00:00:03.490 Judith: Welcome to Berry's In the Interim podcast, where we explore the 00:00:03.490 --> 00:00:07.650 cutting edge of innovative clinical trial design for the pharmaceutical and 00:00:07.650 --> 00:00:10.079 medical industries, and so much more. 00:00:10.380 --> 00:00:11.029 Let's dive in. 00:00:12.703 --> 00:00:13.273 Scott Berry: All right. 00:00:13.273 --> 00:00:14.413 Welcome everybody. 00:00:14.413 --> 00:00:20.443 Back to, in the interim, I'm your host, Scott Berry, and today I have 00:00:20.473 --> 00:00:24.343 three guests and we're gonna talk about a new adaptive platform trial. 00:00:24.793 --> 00:00:29.353 And the, the trial name is Panther and we'll get to what, what Panther is. 00:00:29.893 --> 00:00:32.143 But, uh, let me introduce you to our guest today. 00:00:32.503 --> 00:00:35.473 First, I have Professor Victoria Cornelius. 00:00:35.933 --> 00:00:40.523 She's a professor of medical statistics and trial methodology, and the director 00:00:40.523 --> 00:00:47.063 of the Imperial Imperial Clinical Unit and co-director of the NIHR Research 00:00:47.063 --> 00:00:50.183 Support Services, Imperial College London. 00:00:50.693 --> 00:00:55.013 And she has extensive experience in designing and analyzing trials to 00:00:55.013 --> 00:00:57.563 evaluate drug and complex interventions. 00:00:57.933 --> 00:01:03.303 And uses, uh, both Bayesian and Frequentist adaptive designs using 00:01:03.303 --> 00:01:05.913 innovative statistical, uh, approaches. 00:01:05.913 --> 00:01:07.743 And we will talk about those today. 00:01:08.253 --> 00:01:11.103 Uh, we also have Dr. 00:01:11.103 --> 00:01:15.453 Danny McCauley, who is a consultant and professor in intensive care 00:01:15.453 --> 00:01:21.153 medicine at the regional intensive care unit at the Royal Victoria Hospital 00:01:21.153 --> 00:01:22.923 in Queens University in Belfast. 00:01:23.833 --> 00:01:28.513 He is the NIHR Scientific Director for research programs. 00:01:28.813 --> 00:01:33.103 He has several research interests, including acute respiratory distress 00:01:33.103 --> 00:01:38.083 syndrome, which will be a topic for today, uh, as well as recovery following 00:01:38.083 --> 00:01:40.903 critical illness, uh, in clinical trials. 00:01:41.353 --> 00:01:45.103 Danny and I have worked together, by the way, extensively on the REMAP CAP 00:01:45.103 --> 00:01:49.903 trial, a different trial that, uh, uh, isn't the main topic, uh, of today. 00:01:50.713 --> 00:01:52.993 And we have Professor Anthony Gordon. 00:01:53.413 --> 00:01:58.723 Uh, uh, professor Gordon is the head and of the division of Anesthetics 00:01:58.723 --> 00:02:02.473 Pain Medicine and Intensive Care at Imperial College London. 00:02:02.953 --> 00:02:07.333 He is a consultant, uh, on the adult intensive care unit at St. 00:02:07.333 --> 00:02:11.983 Mary's Hospital and is an NIHR Senior investigator. 00:02:12.318 --> 00:02:16.723 His research focuses on developing precision medicine and sepsis. 00:02:17.098 --> 00:02:21.748 And he's been the chief investigator for multiple clinical trials in critical care 00:02:22.168 --> 00:02:28.288 and he's now the director of the UK's NIHR Health Tech Technology Assessment 00:02:28.288 --> 00:02:33.688 Program where he's keen to encourage innovative and novel trial designs. 00:02:33.688 --> 00:02:36.538 And I think we have a pretty innovative and novel one today. 00:02:37.078 --> 00:02:42.838 Uh, and Tony is also a member of the most excellent order of the British Empire. 00:02:44.128 --> 00:02:47.818 Uh, and I've also worked quite a bit, uh, uh, for a number of 00:02:47.818 --> 00:02:49.558 years with Tony on remap Cap. 00:02:49.588 --> 00:02:52.798 We've all worked together, so welcome everybody to in the interim. 00:02:54.353 --> 00:02:54.893 Anthony Gordon: Thanks Scott. 00:02:56.068 --> 00:02:56.423 Danny McAuley: Thanks Scott. 00:02:57.478 --> 00:02:59.308 Scott Berry: all right, so Panther. 00:02:59.968 --> 00:03:06.778 Uh, Panther is a new platform trial, and I, uh, I should say that I am a member of 00:03:06.778 --> 00:03:12.118 the DSMB and I'm honored to be a member of the DSMB, but we have seen no data yet. 00:03:12.148 --> 00:03:15.688 So I'm not unblinded, there's no risk that I'm going to give 00:03:15.688 --> 00:03:17.338 away results in the trial. 00:03:17.608 --> 00:03:21.388 Uh, somewhat familiar with the trial, but, uh, uh, so this, 00:03:21.448 --> 00:03:23.398 that'll be a, a fun part of this. 00:03:24.448 --> 00:03:30.898 So the, the Panther platform trial, uh, and it, it labels the objective of 00:03:30.898 --> 00:03:36.058 this is to accelerate the development of pharmacological therapies for 00:03:36.058 --> 00:03:40.528 critical illness by establishing an international phase two precision 00:03:40.528 --> 00:03:46.533 medicine adaptive platform trial, uh, to test for efficacy, uh, in. 00:03:46.933 --> 00:03:52.273 Uh, pharmacological intervention in critically ill patients for acute 00:03:52.273 --> 00:03:59.533 respiratory distress syndrome and pandemic infection and different sub phenotypes. 00:04:00.103 --> 00:04:03.313 So tell me about the Panther trial. 00:04:03.313 --> 00:04:07.453 First of all, why, why do we need the Panther trial? 00:04:07.453 --> 00:04:11.293 What is the Panther trial trying to address and solve? 00:04:14.283 --> 00:04:15.163 Danny McAuley: Thanks, Scott. 00:04:15.163 --> 00:04:19.363 I'm happy to kick off and we'll see where, uh, we, we land with Tony and Victoria. 00:04:20.023 --> 00:04:25.243 So I, I guess in terms of what we're trying to do, uh, there are several 00:04:25.423 --> 00:04:29.173 challenges, um, in treating, uh, a RDS. 00:04:29.743 --> 00:04:36.103 Um, there's a huge amount of heterogeneity within the, uh, overall population. 00:04:37.573 --> 00:04:38.803 Um, and I think. 00:04:39.553 --> 00:04:43.063 More recently, over the last sort of five to 10 years, we've recognized 00:04:43.063 --> 00:04:46.783 that there are phenotypes that exist within these, uh, syndromic 00:04:46.993 --> 00:04:49.933 definitions of, of conditions that we deal with in intensive care. 00:04:49.933 --> 00:04:54.883 Like IRDS the most consistently reported, and there are others Tony may wanna 00:04:54.943 --> 00:05:00.073 pick up on, um, are the inflammatory phenotypes that are, uh, described 00:05:00.073 --> 00:05:02.953 originally by, uh, Carlin Calie. 00:05:03.463 --> 00:05:05.203 Over now, 10 years ago. 00:05:05.773 --> 00:05:08.563 Essentially, these now have been replicated in multiple, 00:05:08.593 --> 00:05:13.033 uh, secondary analysis of RCTs, observational cohorts, adult kids. 00:05:13.543 --> 00:05:17.503 So we're trying to get at that heterogeneity by focusing on, on 00:05:17.503 --> 00:05:21.433 those phenotypes, and we've only recently been able to identify. 00:05:21.868 --> 00:05:25.408 Those at the, the bedside, which we can come back to. 00:05:25.408 --> 00:05:28.498 So that's one big, um, thing that we're trying to deal with. 00:05:29.278 --> 00:05:33.508 The second, uh, big issue is that I think traditionally in, uh, 00:05:33.568 --> 00:05:37.738 critical care, and particularly ARDS we've jumped from relatively 00:05:37.888 --> 00:05:41.308 small promising phase 2 studies. 00:05:41.338 --> 00:05:46.698 into Big phase 3 Um, what we're really trying to do with, uh, Panther 00:05:46.698 --> 00:05:52.518 is give confidence in the therapies that we think might work, uh, with a 00:05:52.518 --> 00:05:54.768 much greater amount of, of certainty. 00:05:54.768 --> 00:06:00.378 So move from small phase 2 to big phase 2 within, uh, Panther. 00:06:01.848 --> 00:06:04.638 And then I think that the other issue is that, um. 00:06:05.203 --> 00:06:09.643 We've really struggled to get, uh, uh, commercial partners engaged 00:06:09.643 --> 00:06:13.793 within, uh, the critical care space, particularly within ARDS 00:06:13.813 --> 00:06:15.758 and sepsis, largely because of a. 00:06:16.798 --> 00:06:21.268 Con misconception, I think that, um, uh, ARDS and critical 00:06:21.268 --> 00:06:23.548 illness are are a, a graveyard. 00:06:23.788 --> 00:06:28.468 And I think what we want to try and do is de-risk the involvement with 00:06:28.468 --> 00:06:32.758 commercial partners because we have an established ongoing platform that we can 00:06:32.758 --> 00:06:35.608 hopefully answer questions that, uh, help. 00:06:36.598 --> 00:06:41.068 Commercial companies, uh, at a sort of, uh, lower risk, but uh, 00:06:41.098 --> 00:06:43.978 also more importantly and perhaps most importantly, help patients. 00:06:44.218 --> 00:06:46.523 So I'll, uh, stop there and see what others have to say. 00:06:49.468 --> 00:06:51.628 Anthony Gordon: Yeah, Scott, I think obviously. 00:06:52.768 --> 00:06:53.818 Align with Danny's thinking. 00:06:53.818 --> 00:06:56.488 I think it's, we've got critically ill patients. 00:06:56.548 --> 00:06:59.668 There's this unmet need to improve their outcomes. 00:06:59.668 --> 00:07:02.278 So these are patients at high risk of dying. 00:07:04.048 --> 00:07:08.308 provide them generally with supportive care, but when it's come to trials 00:07:08.308 --> 00:07:12.538 of specific drugs that might, uh, modulate, for instance their immune 00:07:12.538 --> 00:07:17.908 response to that critical illness, promising drugs from preclinical studies 00:07:18.448 --> 00:07:20.368 haven't translated into that benefit. 00:07:20.368 --> 00:07:21.473 And I think it is because we've. 00:07:22.393 --> 00:07:28.483 As clinicians, we group patients with similar signs, symptoms, 00:07:28.933 --> 00:07:30.103 organs that aren't working. 00:07:30.103 --> 00:07:31.813 So in this case, lung injury, 00:07:33.853 --> 00:07:35.023 given them the treatment. 00:07:35.113 --> 00:07:40.393 And probably some of those treatments have had potential for benefit. 00:07:40.513 --> 00:07:44.203 But in the trials we've just not seen it because there are others who don't benefit 00:07:44.593 --> 00:07:46.903 and probably some, uh, that are harmed. 00:07:46.903 --> 00:07:49.318 And as Danny said, there's been a big emphasis in actually. 00:07:49.963 --> 00:07:55.273 Breaking down these clinical syndromes into more biological sub phenotypes. 00:07:55.273 --> 00:07:59.173 And then it would seem that the drugs, if you could target the biology, 00:07:59.233 --> 00:08:01.183 are more likely to be beneficial. 00:08:01.273 --> 00:08:05.923 And so with this, um, if we do that though, it needs to 00:08:05.923 --> 00:08:08.173 be, uh, a joined up effort. 00:08:08.233 --> 00:08:10.213 International is the other aspect of this. 00:08:10.213 --> 00:08:13.118 If we try and do this on our own, because we're. 00:08:13.738 --> 00:08:16.108 Breaking down the populations into smaller groups. 00:08:16.198 --> 00:08:19.648 Um, we think the important thing is to come together so that we can work 00:08:19.648 --> 00:08:21.418 internationally, get answers more quickly. 00:08:21.778 --> 00:08:26.008 Um, so that is the other key part of this being an international, 00:08:26.458 --> 00:08:29.248 uh, platform, getting the key investigators to work together. 00:08:31.138 --> 00:08:31.528 Scott Berry: Oh, okay. 00:08:31.528 --> 00:08:37.438 So it, it, it's an area, A RDS is an area that not much has worked in, and 00:08:37.438 --> 00:08:39.658 yet it's still a clinical problem. 00:08:39.658 --> 00:08:41.968 It's, it's, I don't wanna call it a, a graveyard, but 00:08:41.968 --> 00:08:43.318 it's been a challenging area. 00:08:43.318 --> 00:08:49.798 And you think to some extent, part of the challenge is ID not all a RDS is the same. 00:08:49.798 --> 00:08:55.138 And so it may be some treatments, precision medicine, treat some 00:08:55.138 --> 00:08:57.593 of them well, but others that may be negative and the net. 00:08:58.483 --> 00:09:01.993 You run a trial, it looks like nothing but so this trial can try to 00:09:01.993 --> 00:09:08.203 address heterogeneity of effect, uh, within this, do it in a larger scale. 00:09:08.803 --> 00:09:13.783 An aspect of the platform, I imagine is easier shots on goal. 00:09:14.458 --> 00:09:19.378 So if you've got this up and running and you want to bring in a treatment from a 00:09:19.378 --> 00:09:24.598 pharmaceutical company or anything to, to take that shot on goal, to give it 00:09:24.598 --> 00:09:29.458 a shot to investigate it, much cheaper, much smaller than going out and building 00:09:29.458 --> 00:09:31.978 a whole new stadium to test that one. 00:09:32.158 --> 00:09:36.203 I imagine that's why the platform part of this is, is interesting. 00:09:38.873 --> 00:09:40.403 Anthony Gordon: Yeah, I think that's right. 00:09:40.403 --> 00:09:45.533 And when you put it like that, there's maybe COVID-19 gave 00:09:45.533 --> 00:09:47.543 us some of that learning and has helped to accelerate that. 00:09:47.543 --> 00:09:48.648 This work was going on already. 00:09:49.633 --> 00:09:53.503 But we saw the benefit of platforms of bringing in drugs 00:09:53.503 --> 00:09:55.483 rapidly and getting answers. 00:09:56.083 --> 00:10:00.853 But I think also just underpins the biological rationale behind this. 00:10:00.943 --> 00:10:07.183 Uh, with COVID, a new infection, um, was essentially a RDS, um, 00:10:07.543 --> 00:10:12.523 but very homogeneous, particularly at the beginning of the pandemic. 00:10:13.093 --> 00:10:15.313 And that homogeneity, I think, was. 00:10:16.378 --> 00:10:21.478 What enabled us, um, you know, multiple groups of trials to show, uh, the 00:10:21.478 --> 00:10:25.258 drugs that were successful in immune modulation, uh, drugs, particularly 00:10:25.258 --> 00:10:27.538 in the critically ill, uh, population. 00:10:27.538 --> 00:10:33.178 So that sort, I think, reassures us that, that the biological rational is 00:10:33.178 --> 00:10:40.228 solid, that we can improve outcomes if we identify the right patients with the, 00:10:40.708 --> 00:10:45.418 uh, right underlying biology, uh, with these therapies. 00:10:45.838 --> 00:10:46.078 Scott Berry: Yep. 00:10:47.173 --> 00:10:53.383 Alright, so before before we move forward, a RDS, um, we've heard the term, you 00:10:53.383 --> 00:10:58.153 know, what, what is a RDS and I know you talked about the heterogeneity. 00:10:58.153 --> 00:10:59.773 So I mean, what is, what is a RDS. 00:11:02.233 --> 00:11:09.193 Danny McAuley: So, uh, essentially, um, a RDS is severe, uh, respiratory 00:11:09.253 --> 00:11:13.003 failure that is, uh, not due to. 00:11:13.813 --> 00:11:19.303 Other recognized conditions like heart failure or, uh, fluid overload. 00:11:19.783 --> 00:11:25.273 Um, and it's characterized by, you know, x-ray changes that are sort of bilateral 00:11:25.333 --> 00:11:32.413 patchiness and severely impaired, um, lung function that we, um, uh, sort of 00:11:32.473 --> 00:11:38.723 measured using measures of oxygenation typically, um, tho those people are on a. 00:11:38.943 --> 00:11:43.623 Mechanical ventilator, although, uh, more recently the, the sort of syndromic 00:11:43.713 --> 00:11:49.653 definition has been updated to include, um, people who are receiving high flow 00:11:49.713 --> 00:11:53.523 nasal oxygen due to the increasing and, and widespread use of that. 00:11:53.523 --> 00:11:55.923 So, so that's the syndromic definition. 00:11:55.923 --> 00:12:00.813 But I guess, you know, as you might imagine, that sort of is 00:12:00.813 --> 00:12:05.283 underpinned by a whole raft of different biological processes that 00:12:05.283 --> 00:12:06.693 we're really only now starting to. 00:12:07.093 --> 00:12:09.463 Get at, which is the sort of move to precision. 00:12:10.063 --> 00:12:10.283 Scott Berry: Hmm. 00:12:11.323 --> 00:12:11.593 Hmm. 00:12:11.923 --> 00:12:12.373 Okay. 00:12:12.433 --> 00:12:16.963 And, and you could this acute failure, so this is, uh, as opposed to as 00:12:17.083 --> 00:12:19.513 chronic, uh, uh, in a particular way. 00:12:19.513 --> 00:12:24.733 So some, some particular event has caused this respiratory distress, 00:12:24.973 --> 00:12:29.923 and that could be sepsis cap and a whole wealth of other things that 00:12:29.923 --> 00:12:32.203 get somebody into this acute status. 00:12:33.478 --> 00:12:34.318 Danny McAuley: Yeah, that's right. 00:12:34.378 --> 00:12:36.988 So I mean, if you get knocked over by a bus, you break your 00:12:36.988 --> 00:12:42.238 leg, you have near drowning sepsis, you have bad pancreatitis. 00:12:42.238 --> 00:12:45.718 So, and again, if you imagine the heterogeneity. 00:12:46.433 --> 00:12:48.983 That as well, adding into the mix. 00:12:48.983 --> 00:12:53.363 So it, it's not at all surprising that we, if we've treated all these patients 00:12:53.363 --> 00:12:58.793 the same way that we've struggled to find a, a specific, um, therapy. 00:12:58.793 --> 00:13:02.723 So I, I think again, that just emphasizes the need to, to follow the 00:13:02.813 --> 00:13:04.823 biology and the then the phenotypes. 00:13:05.188 --> 00:13:05.458 Scott Berry: Yeah. 00:13:06.298 --> 00:13:06.778 Okay. 00:13:06.808 --> 00:13:10.048 So there's this larger goal we, we, we should say, by the way, 00:13:10.048 --> 00:13:10.973 so you're interested in this. 00:13:11.253 --> 00:13:13.113 Panther platform trial. 00:13:13.443 --> 00:13:17.643 And you've, you've presented this solution to a problem and 00:13:17.643 --> 00:13:19.053 you have gotten this funded. 00:13:19.323 --> 00:13:22.233 Uh, so who is the major funder of this? 00:13:24.148 --> 00:13:28.438 Danny McAuley: So, um, the, the sort of first funder was the, uh, 00:13:28.528 --> 00:13:34.438 national Institute for Health and Care, uh, um, research in the uk. 00:13:34.918 --> 00:13:39.778 Um, I should say, uh, Tony and I also, uh, worked for the NIHR 00:13:39.783 --> 00:13:41.188 as as well as, as you mentioned. 00:13:41.188 --> 00:13:43.348 So, uh, just to, to mention that. 00:13:43.648 --> 00:13:44.878 But we've now been, um. 00:13:45.388 --> 00:13:50.338 Really successful in getting multiple other funders, which I think highlights 00:13:50.338 --> 00:13:54.868 the, the sort of recognition of the, the importance of the unmet 00:13:54.868 --> 00:14:00.628 need Were funded in the US and were by the Department of Defense. 00:14:01.018 --> 00:14:04.408 Were funded in, uh, Canada by the CIHR. 00:14:04.703 --> 00:14:09.053 We're funded, uh, in Australia now by, uh, a collaborative between 00:14:09.053 --> 00:14:14.873 N-H-M-R-C and MRFF, and we've also got funding in Ireland from HRB as 00:14:14.873 --> 00:14:17.723 well as, uh, Germany and, uh, Japan. 00:14:18.113 --> 00:14:20.933 I don't think I've left any out there, but if I have, uh, but 00:14:21.113 --> 00:14:22.553 Tony will correct me or Victoria. 00:14:23.023 --> 00:14:23.263 Scott Berry: Yeah. 00:14:24.538 --> 00:14:29.488 Okay, so we, we kind of understand that what, what we want this to solve. 00:14:29.728 --> 00:14:33.568 And now this sort of comes to the clinical trial science part of it. 00:14:33.568 --> 00:14:37.408 So how do we create something that solves some of these problems? 00:14:37.708 --> 00:14:44.128 So maybe we should now talk about what the trial is, uh, the science of the trial. 00:14:44.518 --> 00:14:47.518 So, Victoria, this is a platform trial. 00:14:47.548 --> 00:14:52.138 Now, platform trials can mean lots of different things, uh, in this. 00:14:52.483 --> 00:14:56.353 Uh, what, let, let's talk about the trial design. 00:14:56.353 --> 00:15:00.763 What, what is the trial design now to help create some of these solutions? 00:15:01.998 --> 00:15:02.388 Victoria Cornelius: Uh, yeah. 00:15:02.388 --> 00:15:03.138 Thank you Scott. 00:15:03.138 --> 00:15:05.208 It's uh, lovely to be with you here today as well. 00:15:05.598 --> 00:15:06.018 Um. 00:15:06.523 --> 00:15:10.123 So it is interesting that you said that platforms can be lots of different things. 00:15:10.183 --> 00:15:15.193 Um, uh, I think, yeah, it, it would be good to talk about that and get your, 00:15:15.223 --> 00:15:18.193 your opinion on whether they, how, how, how different those things can be. 00:15:18.463 --> 00:15:20.773 Ultimately, we're talking about platform trials. 00:15:21.223 --> 00:15:26.173 I think we're talking about, um, one area, one clinical area, and we're 00:15:26.173 --> 00:15:31.573 talking about the ability to adapt things over time, to add in interventions and 00:15:31.573 --> 00:15:33.133 to drop those interventions as well. 00:15:33.133 --> 00:15:34.513 So that, that's how I would see it. 00:15:34.513 --> 00:15:35.298 So some sort of adaptive. 00:15:36.043 --> 00:15:40.363 Uh, trials design within, you know, o overarching, uh, structure. 00:15:41.203 --> 00:15:43.723 Um, so with this, this is exciting. 00:15:43.723 --> 00:15:46.543 Pan, pan is exciting 'cause we've got these, like I say, we're doing these, 00:15:46.663 --> 00:15:48.823 uh, interest in these two phenotypes. 00:15:48.823 --> 00:15:51.733 I dunno if we've named them yet actually as hyper and hypo 00:15:51.733 --> 00:15:53.833 inflammatory, uh, processes. 00:15:54.133 --> 00:15:56.323 Um, and we, what? 00:15:56.863 --> 00:16:03.283 The, the overarching design actually is to stratify by, by these two sub phenotypes. 00:16:03.523 --> 00:16:08.203 So I would call it a stratified, uh, trial, uh, adaptive. 00:16:08.713 --> 00:16:13.963 Um, and within that, um, we are gonna be using, we've, we've chosen to do this 00:16:13.993 --> 00:16:16.183 within a analysis framework as well. 00:16:17.368 --> 00:16:17.578 Scott Berry: Hmm. 00:16:18.418 --> 00:16:18.778 Okay. 00:16:18.778 --> 00:16:22.198 So there's, uh, by, by the way, one of the fun challenges of these 00:16:22.198 --> 00:16:24.328 podcasts is not having slides. 00:16:24.388 --> 00:16:27.928 Uh, or you could have a slide that shows all of these components 00:16:27.928 --> 00:16:30.478 together, but you have to sort of describe it to the audience. 00:16:30.838 --> 00:16:34.618 So the platform part of this is you're gonna bring in multiple therapies, 00:16:34.618 --> 00:16:37.858 and right now you have two of them that you have brought into the 00:16:37.858 --> 00:16:41.668 trial and we can talk more about, but Simvastatin and Baricitinib. 00:16:42.268 --> 00:16:45.868 So you have the two arms in remap cap, for example. 00:16:46.358 --> 00:16:52.568 We might do factorial randomization, where you could get one or the other or both. 00:16:52.928 --> 00:16:57.308 In this trial, I think at least now you've got this setup where you have parallel 00:16:57.308 --> 00:17:00.878 arms, so you have a common control arm. 00:17:01.178 --> 00:17:05.918 You can have simvastatin and Baricitinib, and when you add a new arm, it kind 00:17:05.918 --> 00:17:07.778 of enters in this parallel way. 00:17:08.048 --> 00:17:11.408 So a patient that comes in is randomized among. 00:17:12.028 --> 00:17:16.198 Today, right now with the, with those two experimental arms, randomized 00:17:16.198 --> 00:17:17.878 among those three possibilities. 00:17:18.178 --> 00:17:18.958 Is that right? 00:17:19.738 --> 00:17:20.428 Victoria Cornelius: That's right. 00:17:20.458 --> 00:17:22.138 But stratified obviously with, because we are 00:17:22.138 --> 00:17:25.298 doing it in the hypo inflammatory and the hyper inflammatory as well. 00:17:25.768 --> 00:17:26.038 Yeah. 00:17:26.188 --> 00:17:26.638 And we, yeah. 00:17:26.638 --> 00:17:28.528 So it's not a multifactorial. 00:17:30.958 --> 00:17:34.168 Scott Berry: Now, the, the, the sub phenotypes that you talked 00:17:34.168 --> 00:17:35.488 about, the hypo and hyper. 00:17:36.628 --> 00:17:38.638 Uh, so a patient that comes in. 00:17:38.638 --> 00:17:40.948 So let's talk about the perspective of a patient. 00:17:40.948 --> 00:17:45.868 A patient that comes in is the, the, the process of this. 00:17:45.868 --> 00:17:50.128 So Tony, you see a patient, they, they fit the a RDS. 00:17:50.128 --> 00:17:50.728 Inclusion. 00:17:50.728 --> 00:17:55.288 Exclusion are the inclusion exclusion criteria for simvastatin 00:17:55.288 --> 00:17:57.148 and baricitinib identical. 00:17:58.258 --> 00:17:59.248 Anthony Gordon: They're very similar, so. 00:18:00.238 --> 00:18:04.618 As a platform, we have inclusion exclusion criteria for the platform. 00:18:04.618 --> 00:18:08.578 So as you said, it's essentially a patient with a RDS. 00:18:09.628 --> 00:18:16.018 Um, there are then they're eligible for the, for the platform. 00:18:16.513 --> 00:18:16.843 Scott Berry: Uh huh. 00:18:17.428 --> 00:18:21.778 Anthony Gordon: Importantly it is then at that time they have their blood samples 00:18:21.778 --> 00:18:28.288 measured and their assignment to the hypo or hypo inflammatory sub phenotype. 00:18:28.963 --> 00:18:34.513 Done upfront before they're randomized so that they can then be randomized 00:18:34.573 --> 00:18:36.553 essentially into the two strata. 00:18:36.643 --> 00:18:42.223 Um, according to the, the sub phenotypes, the, the inclusion 00:18:42.223 --> 00:18:43.573 exclusion criteria for each drug. 00:18:43.603 --> 00:18:44.733 Um, as I said, I, I. 00:18:45.988 --> 00:18:49.498 Virtually the same, but there have to be a few exceptions because 00:18:49.498 --> 00:18:50.608 the drugs work in different ways. 00:18:50.608 --> 00:18:52.948 So the obvious one is if you're allergic to one of the 00:18:52.948 --> 00:18:54.628 medications, you can't have it. 00:18:54.958 --> 00:18:55.918 But there are some. 00:18:55.918 --> 00:18:59.998 For instance, with simvastatin, you have to be careful with drug interactions. 00:19:00.148 --> 00:19:02.638 So if you're on another drug, you may be excluded. 00:19:02.968 --> 00:19:07.948 There's concerns around patients with renal failure, for instance, that 00:19:07.948 --> 00:19:09.568 would exclude you from Baricitinib. 00:19:09.568 --> 00:19:11.458 But essentially they're the same. 00:19:11.458 --> 00:19:11.878 And then. 00:19:13.483 --> 00:19:16.753 Well those eligibility, once you know, the sub phenotype has been 00:19:16.753 --> 00:19:22.303 determined, the randomization happens separately within each stratum, the 00:19:22.303 --> 00:19:24.193 way you, the patient is allocated. 00:19:24.463 --> 00:19:29.053 And so, as Victoria said, it's then a stratified trial. 00:19:29.263 --> 00:19:33.643 Um, so the patients are in either one of the sub phenotypes. 00:19:34.933 --> 00:19:38.473 Scott Berry: so as as a patient comes in, they're classified by the sub phenotypes. 00:19:38.473 --> 00:19:41.023 Right now, I believe Simvastatin and Baricitinib are. 00:19:42.973 --> 00:19:48.253 Uh, um, they're, they're getting patients from either phenotype when they start. 00:19:48.463 --> 00:19:53.593 I imagine you could bring in a third arm where you already know 00:19:53.593 --> 00:19:58.753 or think it would be, uh, uh, not good to test them in one of them. 00:19:58.753 --> 00:20:01.183 And it could, it could, could come in, in only one, I assume, soon. 00:20:03.483 --> 00:20:04.948 Anthony Gordon: It could in theory. 00:20:05.068 --> 00:20:08.368 Um, um, and this is an interesting point. 00:20:08.368 --> 00:20:13.918 We've had a lot of discussion around this, uh, particularly actually around 00:20:13.918 --> 00:20:15.383 simvastatin, for instance, because. 00:20:16.888 --> 00:20:22.438 The evidence from Danny's previous trial, maybe he should, uh, describe it. 00:20:22.618 --> 00:20:29.098 Um, or maybe I should keep it shorter, that, uh, d Danny ran a, Danny ran a 00:20:29.098 --> 00:20:34.228 previous trial, um, of Simvastatin in a RDS and in the overall population 00:20:35.008 --> 00:20:40.888 didn't show any, uh, statistically significant benefit, but then. 00:20:41.308 --> 00:20:47.638 Doing the, uh, sub phenotype analysis in a postoc way showed there was benefit 00:20:47.638 --> 00:20:50.938 in the hyper inflammatory group, but not in the hypo inflammatory group. 00:20:51.178 --> 00:20:54.718 So Danny and I particularly had the conversation about, well, 00:20:55.558 --> 00:20:58.408 let's just go forward in the hyper inflammatory sub phenotype. 00:20:58.408 --> 00:21:04.468 But I think a lot of people want to see both groups to understand 00:21:04.468 --> 00:21:05.608 if there really is a difference. 00:21:05.848 --> 00:21:09.988 And I think importantly, if you take the wider picture drug regulators. 00:21:10.408 --> 00:21:16.888 Want to understand the effect I if in the two sub phenotypes to understand, 00:21:16.978 --> 00:21:24.088 um, partly to know should have you recruited the optimal population, but 00:21:24.088 --> 00:21:27.598 also what about safety, for instance, in the other group, if, if people 00:21:27.598 --> 00:21:31.948 started using it outside of a sub phenotype, what would the effect be? 00:21:31.948 --> 00:21:36.148 So we thought at this stage we, it was important to include them 00:21:36.148 --> 00:21:38.788 in both, uh, sub phenotypes. 00:21:39.448 --> 00:21:41.488 Um, at, at, at initial. 00:21:41.488 --> 00:21:43.918 But whether that changes over time, I think it will be interesting as 00:21:43.918 --> 00:21:46.348 new, um, drugs potentially come in. 00:21:46.348 --> 00:21:51.208 But at the moment, yes, we're including them in both strata and want to analyze 00:21:51.208 --> 00:21:54.243 them separately throughout the platform. 00:21:54.943 --> 00:21:55.143 Scott Berry: Yep. 00:21:55.448 --> 00:21:58.723 Danny McAuley: And I guess just to add a couple of bits, that the, the patients 00:21:58.723 --> 00:22:04.033 were also really pain, that we didn't miss an effect in the other phenotype 00:22:04.123 --> 00:22:07.483 where we, even though we expected it to work in hyper inflammatory, 00:22:07.783 --> 00:22:10.273 and, you know, I think that's one of the things that we're, we're pain. 00:22:10.273 --> 00:22:14.563 That the, the sort of design is underpinned by, uh, patient and, 00:22:14.563 --> 00:22:16.333 and sort of public involvement. 00:22:17.323 --> 00:22:21.823 Um, so that, that was actually a, a, another, uh, key piece of it. 00:22:22.213 --> 00:22:22.813 Um, 00:22:23.383 --> 00:22:23.713 Yeah, 00:22:24.153 --> 00:22:26.113 Scott Berry: Yeah, so, so, so I think that's great. 00:22:26.113 --> 00:22:30.373 And you, you said it's stratified by this, and that's one of those words that can 00:22:30.373 --> 00:22:31.963 mean a whole bunch of different things. 00:22:32.353 --> 00:22:36.793 Um, uh, whether it's the randomization, whether it's the analysis, but it 00:22:36.793 --> 00:22:40.333 could be during the course of the trial and we'll get to the adaptive design. 00:22:40.688 --> 00:22:43.178 That you stop enrolling one of the drugs. 00:22:43.178 --> 00:22:47.738 So for example, suppose this bears out that simvastatin doesn't work in hypo, 00:22:47.978 --> 00:22:52.268 and you, you could stop enrolling that in hypo based on the empirical evidence. 00:22:52.568 --> 00:22:58.148 And then if a hypo patient comes in, they would only be eligible for the 00:22:58.148 --> 00:23:03.878 control and baricitinib and not, uh, randomized to simvastatin at that point. 00:23:03.878 --> 00:23:06.158 But yet, a, a hyper could be random. 00:23:07.198 --> 00:23:07.648 To that. 00:23:08.278 --> 00:23:13.138 Um, uh, so you're, you're, you're, this, this could be enrichment. 00:23:13.468 --> 00:23:17.158 We haven't said the term enrichment, but you know, as you go along, you're, 00:23:17.158 --> 00:23:19.383 you're learning this as well, uh, about. 00:23:20.038 --> 00:23:25.558 Benefit or not within them That the, the, the, this is a case where you 00:23:25.558 --> 00:23:29.308 don't, what the, let's talk about the control arm, the common control arm. 00:23:29.578 --> 00:23:33.268 You're not using placebos here, so we're not doing double 00:23:33.268 --> 00:23:35.608 blinding or multiple blinding. 00:23:35.608 --> 00:23:39.568 So, uh, that pa you're not blinded to what the treatments 00:23:39.568 --> 00:23:41.458 take, the patient is taking here. 00:23:41.728 --> 00:23:44.578 And so control is standard of care, I assume. 00:23:45.868 --> 00:23:46.198 Okay. 00:23:46.558 --> 00:23:46.888 Okay. 00:23:47.638 --> 00:23:50.908 Alright, so we've got the, the this. 00:23:50.908 --> 00:23:54.538 A patient comes in, they're classified by hyper and hypo. 00:23:54.778 --> 00:23:57.988 They are then randomized among the arms that are enrolling, that 00:23:57.988 --> 00:24:00.118 always equal across the arms. 00:24:00.478 --> 00:24:04.558 Victoria, was there any thought of doing response? 00:24:04.558 --> 00:24:07.858 Adaptive randomization, uh, in those cases. 00:24:09.028 --> 00:24:12.238 Victoria Cornelius: Yeah, I mean, we talked about this a lot, uh, 00:24:12.268 --> 00:24:17.068 during the design and in the end we decided not to use it. 00:24:17.098 --> 00:24:17.278 So 00:24:17.278 --> 00:24:18.568 we, we, we did consider it. 00:24:18.988 --> 00:24:23.608 And it, and it's interesting actually, it, part of it was, uh, the, the thought 00:24:23.608 --> 00:24:28.048 of around the operational side of these things, um, as well as only having 00:24:28.048 --> 00:24:29.968 sort of the, the two active arms versus 00:24:29.968 --> 00:24:31.563 the control as well, and not being convinced. 00:24:32.458 --> 00:24:34.558 Of, of the statistical benefits as well. 00:24:34.858 --> 00:24:39.598 So, uh, we, we chose not to do it, uh, to implement that. 00:24:40.348 --> 00:24:42.718 Scott Berry: Yeah, no, I, I think that's, it's a really interesting question. 00:24:42.898 --> 00:24:47.548 If you had six or seven and it was a pandemic scenario and you wanted to 00:24:47.548 --> 00:24:52.738 accelerate drug one to the detriment of drug two, that might be more compelling. 00:24:52.738 --> 00:24:58.618 I think here you're trying to find the evidence for a drug and accelerating 00:24:58.618 --> 00:25:00.658 simvastatin and slowing baricitinib. 00:25:01.123 --> 00:25:04.153 Probably doesn't make sense in what your trial is trying to do. 00:25:04.153 --> 00:25:08.023 So I, I it's, and, and you don't want to add that complexity as you 00:25:08.023 --> 00:25:10.183 described for not much benefit. 00:25:10.183 --> 00:25:11.533 So I think that makes sense. 00:25:12.078 --> 00:25:15.948 Anthony Gordon: Yeah, Scott, just to add, we, that's exactly it. 00:25:16.428 --> 00:25:20.778 As you said, outside of a pandemic where there is no time urgency, um, this 00:25:20.778 --> 00:25:26.118 is about comparing each drug against a consultant to learn whether it's. 00:25:26.548 --> 00:25:29.368 A promising therapy that we can talk about what happens at 00:25:29.368 --> 00:25:31.078 the end of this, uh, platform. 00:25:31.078 --> 00:25:32.788 Because this is a phase two platform. 00:25:32.998 --> 00:25:37.348 It's to identify promising drugs that would progress. 00:25:37.348 --> 00:25:41.338 It's not about comparing different drugs, it's, it is working 00:25:41.338 --> 00:25:43.588 out the efficacy of each drug. 00:25:43.588 --> 00:25:49.768 And so therefore the efficiency of one, essentially one to one randomization 00:25:49.768 --> 00:25:51.868 with the control is I think, um. 00:25:52.753 --> 00:25:56.593 This, me saying it to some statisticians now, I think is the most efficient 00:25:56.743 --> 00:26:01.183 design, um, to get your, your answers quickly for each individual drug. 00:26:01.693 --> 00:26:04.663 And so that, that's why we're keeping it, that fixed ratio. 00:26:05.383 --> 00:26:07.993 Danny McAuley: And I think the other thing, Scott, sorry Scott, the other 00:26:07.993 --> 00:26:09.373 thing, Victoria might wanna come in. 00:26:09.583 --> 00:26:13.123 You know, the way that we've set up the, the triggers to stop is that, you know, 00:26:13.123 --> 00:26:18.013 you have to, you know, be convincing for efficacy, but we don't wanna prove harm. 00:26:18.193 --> 00:26:22.303 So, you know, we stop relatively early if the signal isn't promising. 00:26:22.633 --> 00:26:25.238 Uh, almost trying to back the winner type approach. 00:26:27.238 --> 00:26:29.818 Scott Berry: Okay, so we've talked about what it looks like for a patient 00:26:29.818 --> 00:26:32.008 going in now when an arm comes in. 00:26:32.008 --> 00:26:35.458 So you have, you have a master protocol where when you bring 00:26:35.458 --> 00:26:41.188 Simvastatin or Baricitinib or arm C in, it comes in as an appendix. 00:26:41.368 --> 00:26:45.718 Let's talk about what that looks like from the perspective of an arm and maybe 00:26:45.718 --> 00:26:50.908 even thinking about a pharmaceutical company that wants to put an agent in and 00:26:50.908 --> 00:26:53.338 thinking about, okay, what happens to my. 00:26:54.313 --> 00:26:57.193 My, my, my baby as it goes into this trial. 00:26:57.193 --> 00:26:59.383 What is the, the design for that? 00:26:59.923 --> 00:27:04.963 So the, the, the arm enters in and it wants to enroll in both, 00:27:05.623 --> 00:27:07.963 uh, phenotypes, sub phenotypes. 00:27:08.263 --> 00:27:10.663 What is the design for an arm? 00:27:10.663 --> 00:27:12.703 Victoria, what does that look like? 00:27:14.863 --> 00:27:16.093 Sample size, 00:27:16.198 --> 00:27:16.648 Victoria Cornelius: Yeah. 00:27:16.648 --> 00:27:17.068 So 00:27:17.473 --> 00:27:18.043 Scott Berry: analysis. 00:27:18.043 --> 00:27:18.133 Yep. 00:27:18.958 --> 00:27:19.228 Victoria Cornelius: yeah. 00:27:19.228 --> 00:27:22.588 So, um, this is, again, this is something we've been, uh, obviously 00:27:22.588 --> 00:27:25.318 spending a lot of time on the current design with the arms. 00:27:25.468 --> 00:27:29.518 And actually one thing of the things I did want to talk about, uh, with, 00:27:29.578 --> 00:27:32.188 um, this design, because we are, we are, we are really lucky to be 00:27:32.188 --> 00:27:33.448 doing this stratified trial, this 00:27:33.448 --> 00:27:37.438 precision medicine approach is actually, in order to do that, 00:27:37.768 --> 00:27:39.658 we've got to have devices. 00:27:40.363 --> 00:27:44.323 And so one of the design considerations for the whole platform was that 00:27:44.323 --> 00:27:47.143 the number of devices we can get, because that's gonna restrict the 00:27:47.143 --> 00:27:50.653 number of centers we can include, is gonna restrict the sample size. 00:27:50.893 --> 00:27:51.793 So that was So we've 00:27:52.018 --> 00:27:55.648 Scott Berry: So sorry, can I, devices meaning ability 00:27:55.648 --> 00:27:56.908 to identify hypo and hyper. 00:27:58.243 --> 00:27:58.753 Victoria Cornelius: Yes. 00:27:59.113 --> 00:27:59.653 Scott Berry: Uh, okay. 00:27:59.658 --> 00:27:59.698 Okay. 00:28:00.568 --> 00:28:03.658 Victoria Cornelius: so one of the very early design considerations is around, 00:28:04.138 --> 00:28:08.788 around, uh, getting enough evidence for the phase two, doing that robustly, 00:28:08.788 --> 00:28:13.168 as Danny had said, but actually just getting enough evidence such that 00:28:13.558 --> 00:28:15.148 it, it's good enough to get through. 00:28:15.148 --> 00:28:15.418 Right. 00:28:15.418 --> 00:28:17.128 Let's test this in phase three. 00:28:17.878 --> 00:28:22.018 So, So, we, so there is a sample size consideration there, so regard 00:28:22.018 --> 00:28:24.328 to bringing in an additional arm. 00:28:24.598 --> 00:28:27.683 I think part of that will be, have to come within the whole framework. 00:28:28.423 --> 00:28:34.183 Of, uh, how far we are along with, um, the current two active interventions. 00:28:34.213 --> 00:28:34.423 Yeah. 00:28:35.488 --> 00:28:36.928 Scott Berry: So, uh, go ahead. 00:28:37.003 --> 00:28:37.453 Victoria Cornelius: yeah, Sorry. 00:28:37.453 --> 00:28:41.083 just to say it, so at, maybe if it came in now at the start, it would 00:28:41.083 --> 00:28:42.643 have very similar considerations. 00:28:42.853 --> 00:28:46.543 Um, but uh, later on we would have to redo and relook at those things. 00:28:47.413 --> 00:28:52.693 Scott Berry: Okay, so a a, the, the design for Simvastatin, for example, 00:28:52.693 --> 00:28:57.913 is it comes in and it's analyzed separately in hyper and hypo. 00:28:58.333 --> 00:29:02.563 Uh, and maybe we'll come back to the question of, uh, borrowing or, or 00:29:02.563 --> 00:29:07.183 independent analysis within there, but you've got an adaptive design that every. 00:29:07.648 --> 00:29:12.748 Every three months, you do an interim analysis, and when a minimum sample 00:29:12.748 --> 00:29:18.508 size is reached for that particular arm, it enters into the possibility 00:29:18.508 --> 00:29:23.998 for stopping rules where it could be stopped for promise, or it could be 00:29:23.998 --> 00:29:29.848 stopped for lack of promise, presumably, or it could hit a maximum sample size. 00:29:30.178 --> 00:29:32.908 So if my arm comes in, it goes through these. 00:29:33.238 --> 00:29:38.848 Quarterly analyses and, uh, the maximum sample size, just roughly, 00:29:39.118 --> 00:29:41.758 uh, for, for an arm is what? 00:29:42.558 --> 00:29:44.628 Victoria Cornelius: It's around about 505, I think. 00:29:44.628 --> 00:29:45.378 5, 2 5. 00:29:45.378 --> 00:29:46.308 For each arm? 00:29:46.948 --> 00:29:48.748 Scott Berry: For, for each sub phenotype? 00:29:48.888 --> 00:29:49.933 Victoria Cornelius: Yeah, for each arm. 00:29:49.948 --> 00:29:50.278 Scott Berry: Okay. 00:29:50.428 --> 00:29:54.238 So once it reaches that max, where, where we've got enough 00:29:54.238 --> 00:29:57.928 information, this is phase two, but it could stop sooner than that. 00:29:57.928 --> 00:30:01.888 And it can stop at different times within hyper and hypo. 00:30:02.248 --> 00:30:06.478 And for different reasons, it could be promising and hyper simvastatin 00:30:06.658 --> 00:30:10.798 if, if it reproduces a previous result and it could lack promise in 00:30:10.798 --> 00:30:13.258 hypo, uh, as a potential within that. 00:30:13.858 --> 00:30:18.778 Now, the, the analysis that done, uh, the, there's, there's a huge amount of question 00:30:18.778 --> 00:30:20.953 in these, in intensive care type trials. 00:30:21.148 --> 00:30:22.288 There's what's the endpoint? 00:30:22.678 --> 00:30:27.748 Um, so what is the primary endpoint that is used for the determination of 00:30:28.078 --> 00:30:30.088 promise or not promise for an agent? 00:30:31.278 --> 00:30:33.228 Victoria Cornelius: Yeah, a, uh, a, a great question. 00:30:33.528 --> 00:30:37.878 Um, so we had, uh, again, another thing we talked about a lot, um, 00:30:37.908 --> 00:30:41.748 obviously we are trying to, the, the obvious one would be to use mortality. 00:30:42.018 --> 00:30:44.718 Um, but we were trying to, we were trying to move beyond mortality 00:30:44.718 --> 00:30:45.988 in these situations because. 00:30:46.708 --> 00:30:52.048 We want something, um, partly because the statistical considerations around using 00:30:52.048 --> 00:30:56.848 it, which we need thousands and thousands, uh, but also trying to get an, uh, sort of 00:30:56.848 --> 00:31:00.298 capture an important part of the patient journey as well within the outcome. 00:31:00.748 --> 00:31:03.928 So terribly inspired by the REMAP cap trial. 00:31:04.318 --> 00:31:09.448 Um, we have got the primary outcome of 28 days of a composite 00:31:09.718 --> 00:31:11.308 the same, but it's for 28 days. 00:31:11.713 --> 00:31:13.213 Organ free support. 00:31:13.573 --> 00:31:18.403 Um, so we've got our mortality being our minus one score and then, and 00:31:18.403 --> 00:31:20.443 we've got it up to zero, up to 28 days. 00:31:20.443 --> 00:31:22.183 Organ free support being the best outcome. 00:31:23.668 --> 00:31:27.208 Scott Berry: Okay, so you described these ordinal outcomes where death is the worst 00:31:27.208 --> 00:31:32.638 outcome, and then being on organ support for 28 days is the next worst, and so on. 00:31:32.668 --> 00:31:35.968 And so you've got this ordinal outcome which you analyze 00:31:35.968 --> 00:31:37.558 using a proportional odds. 00:31:37.558 --> 00:31:39.418 Bayesian proportional odds model. 00:31:39.988 --> 00:31:40.348 Yep. 00:31:40.603 --> 00:31:41.293 Victoria Cornelius: Yeah, that's right. 00:31:41.383 --> 00:31:41.623 Yeah. 00:31:42.403 --> 00:31:42.913 Scott Berry: Okay. 00:31:43.213 --> 00:31:48.253 And, um, I, and in a really interesting question, and I think it almost becomes 00:31:48.253 --> 00:31:53.413 more interesting, part of what I found intriguing about the trial is you've got 00:31:53.413 --> 00:32:02.383 an appendix for subphenotypes where the science may evolve, where you learn that 00:32:02.413 --> 00:32:06.283 there are really important subphenotypes and you add them to the trial. 00:32:06.433 --> 00:32:09.943 Right now you have two, and so you have this question when you analyze. 00:32:10.363 --> 00:32:13.303 Um, uh, hyper and hypo. 00:32:13.543 --> 00:32:15.853 You run a completely separate model. 00:32:16.288 --> 00:32:19.468 Within each of these, and so there's no borrowing. 00:32:19.468 --> 00:32:23.608 So if a drug is doing well in one and well in the other, there's no 00:32:23.608 --> 00:32:25.318 kind of borrowing strength there. 00:32:25.678 --> 00:32:28.438 Partially you're worried about heterogeneity, and that may 00:32:28.438 --> 00:32:29.668 have the opposite effect. 00:32:29.908 --> 00:32:34.048 This could be a bigger problem if you add another sub phenotype 00:32:34.048 --> 00:32:36.958 to the trial that the question is then how do we analyze across this? 00:32:37.438 --> 00:32:40.678 Was there any discussion about potentially doing borrowing 00:32:41.403 --> 00:32:44.013 Victoria Cornelius: There, there was a lot of discussion about doing borrowing. 00:32:44.373 --> 00:32:47.463 Um, philosophically I have a problem with that. 00:32:47.763 --> 00:32:51.333 Like you say, we're actually out and we've got quite strong, you know, we've got some 00:32:51.333 --> 00:32:53.073 underpinning evidence we're expecting. 00:32:53.533 --> 00:32:54.883 Differential responses here. 00:32:55.213 --> 00:32:59.353 So it feels, the premise of it doesn't feel correct and, uh, to, to be borrowing 00:32:59.353 --> 00:33:03.403 across something where we don't, uh, expect it, you know, and we wouldn't, we 00:33:03.403 --> 00:33:05.203 would only then borrow if it was similar. 00:33:05.203 --> 00:33:07.543 And then I actually, I, as a statistician, I struggle. 00:33:07.858 --> 00:33:09.868 With only borrowing when it's similar as well. 00:33:09.868 --> 00:33:14.458 So I, I do struggle a little bit with the borrowing concept when it's not 00:33:14.698 --> 00:33:16.828 underpinned by other justifications. 00:33:16.828 --> 00:33:18.838 Yeah, so we did discuss it. 00:33:19.138 --> 00:33:23.608 I think ultimately it was because, uh, we are expecting differential 00:33:23.608 --> 00:33:24.958 treatment effects here, so we wouldn't. 00:33:25.103 --> 00:33:25.433 Scott Berry: Yeah. 00:33:25.943 --> 00:33:26.243 Yeah. 00:33:26.963 --> 00:33:29.453 The, the problem of dimensionality could. 00:33:30.058 --> 00:33:35.668 Be an enemy to you though right now you've got maximums of about 502 groups. 00:33:35.818 --> 00:33:39.778 Suppose you added another sub phenotype that made it two by two. 00:33:40.258 --> 00:33:44.578 Now 504 different groups becomes 2000. 00:33:44.938 --> 00:33:47.998 If you had two by two by two, now you've got, uh, you know, 00:33:47.998 --> 00:33:49.108 you, you're making this. 00:33:49.588 --> 00:33:51.868 8,000, you're making this an enormous trial. 00:33:51.868 --> 00:33:55.708 4,000, an enormous trial without some level of borrowing, 00:33:56.158 --> 00:33:57.598 but you're not there yet. 00:33:57.658 --> 00:34:01.768 You're two where, and, and borrowing in two is always kind of a weird thing. 00:34:01.918 --> 00:34:02.728 Yes or no? 00:34:03.088 --> 00:34:08.848 Uh, I, I, I, the, the science of this, do you expect to have more sub 00:34:09.658 --> 00:34:11.998 phenotypes in the next few years? 00:34:12.358 --> 00:34:12.838 Tony? 00:34:13.993 --> 00:34:17.383 Anthony Gordon: Yeah, it is a really interesting point, Scott. 00:34:17.563 --> 00:34:21.883 Um, I think there is, there is a strong possibility we 00:34:21.883 --> 00:34:25.033 might, um, Victoria might get. 00:34:25.903 --> 00:34:27.133 Try and urge just 00:34:27.388 --> 00:34:27.678 Scott Berry: Yeah. 00:34:28.153 --> 00:34:33.043 Anthony Gordon: to hold back our enthusiasm, but as Danny alluded to right 00:34:33.043 --> 00:34:40.513 at the beginning here, the, the, there is this, the clinical, uh, syndromes. 00:34:40.843 --> 00:34:45.433 We, we, we talked about a RDS, but there's a massive overlap with sepsis in general. 00:34:45.703 --> 00:34:50.293 Um, you know, ar they're like two big parts of a Venn diagram. 00:34:50.293 --> 00:34:51.343 They overlap, but actually. 00:34:52.153 --> 00:34:55.303 They're very similar, the biological processes. 00:34:55.363 --> 00:35:00.073 And so you could imagine we might want to include a broader population with 00:35:00.073 --> 00:35:05.233 sepsis and a RDS because the underlying biological processes are similar. 00:35:05.863 --> 00:35:11.083 And also the, these hypo and hyper inflammatory phenotypes are 00:35:11.083 --> 00:35:13.003 probably the most well described. 00:35:13.003 --> 00:35:14.528 But there are others work we've been doing. 00:35:15.493 --> 00:35:20.173 Um, with colleagues in Oxford, for instance, uh, Julian Knight, um, 00:35:20.443 --> 00:35:25.213 around gene expression profiles that is looking really promising as well as 00:35:25.513 --> 00:35:31.663 identifying, um, sub phenotypes that will respond to different treatments if 00:35:31.663 --> 00:35:33.073 we were then to bring them all together. 00:35:33.628 --> 00:35:34.438 Then I think you're right. 00:35:34.498 --> 00:35:38.248 Making a good point of why we might need to consider borrowing, but 00:35:38.428 --> 00:35:41.758 I, I don't think we're there yet, but we're always thinking big, 00:35:41.878 --> 00:35:43.978 um, and looking to the future. 00:35:43.978 --> 00:35:48.088 But I think probably that's where we need to go to take the whole area of critical 00:35:48.088 --> 00:35:52.078 care research, um, further forward. 00:35:52.198 --> 00:35:55.978 Um, but we, we might need to come and revisit that, um, and 00:35:55.978 --> 00:35:59.338 do some brainstorming about what that actually would look like. 00:35:59.338 --> 00:35:59.668 I think. 00:36:00.358 --> 00:36:00.628 Scott Berry: Mm. 00:36:01.178 --> 00:36:03.673 Danny McAuley: And I guess Scott, the other thing to say, you know, we're, 00:36:03.673 --> 00:36:08.713 we're saying we've got this heterogeneous mass and we've divided into two, and 00:36:08.713 --> 00:36:11.623 the idea that two is the ground truth. 00:36:11.803 --> 00:36:16.213 So I think this is just the start of the, the journey to get, you know, better 00:36:16.273 --> 00:36:18.643 definition of all of these sub phenotypes. 00:36:18.883 --> 00:36:22.543 And that's one of the really important other design features were. 00:36:22.813 --> 00:36:26.503 Capturing biological samples within the trial as we go along 00:36:26.743 --> 00:36:30.643 to hopefully understand the, the, the syndromes better as well 00:36:31.318 --> 00:36:35.068 Scott Berry: So I imagine, suppose Simvastatin enrolls 500 00:36:35.068 --> 00:36:36.778 and 500 and it gets to the end. 00:36:37.168 --> 00:36:38.068 You've got these 00:36:38.083 --> 00:36:40.543 Danny McAuley: and works and and, obviously he's gonna work. 00:36:40.903 --> 00:36:41.173 Scott Berry: right. 00:36:41.353 --> 00:36:41.743 Yeah. 00:36:41.983 --> 00:36:42.853 Well that was clear. 00:36:43.153 --> 00:36:47.773 Um, but the, you've got the sub phenotypes, but I imagine you're 00:36:47.773 --> 00:36:54.043 gonna do a great deal of after the fact investigation of heterogeneity 00:36:54.133 --> 00:36:58.603 treatment effect over all kinds of different, uh, other things when the 00:36:58.603 --> 00:37:03.493 data are finally in, uh, also creation of new sub phenotypes based on the 00:37:03.493 --> 00:37:05.083 data that's accruing within this trial. 00:37:06.923 --> 00:37:07.213 Yeah. 00:37:07.998 --> 00:37:08.688 Anthony Gordon: Yeah. 00:37:08.808 --> 00:37:10.603 And, and Scott, I think that's an important part. 00:37:10.813 --> 00:37:18.978 These, these phenotypes have really emanated from postdoc analysis of a 00:37:18.978 --> 00:37:21.318 more standard traditional A versus B. 00:37:22.378 --> 00:37:22.888 Trial. 00:37:23.548 --> 00:37:27.928 And I think part of the international collaboration here is about 00:37:27.928 --> 00:37:30.448 trying to bring those who are interested in this field together. 00:37:31.438 --> 00:37:35.788 And this isn't just clinical trial, this is, there's people in the 00:37:35.788 --> 00:37:40.558 international group that do much more of the basic science and will do 00:37:40.558 --> 00:37:44.128 that biomarker work, that discovery, and actually try and take the whole 00:37:44.728 --> 00:37:48.988 field, uh, forward, uh, together. 00:37:49.228 --> 00:37:50.128 And so, rather than. 00:37:50.623 --> 00:37:54.493 Do it on an ad hoc basis, can we sort of plan it upfront that we are actually 00:37:54.493 --> 00:37:59.473 setting up the whole infrastructure, randomized patients in the trial, learn 00:37:59.563 --> 00:38:04.543 about those specific questions that are the randomized questions, and at 00:38:04.543 --> 00:38:10.783 the same time, um, build that precious resource that, um, is exploratory but 00:38:10.783 --> 00:38:15.608 drives the next question that can come into the platform, um, in, in the future. 00:38:16.993 --> 00:38:21.823 Scott Berry: Yeah, it makes a ton of sense to have this central resource of data in 00:38:21.823 --> 00:38:27.673 a RDS with multiple treatments to do this further, moving the science forward of 00:38:27.673 --> 00:38:34.063 understanding a RDS and endpoints and, uh, uh, different phenotypes is, is amazing. 00:38:34.363 --> 00:38:36.928 Uh, where if everybody did these trials separately. 00:38:37.273 --> 00:38:39.643 E, this is a much weaker. 00:38:40.048 --> 00:38:44.638 Global effort in a RDS, which is one of the, the, the things that I don't think 00:38:44.638 --> 00:38:50.338 is talked about much, um, is that the, having all this data together, so this, 00:38:50.368 --> 00:38:54.718 we, we've talked about the huge advantages of this, this bringing all this data 00:38:54.718 --> 00:38:56.788 together, bringing the multiple arms in. 00:38:57.338 --> 00:39:01.418 Uh, what are the challenges, uh, uh, in this moving forward? 00:39:01.418 --> 00:39:04.568 And I, I assume some of them are operational, logistical. 00:39:04.808 --> 00:39:05.978 I, I don't know if they're funding. 00:39:05.978 --> 00:39:09.458 What are the challenges that you're going to be facing, uh, maybe 00:39:09.458 --> 00:39:11.288 initially in running this trial? 00:39:11.288 --> 00:39:12.068 Victoria? 00:39:12.248 --> 00:39:15.818 What keeps you up at night, other than having me on your 00:39:15.818 --> 00:39:17.428 DSMB, what keeps you up at night? 00:39:19.673 --> 00:39:22.928 Victoria Cornelius: I, I definitely wanna bring in to Tony and DNI on this as well, 00:39:23.078 --> 00:39:26.608 but just so as you introduced me at the start, I also direct the, the kind of. 00:39:26.838 --> 00:39:28.248 Trials unit at Imperial. 00:39:28.428 --> 00:39:31.188 And actually for us, this is a really important, uh, platform 00:39:31.218 --> 00:39:32.598 'cause it's our first platform. 00:39:32.988 --> 00:39:36.018 And, uh, we've got, you know, we've got a lot of trials in our books and 00:39:36.078 --> 00:39:38.538 we've got about IET at the moment, but this is our first platform. 00:39:39.048 --> 00:39:43.068 And so we've had to learn quite a lot, uh, uh, across the whole team. 00:39:43.073 --> 00:39:43.323 Obviously the. 00:39:44.148 --> 00:39:45.168 Statistical team. 00:39:45.588 --> 00:39:50.118 Um, uh, it is, it's, you know, the funding for that, how to deliver and 00:39:50.118 --> 00:39:51.348 work together, all the rest of it. 00:39:51.348 --> 00:39:52.938 Our standard operating procedures. 00:39:52.938 --> 00:39:57.618 We've got our operational side and also our, our clinical data systems as well. 00:39:57.618 --> 00:40:01.398 So it's been, it's been quite a journey for us o on that side of things. 00:40:01.398 --> 00:40:05.293 And like I say, uh, we talked about the funder, but actually NHR uh, funded us. 00:40:06.083 --> 00:40:08.993 For an accelerator to get ourselves ready. 00:40:09.233 --> 00:40:12.713 So we had a year, uh, of preparing, you know, designing that trial. 00:40:13.013 --> 00:40:16.013 And then we've had a very generous funding, uh, to get the 00:40:16.013 --> 00:40:17.393 platform up and start as well. 00:40:17.393 --> 00:40:21.743 So I think we wouldn't have been able to do that now that we're embarking on it. 00:40:21.833 --> 00:40:25.553 Um, I'm gonna, I'll, I'll let Danny and Tony come in to what, 00:40:25.553 --> 00:40:26.783 what may be worrying them. 00:40:29.053 --> 00:40:32.473 Danny McAuley: So I, I mean, I, I guess this is probably a, um, 00:40:32.563 --> 00:40:34.153 a global issue to some degree. 00:40:34.153 --> 00:40:39.283 But, but, you know, clearly we want to protect patient safety at all costs, 00:40:39.853 --> 00:40:45.913 but the actual process and governance process of getting research established 00:40:45.943 --> 00:40:51.583 particularly, um, in our experience in the UK is very, very difficult. 00:40:51.793 --> 00:40:55.843 So I, I think, uh, that that is the one thing that that keeps. 00:40:56.128 --> 00:40:59.158 Well, not one, the one thing, but one of the many things that keeps 00:40:59.158 --> 00:41:05.338 me, uh, up at night and in terms of how we actually embed research more 00:41:05.338 --> 00:41:11.063 efficiently and, and increase, uh, recruitment into these important trials. 00:41:11.978 --> 00:41:15.698 Under just the bureaucracy that we face in, in getting the trials open. 00:41:15.698 --> 00:41:20.588 And it's a really important, uh, sort of national priority, I guess. 00:41:20.588 --> 00:41:23.708 The, the, the, the one other thing we, we work very closely and we 00:41:23.708 --> 00:41:28.598 talked about, um, the device that we, uh, use, uh, to phenotype patients. 00:41:28.598 --> 00:41:33.398 That's on a, a collaboration with, uh, a company called Randox and, 00:41:33.728 --> 00:41:36.128 uh, getting the, uh, sort of, um. 00:41:36.983 --> 00:41:40.193 Devices deployed at sites despite Rand's. 00:41:40.643 --> 00:41:44.093 You know, full support has been a, a challenge as well. 00:41:44.093 --> 00:41:47.483 And, and scaling that up internationally then, um, presents, 00:41:47.723 --> 00:41:49.643 uh, a potential, uh, challenge. 00:41:49.673 --> 00:41:52.223 I think, we'll, we'll overcome it, but they would be the, the 00:41:52.313 --> 00:41:53.663 two that worry me the most. 00:41:53.693 --> 00:41:55.253 Uh, but let's see what Tony has to say. 00:41:56.583 --> 00:41:56.943 Anthony Gordon: Yeah. 00:41:57.003 --> 00:42:01.443 Um, well now that we are funded, obviously that was the first issue 00:42:01.443 --> 00:42:04.743 is getting, getting the money and also particularly getting money 00:42:04.743 --> 00:42:07.983 in more than one, uh, region, you know, the international trials. 00:42:07.983 --> 00:42:10.233 But we, we, we are making good progress with that. 00:42:10.323 --> 00:42:11.823 Um, I think. 00:42:12.328 --> 00:42:17.248 Obviously there's elements of this, as alluded to, it involves both the 00:42:17.248 --> 00:42:21.238 device to measure the sub phenotype, the, the biomarkers and the drug. 00:42:21.238 --> 00:42:25.708 So you've got, you've got both device and drug aspects to manage. 00:42:27.238 --> 00:42:28.978 It's large and it's international. 00:42:29.248 --> 00:42:33.058 So I, I think the coordination of that by the trial management 00:42:33.058 --> 00:42:37.918 team is so crucial and I think. 00:42:38.578 --> 00:42:41.668 Uh, it doesn't keep me up at night 'cause I know I've got a good team that do it. 00:42:41.728 --> 00:42:45.088 But, um, I just would, I, I think I just need to recognize, 00:42:45.178 --> 00:42:47.938 uh, those, uh, team members. 00:42:47.998 --> 00:42:52.738 Uh, so in this case our, our team leader, Janice Best Lane, just as phenomenal. 00:42:53.008 --> 00:42:57.268 Her and colleagues have, uh, learned through COVID. 00:42:57.268 --> 00:43:00.958 They worked, you know, on the, um, in remap Cap and the 00:43:00.958 --> 00:43:03.058 challenges there, but how you keep. 00:43:04.123 --> 00:43:09.073 The whole, um, ship, um, sailing, um, to manage this, 00:43:09.253 --> 00:43:10.723 you and you do need that team. 00:43:10.723 --> 00:43:14.983 And so I think, uh, sort of advice to anybody setting out on these sort 00:43:14.983 --> 00:43:18.883 of things is you have to have that support team there to manage all 00:43:18.883 --> 00:43:26.923 aspects of the protocol that the modular nature of the, um, of that protocol. 00:43:27.823 --> 00:43:31.183 We are moving to try and do it all electronically rather than on paper, 00:43:31.183 --> 00:43:36.163 for instance, that things like that help, but then to coordinate it and 00:43:36.193 --> 00:43:41.803 keep all the sites involved around the world, um, to coordinate when there 00:43:41.803 --> 00:43:43.003 are so many things that can change. 00:43:43.003 --> 00:43:47.323 I think running any international trial is a challenge, but if it's a 00:43:47.323 --> 00:43:49.423 fixed protocol that doesn't change. 00:43:49.993 --> 00:43:53.023 It's still a challenge, but if you're gonna change it over 00:43:53.023 --> 00:43:54.193 time, how you manage that. 00:43:54.193 --> 00:43:55.483 And so, um. 00:43:56.188 --> 00:43:58.528 I, I think it can be done, but you need experience. 00:43:58.528 --> 00:43:59.638 You need an experience team. 00:44:00.028 --> 00:44:05.083 And so I just want to recognize the hard work, uh, they put into to deliver it. 00:44:06.283 --> 00:44:07.393 Danny McAuley: I just wanna second that. 00:44:07.393 --> 00:44:11.743 I mean, Janice and, uh, the team managing me, Tony and Victoria 00:44:11.743 --> 00:44:12.943 in itself is a challenge. 00:44:12.943 --> 00:44:16.903 Nevermind the, the, the whole trial infrastructure, but the, the, the 00:44:16.903 --> 00:44:20.353 other thing I just wanted to pick up on was that the funder, and it 00:44:20.353 --> 00:44:24.673 is this problem that we've had in the past of this idea of going to 00:44:24.673 --> 00:44:26.983 multiple jurisdictions and facing. 00:44:27.973 --> 00:44:31.993 Double, triple, quadruple jeopardy to get your trial funded. 00:44:32.233 --> 00:44:36.523 And I, I think we're starting to see funders work together, 00:44:36.943 --> 00:44:38.173 uh, on big ticket items. 00:44:38.173 --> 00:44:41.383 So I think hopefully going forward, uh, that might be a, a, 00:44:41.383 --> 00:44:42.973 an easier issue to get sort of, 00:44:43.903 --> 00:44:44.083 Scott Berry: Hmm. 00:44:45.253 --> 00:44:45.823 So there, 00:44:45.823 --> 00:44:49.753 there's a potential moving forward that you could bring in a pharma sponsor, 00:44:50.053 --> 00:44:52.393 uh, that, that could bring in funding. 00:44:52.393 --> 00:44:55.063 Another, uh, a way to bring in funding of this. 00:44:55.303 --> 00:44:57.553 What does the trial look like going forward? 00:44:57.553 --> 00:44:59.473 You know, what does steady state look like? 00:44:59.713 --> 00:45:02.113 What would be the optimal number of arms? 00:45:02.113 --> 00:45:05.863 And to some extent, there's a risk that one of these two treatments say drop in 00:45:05.863 --> 00:45:10.363 hypo, the other one drops in hyper and you're now running kind of an AB trial 00:45:10.363 --> 00:45:11.893 and each, you only have one arm in that. 00:45:12.283 --> 00:45:13.603 Would you like to have. 00:45:13.943 --> 00:45:15.893 Five arms, two arms. 00:45:15.893 --> 00:45:18.653 What is steady state and what, what is moving forward? 00:45:18.653 --> 00:45:20.213 What would you like this to look like? 00:45:20.393 --> 00:45:20.723 Tony? 00:45:22.288 --> 00:45:26.218 Anthony Gordon: Um, so importantly we have a pipeline, and that was something 00:45:26.218 --> 00:45:27.688 we set up right from the beginning. 00:45:27.688 --> 00:45:32.548 So there are already drugs in the, um, in the queue waiting to come in. 00:45:32.548 --> 00:45:36.718 So if, if we are lucky and get an early win. 00:45:37.588 --> 00:45:38.848 And that's an answer. 00:45:38.848 --> 00:45:41.788 I mean, that if, if we learn it doesn't work, that's still a win. 00:45:41.788 --> 00:45:46.018 We, we know it doesn't go forward and then we've got drugs ready to bring in. 00:45:46.708 --> 00:45:51.478 So, and importantly I think we have a process by doing that as well. 00:45:51.478 --> 00:45:54.208 So, um, and part of that is internal. 00:45:54.208 --> 00:45:58.498 We've have a prioritization committee, but we've also got an external committee 00:45:58.498 --> 00:46:05.068 to advise us, um, that includes clinical and pharmacology expertise to guide us. 00:46:05.068 --> 00:46:05.943 And I think that's something I've learned. 00:46:06.568 --> 00:46:08.878 From platforms, how you decide what comes in. 00:46:08.878 --> 00:46:11.098 It's good to have that independent oversight. 00:46:11.788 --> 00:46:15.628 I think it depends how many sites we have open. 00:46:15.688 --> 00:46:21.448 Um, and Victoria alluded to this, if we, we were talking 70 sites initially, 00:46:21.448 --> 00:46:26.278 we think the three arms with the two active interventions is probably the 00:46:26.278 --> 00:46:28.588 right number to get answers quickly. 00:46:29.128 --> 00:46:33.868 But if we manage to open 200 sites, um, because we are able to. 00:46:34.858 --> 00:46:40.858 Measure the biomarkers in, you know, more laboratories, for instance, I think we 00:46:40.858 --> 00:46:45.808 could then bring in a, you know, a third active intervention at the same time. 00:46:46.258 --> 00:46:51.118 Um, it it, so yeah, with that extra resource, we could do 00:46:51.118 --> 00:46:54.508 more, but we, we thought sensible to, you know, manage that. 00:46:54.568 --> 00:46:55.738 Um, at least initially. 00:46:56.443 --> 00:46:56.683 Scott Berry: Mm. 00:46:58.063 --> 00:47:00.853 So Tony, suppose you get word back. 00:47:01.093 --> 00:47:02.383 Uh, so, sorry, sorry. 00:47:02.623 --> 00:47:06.943 Uh, Danny, suppose you get word back that Simvastatin is successful in this trial. 00:47:06.943 --> 00:47:07.813 It's promising. 00:47:08.473 --> 00:47:09.613 What happens? 00:47:09.673 --> 00:47:11.683 Uh, do you run a phase three trial? 00:47:11.683 --> 00:47:14.023 Does Panther run a phase three trial? 00:47:14.233 --> 00:47:18.553 It's, I, I think this is completely, uh, off patent and generic. 00:47:18.553 --> 00:47:19.273 What happens? 00:47:20.893 --> 00:47:25.933 Danny McAuley: So I, I guess simvastatin is, um, probably a wee bit different from 00:47:25.933 --> 00:47:27.883 maybe some of the other drugs coming in. 00:47:27.883 --> 00:47:30.523 And I'll maybe explain, picking up on Tony's point. 00:47:30.913 --> 00:47:35.773 You know, there probably is a, a pretty strong prior in the hyper inflammatory 00:47:36.103 --> 00:47:38.563 group that, uh, simvastatin might work. 00:47:38.863 --> 00:47:41.593 And if we showed in a big phase two. 00:47:42.333 --> 00:47:48.573 With, you know, good certain day of, uh, um, positive effect that might be enough 00:47:48.573 --> 00:47:54.663 to change practice in that, I think fairly unique situation in most situations. 00:47:54.693 --> 00:47:58.023 You know, taking, uh, baricitinib, there is some proof of concept 00:47:58.023 --> 00:48:03.333 largely from, uh, COVID, but it's not probably enough to change practice 00:48:03.363 --> 00:48:08.253 even in the setting of a positive readout from the, uh, Panther trial. 00:48:08.583 --> 00:48:10.293 So to me, in that setting, 00:48:10.593 --> 00:48:11.523 that's where we would. 00:48:11.593 --> 00:48:16.183 We would feed the beast that is, uh, remap cap, which is so well set up to 00:48:16.183 --> 00:48:18.793 answer these multifactorial questions. 00:48:19.213 --> 00:48:22.123 And that's other, that's one of the other things that we, you know, talked 00:48:22.123 --> 00:48:24.343 about in terms of pandemic preparedness. 00:48:24.403 --> 00:48:27.973 You know, one of the nice things about Panther and Remap Cap working 00:48:27.973 --> 00:48:31.063 closely together is that, you know, if we did a pivot in pandemic 00:48:31.063 --> 00:48:33.013 preparedness, we would be able to. 00:48:33.213 --> 00:48:36.693 Quickly prioritize phase two assets that then could go into 00:48:36.693 --> 00:48:40.833 the, the, the phase three that that remap cap does, uh, very well. 00:48:40.833 --> 00:48:43.548 So that's how we sort of, uh, imagine that would work. 00:48:44.368 --> 00:48:44.698 Scott Berry: Mm. 00:48:45.208 --> 00:48:48.958 Anthony Gordon: Scott, can I, uh, suggest another alternative as 00:48:48.958 --> 00:48:50.433 well, and it's the sort of industry. 00:48:51.193 --> 00:48:52.393 Uh, perspective here. 00:48:52.843 --> 00:48:57.433 So I think that, you know, what we think is that, um, pharma companies 00:48:57.433 --> 00:48:59.713 will have a number of drugs already. 00:49:00.553 --> 00:49:04.063 Maybe they're already, um, got licenses for other respiratory 00:49:04.063 --> 00:49:05.983 or other inflammatory conditions. 00:49:07.273 --> 00:49:13.573 It's a big ask for them to, um, maybe run their own phase 2 trial. 00:49:13.573 --> 00:49:16.873 That, you know, we, as we've talked about, the issues with critical 00:49:16.873 --> 00:49:18.733 care trials, um, that haven't. 00:49:20.218 --> 00:49:22.768 Produced, uh, successful results. 00:49:23.008 --> 00:49:26.908 The idea would be we have a platform already up and running their asset that 00:49:26.908 --> 00:49:32.038 they have maybe using in a chronic lung disease, put it into the Panther platform. 00:49:32.608 --> 00:49:34.408 We've already got the infrastructure there. 00:49:34.438 --> 00:49:35.608 We've essentially de-risked it. 00:49:35.608 --> 00:49:39.028 They learn whether the drug is looking, promising. 00:49:39.508 --> 00:49:43.348 If it is, they get that result and they might choose to do their own 00:49:43.348 --> 00:49:46.738 licensing trial, um, for this indication. 00:49:47.293 --> 00:49:51.193 Or they learn it wasn't effective, and they learn that, uh, quickly 00:49:51.253 --> 00:49:53.353 and we've sort of de-risked the whole process for them. 00:49:53.353 --> 00:49:56.383 So we think this would appeal to them and, and gives a better 00:49:56.383 --> 00:50:01.093 chance for us to actually, uh, bring new therapies to patients. 00:50:01.153 --> 00:50:05.953 And it's that academic industry collaboration that, um, I 00:50:05.953 --> 00:50:07.063 think could be really helpful. 00:50:07.868 --> 00:50:08.383 Scott Berry: Uh, yeah. 00:50:08.383 --> 00:50:11.983 And the amazing thing is for, for that pharma company to go out and run that 00:50:11.983 --> 00:50:17.533 phase 2 trial and go get 70 sites and, uh, get devices and all that might, might 00:50:17.533 --> 00:50:21.673 cost x million dollars for you guys to do. 00:50:21.673 --> 00:50:23.743 It might be a 10th of that. 00:50:24.358 --> 00:50:28.858 Uh, and the cost, I, and I don't know what it is, but some fraction of that 00:50:29.248 --> 00:50:34.498 to, to do this, to take this shot on goal to, to the benefit of all, maybe 00:50:34.498 --> 00:50:36.838 you guys get 10 times as many shots. 00:50:36.838 --> 00:50:41.008 Because, because of that, it's just such a, an awesome potential. 00:50:42.943 --> 00:50:47.443 It seems by the way, that many of these platforms have come about by 00:50:47.443 --> 00:50:53.953 patient organizations in pancreatic cancer, in glioblastoma, in a LS where 00:50:53.953 --> 00:50:59.203 not things don't work and companies stop taking shots on goal because 00:50:59.203 --> 00:51:03.433 it's so challenging and many of these platforms are developed for Exactly. 00:51:03.433 --> 00:51:06.913 Trying to solve this, the, the, this, this dilemma. 00:51:06.913 --> 00:51:08.773 It's, it's a huge potential. 00:51:10.683 --> 00:51:12.778 Danny McAuley: Y Yeah, no, I think that's right Scott. 00:51:12.778 --> 00:51:17.608 And, and as Tony said, the, the idea of de-risking in a high risk. 00:51:18.253 --> 00:51:19.963 Environment that is critical care. 00:51:19.963 --> 00:51:25.603 You know, and the sort of the, the, almost the taking smart risk, uh, is, is 00:51:25.663 --> 00:51:30.343 sort of the mantra that we're trying to sort of get across to, uh, pharma, that 00:51:30.368 --> 00:51:35.863 that will be of benefit to, to them, but also to, uh, patient, uh, outcomes. 00:51:36.328 --> 00:51:36.658 Scott Berry: Hmm. 00:51:37.378 --> 00:51:41.968 And, and, uh, uh, a hugely positive thing with a successful 00:51:41.968 --> 00:51:44.083 drug in a RDS that improves. 00:51:45.148 --> 00:51:50.368 Organ support free days of the, the, the size of the potential, 00:51:50.608 --> 00:51:52.588 uh, win and the, the benefit. 00:51:52.678 --> 00:51:56.073 Uh, so the huge potential at the end of the day just been a, 00:51:56.078 --> 00:51:57.748 a challenging area to go into. 00:52:00.088 --> 00:52:00.958 All right. 00:52:00.988 --> 00:52:03.178 Uh, a very cool trial. 00:52:03.178 --> 00:52:08.488 I'm, I'm, I'm proud to, to watch this go on and excited to see how this goes. 00:52:08.968 --> 00:52:15.148 Uh, and lots of times I will be in the interim and, uh, I appreciate 00:52:15.148 --> 00:52:19.438 you all coming here in the interim, uh, and joining us all. 00:52:19.438 --> 00:52:20.638 So thank you all. 00:52:22.353 --> 00:52:22.808 Victoria Cornelius: Thank you very 00:52:22.808 --> 00:52:23.008 much. 00:52:23.008 --> 00:52:23.408 Thanks. 00:52:23.973 --> 00:52:24.243 Anthony Gordon: Thanks. 00:52:24.243 --> 00:52:26.013 It's been brilliant to chat about it, sco. 00:52:26.013 --> 00:52:26.223 Cheers. 00:52:26.443 --> 00:52:26.713 Scott Berry: Yeah. 00:52:26.983 --> 00:52:27.553 Wonderful. 00:52:27.553 --> 00:52:28.063 Thank you. 00:52:28.063 --> 00:52:31.273 And everybody else, we will be here in the interim.