WEBVTT NOTE This file was generated by Descript 00:00:00.030 --> 00:00:03.700 Judith: Welcome to Berry's In the Interim podcast, where we explore the 00:00:03.700 --> 00:00:07.940 cutting edge of innovative clinical trial design for the pharmaceutical and 00:00:07.940 --> 00:00:10.270 medical industries, and so much more. 00:00:10.530 --> 00:00:11.250 Let's dive in. 00:00:13.569 --> 00:00:18.389 Scott Berry: Welcome everybody to in the interim, uh, Barry consultants 00:00:18.469 --> 00:00:24.209 podcast about all things, science, statistical and clinical trial and medical 00:00:24.209 --> 00:00:27.749 sciences of a really cool guest today. 00:00:28.049 --> 00:00:34.359 Uh, Mike Krams is our guest today and for everybody's Uh, knowledge, he joined 00:00:34.369 --> 00:00:39.989 Berry Consultants in January, but Mike has a, a really interesting history in 00:00:39.989 --> 00:00:45.309 clinical trials, drug development, he's been 30 years at multiple pharmaceutical 00:00:45.329 --> 00:00:50.559 companies, he's led quantitative sciences departments at these, uh, he's done 00:00:50.639 --> 00:00:55.409 innovation everywhere he's been, and now we're thrilled to have him at Berry, but 00:00:55.409 --> 00:01:01.614 we talk about innovation, how do we do innovation at in, in drug development. 00:01:01.904 --> 00:01:04.114 So Mike, welcome to In the Interim. 00:01:04.539 --> 00:01:07.139 Mike Krams: Hi Scott, and hey, you forgot to mention how it all works. 00:01:07.139 --> 00:01:13.309 You write a letter to Professor Don Berry, uh, 25 years ago, and think there'll 00:01:13.309 --> 00:01:16.579 never be a response, but then there was a response, and the rest is history. 00:01:17.469 --> 00:01:17.709 Scott Berry: Yeah. 00:01:17.719 --> 00:01:21.349 So, so, so this is a great source of, we, we are celebrating Barry 00:01:21.349 --> 00:01:23.749 Consultants 25th anniversary this year. 00:01:24.059 --> 00:01:27.209 Uh, we're, we're marketing this and you can see this everywhere, 00:01:27.649 --> 00:01:31.669 but we've been working with Mike Krams for well over 25 years. 00:01:32.029 --> 00:01:37.759 Um, so I, I'd love to hear a little bit about, and I know much of this, but tell 00:01:37.759 --> 00:01:42.019 us about the Aston Stroke trial, which was your first interaction with Don Barry. 00:01:42.294 --> 00:01:47.014 Mike Krams: Yes, I was trained as a neurologist and a stroke neurologist. 00:01:47.454 --> 00:01:51.274 Um, you know, we, uh, worked in one of the first stroke units in 00:01:51.284 --> 00:01:57.044 Germany, uh, before I went to London to do, um, functional brain imaging. 00:01:57.484 --> 00:02:01.694 And in that functional brain imaging environment, I learned a lot about being 00:02:01.694 --> 00:02:07.034 clever on how to detect a weak signal in functional MRI and PET studies, a 00:02:07.034 --> 00:02:09.044 weak signal in a noisy environment. 00:02:09.114 --> 00:02:10.584 I learned a lot of statistics. 00:02:10.994 --> 00:02:14.894 And then I joined a pharmaceutical R& D, uh, organization. 00:02:15.274 --> 00:02:18.434 Um, they were looking for a stroke neurologist with a background 00:02:18.464 --> 00:02:22.524 in functional brain imaging, interested in developing acute 00:02:22.594 --> 00:02:24.804 ischemic neuroprotectins for stroke. 00:02:25.184 --> 00:02:27.354 And so I was made for the job. 00:02:28.039 --> 00:02:32.519 And then I looked at what was already happening in that area. 00:02:32.519 --> 00:02:36.409 And there were plenty of efforts to create new treatments for 00:02:36.439 --> 00:02:37.979 acute ischemic stroke patients. 00:02:38.429 --> 00:02:40.759 And one failed after the other. 00:02:41.369 --> 00:02:46.469 And, you know, when I, when I started in my career in pharma R& D, I just 00:02:46.479 --> 00:02:50.409 came from the Institute of Neurology Functional Brain Imaging Unit. 00:02:50.919 --> 00:02:56.259 Um, you know, the sophistication of the, um, of the functional brain 00:02:56.259 --> 00:03:02.179 imaging, experimental design and analysis world contrasted with a 00:03:02.179 --> 00:03:08.489 world in those days where you spend millions of dollars into having two 00:03:08.489 --> 00:03:10.749 groups and doing a t test at the end. 00:03:11.079 --> 00:03:12.729 And it was just mind boggling. 00:03:13.339 --> 00:03:18.409 And it also was pretty clear that identifying the correct dose and 00:03:18.419 --> 00:03:24.169 treatment regimen was a big, big issue when people went from phase 2 to phase 3. 00:03:24.969 --> 00:03:29.699 And so, I tried to figure out, you know, if that's the problem, if we are not 00:03:29.709 --> 00:03:33.679 very good in learning about the correct dose and treatment regimen to take into 00:03:33.689 --> 00:03:36.429 confirmative trials, what needs to change? 00:03:36.839 --> 00:03:37.199 And that 00:03:37.289 --> 00:03:39.069 Scott Berry: so let's, let's set this up a little bit. 00:03:39.239 --> 00:03:43.789 So you've got a, you've got a potential neuro protectant for acute stroke. 00:03:44.589 --> 00:03:51.099 You go to a traditional, uh, trial design invariably your statistician is going 00:03:51.099 --> 00:03:53.479 to say three doses, 80 patients a dose, 00:03:53.924 --> 00:03:55.754 Mike Krams: Uh, maybe more 00:03:55.969 --> 00:03:56.369 Scott Berry: two. 00:03:56.894 --> 00:04:01.694 Mike Krams: yes, but, but yes, it's, it's, it's like, uh, two or three, uh, 00:04:01.764 --> 00:04:08.174 active, uh, treatment arms and a control and pairwise comparisons and that's it. 00:04:08.944 --> 00:04:16.634 And, uh, you know, just mind boggling, uh, um, how, um, how, how one can do that 00:04:16.674 --> 00:04:18.914 and not think about, uh, alternatives. 00:04:19.304 --> 00:04:23.594 And so I, Uh, started educating myself about what else one 00:04:23.594 --> 00:04:24.614 could do when I came about. 00:04:25.609 --> 00:04:31.439 There were a number of papers that were really well written and the author was 00:04:31.439 --> 00:04:37.169 this professor whom I imagined with a long beard and probably would never talk to me. 00:04:37.799 --> 00:04:39.859 And the name was Professor Don Barry. 00:04:40.199 --> 00:04:45.079 Anyhow, I eventually found the courage to write him a letter 00:04:45.079 --> 00:04:48.594 and say, hey, I'm really I'm very impressed with your, uh, papers. 00:04:48.594 --> 00:04:52.964 There's this one paper about Bayesian thinking in clinical research and, 00:04:53.004 --> 00:04:57.474 you know, it totally resonates with me because as a medic, that's how I function. 00:04:57.804 --> 00:05:01.584 What you describe as the Bayesian thinking, that's, that's how, how, 00:05:01.604 --> 00:05:03.874 how you work, uh, in medicine. 00:05:04.454 --> 00:05:09.624 And so, hey, can we meet and can you perhaps, uh, uh, discuss with us, um, 00:05:09.634 --> 00:05:14.974 what one could do to approach this, uh, problem, namely, uh, identifying 00:05:14.984 --> 00:05:16.594 the correct dose in a different manner. 00:05:17.154 --> 00:05:18.434 And so that's how it all started. 00:05:19.054 --> 00:05:25.824 And then, uh, you know, we had, uh, just an amazing time, uh, exploring 00:05:25.864 --> 00:05:31.294 the opportunity space for what could be done with fantastic colleagues in 00:05:31.294 --> 00:05:38.904 the team and Don, of course, and others Peter Muller and many others Andy Greve, 00:05:39.004 --> 00:05:47.129 key person and, you know, over many months we were able to Effectively, 00:05:47.179 --> 00:05:52.039 in those days, not exactly invent, but really apply for one of the first times 00:05:52.279 --> 00:05:55.379 simulation guided clinical trial design. 00:05:57.119 --> 00:06:02.359 And, uh, you know, that the, the explanation that we gave, uh, to our 00:06:02.379 --> 00:06:06.139 senior managers was look, the way we currently work is we build an airport. 00:06:06.929 --> 00:06:08.799 Um, we then build a plane. 00:06:08.919 --> 00:06:12.419 We put peasant passengers on a plane that's never been flown before. 00:06:13.494 --> 00:06:17.184 As the plane is traveling, we build another airport where it'll 00:06:17.184 --> 00:06:21.044 land, and then it'll land, and by that time, we'll have destroyed 00:06:21.044 --> 00:06:22.584 the airport from where we started. 00:06:22.874 --> 00:06:24.854 And then we do this over and over again. 00:06:25.364 --> 00:06:26.964 And that's how we do clinical research. 00:06:27.034 --> 00:06:28.524 How can we do things differently? 00:06:29.254 --> 00:06:33.034 And, uh, you know, with Don's help, and Andy Reeve's help, 00:06:33.034 --> 00:06:33.944 and other people's help. 00:06:34.449 --> 00:06:41.209 Um, we eventually came up with, uh, design that's published and well presented. 00:06:41.819 --> 00:06:47.169 Um, where we had, believe it or not, 16, uh, different treatment arms. 00:06:47.679 --> 00:06:52.589 And what is called a response adaptive allocation to treatments. 00:06:53.129 --> 00:06:58.889 Uh, uh, uh, responding to the data, uh, on, uh, stroke 00:06:58.889 --> 00:07:00.019 scores coming in in real time. 00:07:00.019 --> 00:07:01.009 So that's how it started. 00:07:01.009 --> 00:07:03.114 Nope. 00:07:03.624 --> 00:07:07.694 Scott Berry: uh, interestingly that the time it took to do 00:07:07.694 --> 00:07:09.184 those simulations and build this. 00:07:09.184 --> 00:07:12.464 This is a time where software is not available. 00:07:12.464 --> 00:07:14.014 You're custom coding. 00:07:14.284 --> 00:07:18.454 This is many months to carry out these simulations. 00:07:18.999 --> 00:07:24.719 But even today that trial 16 doses response adaptive randomization the result 00:07:24.719 --> 00:07:29.349 of that trial Which has been published was a resounding success in that it 00:07:29.359 --> 00:07:31.449 demonstrated clearly the drug didn't work 00:07:31.804 --> 00:07:32.234 Mike Krams: it did. 00:07:32.764 --> 00:07:38.124 And it did so, there was a futility rule built in, and so it stopped 00:07:38.204 --> 00:07:41.814 early for, um, for, for futility. 00:07:42.144 --> 00:07:45.234 And so the design did what it was supposed to do, yes. 00:07:45.924 --> 00:07:50.544 And, but you mentioned, uh, the time that it took in those days to 00:07:50.864 --> 00:07:59.839 fine tune the, uh, Uh, the software that was, uh, handmade, uh, custom 00:07:59.839 --> 00:08:02.229 built really to, uh, support this. 00:08:02.319 --> 00:08:05.799 And, you know, we were always angry when we had to wait another 00:08:05.869 --> 00:08:08.869 two or three weeks before the next iteration of software came in. 00:08:09.119 --> 00:08:13.139 Compare this to today, where you have, you know, software packages like facts 00:08:13.139 --> 00:08:17.069 or others, where on a push of a button, you can plug in stuff and immediately 00:08:17.229 --> 00:08:19.599 get a first sense of how things work. 00:08:20.039 --> 00:08:22.509 So, hey, that, but that's, that's how it started. 00:08:22.569 --> 00:08:22.769 Yep. 00:08:23.104 --> 00:08:23.364 Scott Berry: Yeah. 00:08:23.384 --> 00:08:23.584 Yeah. 00:08:23.584 --> 00:08:27.364 So, so we now have software that can do those simulations, 00:08:27.364 --> 00:08:28.954 can build trials like that. 00:08:29.504 --> 00:08:34.014 But in doing that, the hard part may not have been the simulations. 00:08:34.014 --> 00:08:36.484 The hard part may not have been the modeling, the response 00:08:36.484 --> 00:08:37.654 adaptive randomization. 00:08:37.834 --> 00:08:40.844 It helps when you have Peter Mueller, uh, you know, brilliant 00:08:40.844 --> 00:08:43.014 scientist, uh, doing all of that. 00:08:43.284 --> 00:08:46.974 So I, I want to talk a little bit about bringing change. 00:08:47.384 --> 00:08:53.334 You go into a place where it's typically fixed trial designs, enroll this, and come 00:08:53.334 --> 00:08:55.544 back and show me the data in three years. 00:08:55.844 --> 00:09:01.764 Now you're doing interim's monthly, weekly, response adaptive randomization. 00:09:02.064 --> 00:09:04.144 How do you bring change to this industry? 00:09:04.154 --> 00:09:07.254 Is it, you know, so that's what I'd like to talk about. 00:09:07.304 --> 00:09:08.124 You know, this, 00:09:08.354 --> 00:09:08.574 Mike Krams: sure. 00:09:08.694 --> 00:09:13.424 And let's, let's just talk in general terms rather than about one 00:09:13.424 --> 00:09:16.424 particular trial in one particular pharma R& D environment, because 00:09:16.444 --> 00:09:21.514 the general aspects hold true, uh, really, uh, wherever you look. 00:09:22.024 --> 00:09:30.334 Overall, Uh, our industry is extremely conservative and people haven't got 00:09:30.404 --> 00:09:36.504 a lot of, uh, encouragement to think out of the box and try things that 00:09:36.514 --> 00:09:42.284 might perhaps require additional interactions with health authorities, 00:09:42.284 --> 00:09:43.924 regulatory scientists, et cetera. 00:09:44.424 --> 00:09:47.144 So the going in position is everybody is. 00:09:47.534 --> 00:09:53.044 Uh, doing what was done before and, uh, is not that comfortable. 00:09:53.904 --> 00:10:00.674 Uh, proposing quite different approaches and the question, of course, is why do 00:10:00.694 --> 00:10:04.974 something different if what we are already doing is working, but it's not working. 00:10:05.344 --> 00:10:06.664 It's so inefficient. 00:10:06.934 --> 00:10:10.224 And so you are asking how to bring about change. 00:10:10.394 --> 00:10:16.704 Well, if you are in an environment that is utterly against it and from a top down 00:10:16.704 --> 00:10:21.634 perspective, you know, senior management will not allow you to, uh, explore. 00:10:22.079 --> 00:10:28.789 Uh, uh, innovative, um, uh, uh, approaches, it's very tough. 00:10:29.169 --> 00:10:35.149 So if you want to do this bottom up and you haven't got a champion in a, um, in 00:10:35.149 --> 00:10:40.159 a more senior position, it's, it's, you know, uh, my experience tells me I've been 00:10:40.159 --> 00:10:45.519 most successful in places where my boss and the boss of my boss were champions 00:10:45.759 --> 00:10:47.299 for the idea that we brought forward. 00:10:47.299 --> 00:10:49.809 So it's important to have champions. 00:10:51.784 --> 00:10:56.174 in senior positions to, to help you achieve this, but then what's 00:10:56.304 --> 00:11:01.204 equally important is to clearly articulate the value proposition. 00:11:02.174 --> 00:11:07.774 You don't do innovation for innovation's sake, but if there is a way of 00:11:07.774 --> 00:11:13.464 convincing the, environment that we work in, that there is a better 00:11:13.464 --> 00:11:18.704 decision to be made at an earlier time point in a more efficient manner. 00:11:19.164 --> 00:11:19.994 Now we're talking. 00:11:20.714 --> 00:11:27.944 And, being able to articulate, clearly understanding the position of the person 00:11:28.024 --> 00:11:34.634 at the other side of the table, and bringing along the audience, that's key. 00:11:35.764 --> 00:11:36.644 Let me give you some 00:11:36.849 --> 00:11:40.119 Scott Berry: So, so, so can I, can I talk about, I think this is so critical, 00:11:40.129 --> 00:11:46.549 so we, I, I, you've got experience of this, you know, in development programs, 00:11:46.599 --> 00:11:52.059 uh, much more top level than I, so I end up working a lot with teams and we 00:11:52.059 --> 00:11:54.989 explore adaptive designs in all of this. 00:11:55.579 --> 00:11:59.959 and in, in, even at that level, you've gotta create a champion that's 00:11:59.959 --> 00:12:02.929 gonna go up and fight, fight for it. 00:12:02.929 --> 00:12:05.269 First of all, you've gotta demonstrate to that person that 00:12:05.269 --> 00:12:06.349 what you're doing is better. 00:12:06.619 --> 00:12:07.819 They've gotta believe in it. 00:12:08.209 --> 00:12:13.399 But I've also found that you need that, uh, a little bit, that that person has 00:12:13.399 --> 00:12:15.469 ownership in that what you've created 00:12:15.524 --> 00:12:16.484 Mike Krams: Oh, absolutely. 00:12:16.699 --> 00:12:20.089 Scott Berry: so that when, when we're doing these sim and so. 00:12:21.189 --> 00:12:25.679 The name, the consultant, we don't go in and say you've got to do X 00:12:25.679 --> 00:12:27.429 and we're kind of beating them down. 00:12:27.789 --> 00:12:29.719 They're not a champion for you. 00:12:29.719 --> 00:12:31.029 They don't necessarily believe in it. 00:12:31.029 --> 00:12:32.899 They're not going to go and fight for this. 00:12:33.219 --> 00:12:36.849 But if you get them to believe what you're doing better, they made the decisions. 00:12:36.849 --> 00:12:40.149 You guided them and you showed them the ramifications. 00:12:40.369 --> 00:12:43.139 That's why clinical trial simulation is beautiful, by the way. 00:12:43.139 --> 00:12:44.809 You can see the ramifications of all that. 00:12:45.199 --> 00:12:46.699 They become the champion. 00:12:46.709 --> 00:12:49.029 They can go up and say here's why. 00:12:49.039 --> 00:12:49.849 And, and, and. 00:12:50.324 --> 00:12:53.314 If they're fighting for it, they're, they're champion at that level. 00:12:53.364 --> 00:12:55.824 And then what happens above that? 00:12:55.969 --> 00:13:00.579 Mike Krams: Yeah, well, you made it so clear that it can't be 00:13:00.579 --> 00:13:04.059 that an external party comes and says this is the way it's done. 00:13:04.359 --> 00:13:06.249 Drug development is a team sport. 00:13:06.639 --> 00:13:11.479 And the way I've experienced this with Don and you and others has been that 00:13:11.479 --> 00:13:18.139 you've empowered us to stand up with a proposal that you helped develop, but 00:13:18.139 --> 00:13:24.029 you really empower the team on point within the farm R and D organization. 00:13:24.399 --> 00:13:28.099 to then carry, uh, the flag and make the points. 00:13:28.529 --> 00:13:31.019 And, uh, what, what happens? 00:13:31.029 --> 00:13:35.789 So, so you need to, uh, think about who are the key decision makers. 00:13:36.089 --> 00:13:40.039 Initially, in, uh, uh, compound development teams, 00:13:40.039 --> 00:13:42.199 you have a, uh, team leader. 00:13:42.869 --> 00:13:49.814 Uh, you have, uh, a, uh, Uh, program or project manager, you have a therapeutic 00:13:49.814 --> 00:13:55.564 area head, you have, uh, functional heads, lots of people who have a say in this. 00:13:56.134 --> 00:14:02.034 And often what happens is that even though you may have been successful in 00:14:02.034 --> 00:14:08.524 bringing your own team, uh, around to, uh, embracing, uh, innovative idea, 00:14:09.004 --> 00:14:14.319 it's enough if just one person somewhere higher up says, Hey, I don't like this. 00:14:14.349 --> 00:14:16.449 This, this, this has never been seen before. 00:14:16.469 --> 00:14:18.169 I don't think that this will fly. 00:14:18.719 --> 00:14:20.249 That's enough to derail it. 00:14:20.729 --> 00:14:26.679 And then it's important, uh, not to give up, but to try to understand 00:14:26.759 --> 00:14:31.859 what is the motivation of that person to say, um, hey, it won't work. 00:14:32.589 --> 00:14:33.759 I'll give you an example. 00:14:34.369 --> 00:14:39.414 When, um, we implemented, um, response adaptive dose finding 00:14:39.414 --> 00:14:41.584 studies in a broader way. 00:14:42.204 --> 00:14:47.804 One of the arguments that we made were, um, it's of value to have 00:14:47.904 --> 00:14:50.044 more doses rather than less doses. 00:14:50.814 --> 00:14:55.734 Um, and, uh, the person who headed up the Pharmaceutical 00:14:55.734 --> 00:14:57.284 Sciences Organization at the time. 00:14:57.734 --> 00:15:02.414 They would have ultimately been accountable for making more dose 00:15:02.424 --> 00:15:07.454 strengths and enabling that whole many doses rather than a few. 00:15:07.934 --> 00:15:08.964 They hated this. 00:15:09.449 --> 00:15:11.019 They absolutely hated it. 00:15:11.479 --> 00:15:16.639 And then, you know, within learn trials, we proposed something that 00:15:16.859 --> 00:15:19.959 proved really, an amazing thing. 00:15:20.129 --> 00:15:25.729 We invited the head of the Pharmaceutical Sciences organization to be a silent 00:15:25.739 --> 00:15:28.989 observer in the data monitoring committee. 00:15:29.519 --> 00:15:39.089 So that person was now able to see firsthand how the information evolved over 00:15:39.089 --> 00:15:45.129 time and was sworn to secrecy, obviously, but in the back of their minds, they 00:15:45.129 --> 00:15:50.799 were clear on how the trajectory of a particular program was more likely to go. 00:15:51.189 --> 00:15:56.099 And of course, that might have implications on, bigger strategic 00:15:56.099 --> 00:16:00.149 thinking and some key decisions that might have been in that person's mind. 00:16:00.659 --> 00:16:07.269 So to understand where the resi the resistance comes from, taking that very 00:16:07.269 --> 00:16:12.280 seriously, but then also finding an opportunity to bring that person into 00:16:12.280 --> 00:16:17.203 a position where that person can also, support and champion what we're doing. 00:16:17.203 --> 00:16:17.859 And that. 00:16:18.309 --> 00:16:23.939 That function ultimately became a big supporter for us, because they understood 00:16:23.949 --> 00:16:29.059 that we were more frequently stopping things that shouldn't go forward, and 00:16:29.069 --> 00:16:32.159 bringing forward things that should go forward more, more, rapidly. 00:16:32.629 --> 00:16:32.999 Scott Berry: Yeah. 00:16:33.119 --> 00:16:33.509 Yeah. 00:16:33.749 --> 00:16:35.079 Uh, so a little bit. 00:16:35.089 --> 00:16:39.379 So the title of this, we've titled this the art and slog of innovation. 00:16:39.799 --> 00:16:44.069 And so a little bit of that seems like the slog that invariably when 00:16:44.069 --> 00:16:47.939 you're doing something different that there's, there's ways this has been 00:16:47.939 --> 00:16:51.169 done many times within a pharmaceutical company within the industry. 00:16:51.469 --> 00:16:54.969 And there's a lot of copycat doing what the last person did and all that. 00:16:55.229 --> 00:16:59.939 And now you're saying, proposing something different and invariably. 00:17:00.304 --> 00:17:06.414 10 people are going to give a reason not to as this goes from concept and 00:17:06.414 --> 00:17:11.314 development and all of these will stop it if you're not able to combat that 00:17:11.694 --> 00:17:15.824 with with information and bring those people along as well that you're not an 00:17:15.824 --> 00:17:17.974 enemy that we're making better decisions. 00:17:17.974 --> 00:17:23.824 That's a bit of the slog of this innovation aspect of it, uh, from it. 00:17:23.834 --> 00:17:26.584 That is just so hard to do it. 00:17:27.454 --> 00:17:30.924 Mike Krams: Well, you know, uh, it's actually hard work. 00:17:31.414 --> 00:17:36.084 And you need to be at the table where strategic decisions are made. 00:17:36.104 --> 00:17:41.104 If you're not there, if you're not present, uh, doing this Um, 00:17:41.104 --> 00:17:47.624 from a distant with only punctual interactions is much more difficult. 00:17:48.154 --> 00:17:54.344 Um, so being embedded in discussions that lead to better problem solving, 00:17:54.804 --> 00:18:01.314 that lead to, uh, creating, uh, resource efficiencies and ultimately that lead to 00:18:01.314 --> 00:18:05.134 creating a new fun intellectual culture. 00:18:05.354 --> 00:18:06.434 That's a key thing. 00:18:07.094 --> 00:18:09.544 Uh, you know, is incredibly rewarding. 00:18:09.544 --> 00:18:13.764 But you have to be part of the inner discussion where the 00:18:13.774 --> 00:18:16.354 strategic direction is being set. 00:18:16.714 --> 00:18:21.734 That's why it's so important not just to look at an individual trial in isolation, 00:18:22.144 --> 00:18:24.394 but at the development strategy overall. 00:18:24.544 --> 00:18:25.484 And then think. 00:18:25.789 --> 00:18:31.579 Within that bigger picture, how do we, um, uh, design the, uh, strategy? 00:18:32.359 --> 00:18:34.219 Scott Berry: yeah, it's it's so interesting. 00:18:34.219 --> 00:18:35.219 So part of this is. 00:18:35.849 --> 00:18:36.579 You hear this. 00:18:36.609 --> 00:18:37.799 You need to be at the table. 00:18:37.799 --> 00:18:39.409 The question is, how do you get to the table? 00:18:40.179 --> 00:18:43.249 You can't just blurt out, I need to be at the table. 00:18:43.609 --> 00:18:44.759 That generally doesn't work. 00:18:45.119 --> 00:18:49.249 And in our circumstances, as a statistician, we may have a number of 00:18:49.259 --> 00:18:54.279 statisticians joining this, we have scenarios where, you know, a client 00:18:54.279 --> 00:18:56.049 may say, can you show us the power? 00:18:56.049 --> 00:18:57.499 Can you show us this, this, and this? 00:18:57.969 --> 00:19:00.649 How you present this is so critical. 00:19:00.649 --> 00:19:04.669 And if you pass this to somebody else who then brings it up there, and they're 00:19:04.679 --> 00:19:06.809 bringing They present it differently. 00:19:06.809 --> 00:19:10.989 They answer questions differently, and it's so much the ability to 00:19:10.989 --> 00:19:15.259 see how people react to this and what is what do they need to see? 00:19:15.259 --> 00:19:16.609 Is it about time? 00:19:16.609 --> 00:19:17.949 Is it about cost? 00:19:18.229 --> 00:19:21.569 Is it about another development program that they want to 00:19:21.579 --> 00:19:22.889 take these additional shots? 00:19:23.209 --> 00:19:26.409 So being able to listen and hear all of this? 00:19:26.584 --> 00:19:31.084 And then be able to present exactly what's going to help them make that decision 00:19:31.324 --> 00:19:33.494 is the really hard part about this. 00:19:33.524 --> 00:19:38.024 And it's earning your way at the table that people think you help them and 00:19:38.184 --> 00:19:41.684 you're presenting the right thing and you understand the bigger part. 00:19:41.954 --> 00:19:44.114 That's what's harder for us as statisticians. 00:19:44.114 --> 00:19:48.184 We're really good at calculating something, but this is the hard 00:19:48.184 --> 00:19:50.344 part to earn your way to the table. 00:19:51.054 --> 00:19:51.524 Mike Krams: True. 00:19:51.904 --> 00:19:56.404 Respect is earned, but I tell you, uh, I have had the privilege to work with so 00:19:56.404 --> 00:20:02.434 many, statistical experts and modeling experts and mathematicians who are 00:20:02.654 --> 00:20:09.634 absolutely brilliant in articulating clearly in a way that the other, function 00:20:09.634 --> 00:20:15.074 that might not be, mathematically inclined still understands, and that 00:20:15.154 --> 00:20:18.204 is a necessary condition for it. 00:20:18.644 --> 00:20:22.814 Getting, the implementation of innovation guaranteed. 00:20:22.814 --> 00:20:28.244 So very good communication skills, but as you pointed out, also very good listening 00:20:28.244 --> 00:20:33.854 skills and psychological skills, where does the other party come from, but, 00:20:34.134 --> 00:20:40.924 there is also a need for putting your foot down and, making sure that, others 00:20:40.924 --> 00:20:47.144 understand what statistical experts do is a contribution to strategic thinking. 00:20:47.774 --> 00:20:52.144 It's not just a subservient number crunching activity in 00:20:52.144 --> 00:20:53.834 the background, absolutely not. 00:20:54.364 --> 00:21:02.974 And insisting that there be that, partnership, between clinical experts, 00:21:03.084 --> 00:21:07.764 translational science experts, regulators, and statistical and 00:21:07.814 --> 00:21:11.114 others, experts, is, very important. 00:21:11.114 --> 00:21:15.219 Yeah. 00:21:15.319 --> 00:21:17.669 Scott Berry: my, my words I associate with you and you say 00:21:17.669 --> 00:21:19.199 this all the time is imagine. 00:21:19.769 --> 00:21:23.219 Um, so, so let me, uh, you know, imagine if we could do the following. 00:21:23.994 --> 00:21:31.254 We started this off with, uh, 1990s, a neuroprotectant for acute stroke. 00:21:31.674 --> 00:21:34.164 We are now 2025. 00:21:34.164 --> 00:21:36.804 We have no neuroprotectant for acute stroke. 00:21:37.074 --> 00:21:38.874 We have thrombolytics. 00:21:38.904 --> 00:21:40.764 We have endovascular therapy. 00:21:40.764 --> 00:21:43.284 That, by the way, is incredibly effective in some patients. 00:21:43.734 --> 00:21:48.114 We're still in search for neuroprotectant, uh, in stroke. 00:21:48.989 --> 00:21:52.139 Imagine if development would have been different. 00:21:52.219 --> 00:21:56.629 Are there neuroprotectants that we missed, that we didn't take shots on goals? 00:21:56.789 --> 00:21:58.199 We got the wrong dose. 00:21:58.389 --> 00:22:01.499 Now, we're, we're, we're, we as an industry, we're 00:22:01.499 --> 00:22:03.279 developing really cool things. 00:22:03.609 --> 00:22:07.479 They're out there, but this is a really hard area where in some ways 00:22:07.479 --> 00:22:09.549 we haven't made tremendous progress. 00:22:09.929 --> 00:22:12.339 And does the development affect that? 00:22:12.569 --> 00:22:12.899 Mike Krams: Yes. 00:22:13.049 --> 00:22:16.529 So, hey, uh, this is so close to my heart, but it's not 00:22:16.529 --> 00:22:18.279 just in acute ischemic stroke. 00:22:18.279 --> 00:22:21.969 It's in any, uh, important, uh, disease where there aren't solutions. 00:22:22.519 --> 00:22:28.399 Uh, you gave a talk once about statistics and baseball, and it inspired me. 00:22:28.469 --> 00:22:35.279 And in it was, uh, The motion of the time machine to be able to compare 00:22:35.669 --> 00:22:40.949 the thing that happened in the past and move seamlessly to the presence 00:22:41.409 --> 00:22:43.319 and, and build models around that. 00:22:43.759 --> 00:22:48.749 And then I heard your dad, uh, Don Barry, uh, talk about platform trials 00:22:49.229 --> 00:22:53.549 and, you know, I've worked in different companies on individual projects. 00:22:54.474 --> 00:22:56.734 observing what the competition did. 00:22:57.264 --> 00:23:04.694 And it really, at times, drove me nuts how mistakes were reinvented without 00:23:04.734 --> 00:23:07.604 comparing notes and working together. 00:23:07.634 --> 00:23:14.414 Now Imagine that at the center of the universe was not, an 00:23:14.414 --> 00:23:19.164 individual, investigational compound, but the need of the patient. 00:23:19.804 --> 00:23:24.794 And imagine that everybody was very keen to get to the right 00:23:24.794 --> 00:23:26.384 solution at the earliest time point. 00:23:26.734 --> 00:23:30.814 Of course, one would think about how to bring things together. 00:23:31.184 --> 00:23:36.004 And what I love to imagine are these integrated research platforms, where 00:23:36.014 --> 00:23:43.014 on one hand, on an ongoing basis, You captivate all learnings on how to observe 00:23:43.054 --> 00:23:46.014 patients in methodology like studies. 00:23:46.054 --> 00:23:50.094 But then you build on top of that the exploration of new 00:23:50.104 --> 00:23:51.744 pharmacological entities. 00:23:51.844 --> 00:23:56.524 A little bit as is done in platform trials such as iSpy2 or the many others 00:23:56.534 --> 00:23:59.054 that have been developed by you guys. 00:23:59.474 --> 00:24:02.049 And so I feel So, that is the future. 00:24:02.609 --> 00:24:07.289 And, uh, there are some, uh, questions on how to achieve that. 00:24:07.649 --> 00:24:10.379 Um, but, hey, uh, that's where we need to go. 00:24:10.379 --> 00:24:11.809 Yeah. 00:24:11.954 --> 00:24:17.424 Scott Berry: to put in a plug for the STEP platform trial, NIH funded, NINDS 00:24:17.434 --> 00:24:19.694 funded that's trying to do exactly this. 00:24:19.924 --> 00:24:25.304 Not rebuilding the airplane, airport every time, uh, you know, so this, this is a 00:24:25.304 --> 00:24:29.914 fantastic effort and we're seeing much more of this, uh, in platform trials. 00:24:29.914 --> 00:24:33.584 So, uh, but I'll come back to the sports things and, you know, I almost. 00:24:33.649 --> 00:24:37.099 I interpret things in sports. 00:24:37.099 --> 00:24:40.029 I go back to this and a lot of this is very similar. 00:24:40.029 --> 00:24:44.639 So, so baseball for years, uh, nobody would do anything different. 00:24:44.639 --> 00:24:48.329 The manager, if you did what everybody else did and the team 00:24:48.329 --> 00:24:50.079 lost, it was the player's fault. 00:24:50.984 --> 00:24:54.274 If you do something innovative and you lose, it's your fault. 00:24:54.584 --> 00:24:56.614 If you did something against the grain and all that. 00:24:57.094 --> 00:24:58.974 Uh, and it's the same in drug development. 00:24:58.974 --> 00:25:02.934 If you do what everybody else did, it's the drug's fault. 00:25:02.934 --> 00:25:05.104 But if you do something innovative, maybe it was my fault. 00:25:05.124 --> 00:25:06.484 Maybe I did it wrong and all that. 00:25:06.764 --> 00:25:10.014 The fascinating thing, of course, in baseball is analytics has 00:25:10.014 --> 00:25:11.214 completely changed the game. 00:25:11.619 --> 00:25:15.339 And in 15 years, the way the game is played, the way it's 00:25:15.339 --> 00:25:17.449 set up, is entirely different. 00:25:17.759 --> 00:25:21.589 So, innovation completely changed it, but it's also done that in drug development. 00:25:22.069 --> 00:25:25.419 Platform trials, adaptive designs in 15 years. 00:25:25.729 --> 00:25:30.279 Now, if you don't do these things, maybe they'll say, Why weren't you doing that? 00:25:30.279 --> 00:25:31.229 Why weren't you doing that? 00:25:31.529 --> 00:25:32.919 And maybe it's a similar thing. 00:25:33.179 --> 00:25:33.969 Mike Krams: you're absolutely right. 00:25:33.969 --> 00:25:35.569 We've come a very long way. 00:25:36.339 --> 00:25:41.739 And what is so amazing, and that is something that statistical experts 00:25:41.739 --> 00:25:48.329 can take a lead in, is the power of simulations to be used as a 00:25:48.349 --> 00:25:52.739 tool to bringing people around the table and then playing ping pong 00:25:52.749 --> 00:25:54.439 with arguments and saying, Hey, if. 00:25:54.959 --> 00:26:00.599 What if, and then you try that out and, uh, and I think the, there's a lot 00:26:00.599 --> 00:26:03.769 of openness to, uh, to, uh, innovate. 00:26:04.669 --> 00:26:08.229 I want to say this also with experts in regulatory science. 00:26:08.589 --> 00:26:10.749 You know, a lot of people say, Oh, regulators don't like it. 00:26:10.809 --> 00:26:12.339 It's absolutely not my experience. 00:26:12.619 --> 00:26:16.489 My experience is that there have been so incredible interactions with 00:26:16.489 --> 00:26:20.849 health authorities that have helped shape on how to go about innovating. 00:26:22.334 --> 00:26:24.404 Scott Berry: Yeah, no, I agree completely. 00:26:24.684 --> 00:26:27.804 And people don't see 10 trials done like this. 00:26:27.814 --> 00:26:31.534 It's not because agencies said you can't do that, but 00:26:31.544 --> 00:26:32.744 they're not being brought that. 00:26:32.754 --> 00:26:37.794 So I think regulators have have played a huge part, actually, in a lot of the 00:26:37.794 --> 00:26:40.304 innovations that's happened in this. 00:26:40.364 --> 00:26:40.514 Yep. 00:26:40.794 --> 00:26:42.674 But that's that's part of it again. 00:26:43.164 --> 00:26:47.044 The slog part of it that when you present this, well, regulators 00:26:47.044 --> 00:26:47.714 aren't going to like this. 00:26:47.724 --> 00:26:51.444 Well, drug develop, uh, drug supply is not going to like this. 00:26:51.444 --> 00:26:54.394 Well, CRO is not going to like this, you know, and that's a bit 00:26:54.394 --> 00:26:58.684 of the slog of, uh, and the hard work in doing something different. 00:26:58.904 --> 00:26:59.584 Mike Krams: yep, yep. 00:27:00.064 --> 00:27:03.564 You know, there's the saying, culture eats strategy for lunch. 00:27:03.844 --> 00:27:09.784 But if you, uh, make it a culture to have fun because you are intellectually 00:27:09.794 --> 00:27:14.634 challenging each other, and it's not innovation for innovation's sake, but 00:27:14.634 --> 00:27:19.264 it's simply the question, what's the best thing in the name of future patients? 00:27:19.724 --> 00:27:21.014 Then everything else will follow. 00:27:21.764 --> 00:27:22.574 Scott Berry: Yeah, yeah. 00:27:22.574 --> 00:27:23.324 Fantastic. 00:27:23.374 --> 00:27:24.084 Fantastic. 00:27:24.304 --> 00:27:26.484 Well, boy, this has been been wonderful. 00:27:26.714 --> 00:27:32.174 I'm incredibly excited as as we move forward and part of Berry Consultants, 00:27:32.174 --> 00:27:36.004 but it's an incredible look at innovation, the art, and the slog. 00:27:36.004 --> 00:27:37.484 Appreciate it very much, Mike. 00:27:37.534 --> 00:27:38.354 Mike Krams: Hey, thank you. 00:27:38.874 --> 00:27:39.194 Scott Berry: Yeah. 00:27:39.634 --> 00:27:40.154 Awesome. 00:27:40.214 --> 00:27:40.834 Thanks.