The Art and Slog of Innovating

Uh, Mike Krams is our guest today and for everybody's Uh, knowledge, he joined Berry Consultants in January, but Mike has a, a really interesting history in clinical trials, drug development, he's been 30 years at multiple pharmaceutical companies, he's led quantitative sciences departments at these, uh, he's done innovation everywhere he's been, and now we're thrilled to have him at Berry, but we talk about innovation, how do we do innovation at in, in drug development.

So Mike, welcome to In the Interim.

Um, they were looking for a stroke neurologist with a background in functional brain imaging, interested in developing acute ischemic neuroprotectins for stroke. And so I was made for the job. And then I looked at what was already happening in that area. And there were plenty of efforts to create new treatments for acute ischemic stroke patients. And one failed after the other.

And, you know, when I, when I started in my career in pharma R& D, I just came from the Institute of Neurology Functional Brain Imaging Unit. Um, you know, the sophistication of the, um, of the functional brain imaging, experimental design and analysis world contrasted with a world in those days where you spend millions of dollars into having two groups and doing a t test at the end. And it was just mind boggling.

And it also was pretty clear that identifying the correct dose and treatment regimen was a big, big issue when people went from phase 2 to phase 3. And so, I tried to figure out, you know, if that's the problem, if we are not very good in learning about the correct dose and treatment regimen to take into confirmative trials, what needs to change? And that

There were a number of papers that were really well written and the author was this professor whom I imagined with a long beard and probably would never talk to me. And the name was Professor Don Barry. Anyhow, I eventually found the courage to write him a letter and say, hey, I'm really I'm very impressed with your, uh, papers. There's this one paper about Bayesian thinking in clinical research and, you know, it totally resonates with me because as a medic, that's how I function.

What you describe as the Bayesian thinking, that's, that's how, how, how you work, uh, in medicine. And so, hey, can we meet and can you perhaps, uh, uh, discuss with us, um, what one could do to approach this, uh, problem, namely, uh, identifying the correct dose in a different manner. And so that's how it all started.

And then, uh, you know, we had, uh, just an amazing time, uh, exploring the opportunity space for what could be done with fantastic colleagues in the team and Don, of course, and others Peter Muller and many others Andy Greve, key person and, you know, over many months we were able to Effectively, in those days, not exactly invent, but really apply for one of the first times simulation guided clinical trial design.

And, uh, you know, that the, the explanation that we gave, uh, to our senior managers was look, the way we currently work is we build an airport. Um, we then build a plane. We put peasant passengers on a plane that's never been flown before. As the plane is traveling, we build another airport where it'll land, and then it'll land, and by that time, we'll have destroyed the airport from where we started. And then we do this over and over again. And that's how we do clinical research.

How can we do things differently? And, uh, you know, with Don's help, and Andy Reeve's help, and other people's help. Um, we eventually came up with, uh, design that's published and well presented. Um, where we had, believe it or not, 16, uh, different treatment arms. And what is called a response adaptive allocation to treatments. Uh, uh, uh, responding to the data, uh, on, uh, stroke scores coming in in real time. So that's how it started. Nope.

Compare this to today, where you have, you know, software packages like facts or others, where on a push of a button, you can plug in stuff and immediately get a first sense of how things work. So, hey, that, but that's, that's how it started. Yep.

You go into a place where it's typically fixed trial designs, enroll this, and come back and show me the data in three years. Now you're doing interim's monthly, weekly, response adaptive randomization. How do you bring change to this industry? Is it, you know, so that's what I'd like to talk about. You know, this,

So the going in position is everybody is. Uh, doing what was done before and, uh, is not that comfortable. Uh, proposing quite different approaches and the question, of course, is why do something different if what we are already doing is working, but it's not working. It's so inefficient. And so you are asking how to bring about change. Well, if you are in an environment that is utterly against it and from a top down perspective, you know, senior management will not allow you to, uh, explore.

Uh, uh, innovative, um, uh, uh, approaches, it's very tough. So if you want to do this bottom up and you haven't got a champion in a, um, in a more senior position, it's, it's, you know, uh, my experience tells me I've been most successful in places where my boss and the boss of my boss were champions for the idea that we brought forward. So it's important to have champions.

in senior positions to, to help you achieve this, but then what's equally important is to clearly articulate the value proposition. You don't do innovation for innovation's sake, but if there is a way of convincing the, environment that we work in, that there is a better decision to be made at an earlier time point in a more efficient manner. Now we're talking.

And, being able to articulate, clearly understanding the position of the person at the other side of the table, and bringing along the audience, that's key. Let me give you some

But I've also found that you need that, uh, a little bit, that that person has ownership in that what you've created

You can see the ramifications of all that. They become the champion. They can go up and say here's why. And, and, and. If they're fighting for it, they're, they're champion at that level. And then what happens above that?

So, so you need to, uh, think about who are the key decision makers. Initially, in, uh, uh, compound development teams, you have a, uh, team leader. Uh, you have, uh, a, uh, Uh, program or project manager, you have a therapeutic area head, you have, uh, functional heads, lots of people who have a say in this.

And often what happens is that even though you may have been successful in bringing your own team, uh, around to, uh, embracing, uh, innovative idea, it's enough if just one person somewhere higher up says, Hey, I don't like this. This, this, this has never been seen before. I don't think that this will fly. That's enough to derail it. And then it's important, uh, not to give up, but to try to understand what is the motivation of that person to say, um, hey, it won't work.

I'll give you an example. When, um, we implemented, um, response adaptive dose finding studies in a broader way. One of the arguments that we made were, um, it's of value to have more doses rather than less doses. Um, and, uh, the person who headed up the Pharmaceutical Sciences Organization at the time. They would have ultimately been accountable for making more dose strengths and enabling that whole many doses rather than a few. They hated this. They absolutely hated it.

And then, you know, within learn trials, we proposed something that proved really, an amazing thing. We invited the head of the Pharmaceutical Sciences organization to be a silent observer in the data monitoring committee. So that person was now able to see firsthand how the information evolved over time and was sworn to secrecy, obviously, but in the back of their minds, they were clear on how the trajectory of a particular program was more likely to go.

And of course, that might have implications on, bigger strategic thinking and some key decisions that might have been in that person's mind. So to understand where the resi the resistance comes from, taking that very seriously, but then also finding an opportunity to bring that person into a position where that person can also, support and champion what we're doing. And that.

That function ultimately became a big supporter for us, because they understood that we were more frequently stopping things that shouldn't go forward, and bringing forward things that should go forward more, more, rapidly.

10 people are going to give a reason not to as this goes from concept and development and all of these will stop it if you're not able to combat that with with information and bring those people along as well that you're not an enemy that we're making better decisions. That's a bit of the slog of this innovation aspect of it, uh, from it. That is just so hard to do it.

Uh, you know, is incredibly rewarding. But you have to be part of the inner discussion where the strategic direction is being set. That's why it's so important not just to look at an individual trial in isolation, but at the development strategy overall. And then think. Within that bigger picture, how do we, um, uh, design the, uh, strategy?

And if you pass this to somebody else who then brings it up there, and they're bringing They present it differently. They answer questions differently, and it's so much the ability to see how people react to this and what is what do they need to see? Is it about time? Is it about cost? Is it about another development program that they want to take these additional shots? So being able to listen and hear all of this?

And then be able to present exactly what's going to help them make that decision is the really hard part about this. And it's earning your way at the table that people think you help them and you're presenting the right thing and you understand the bigger part. That's what's harder for us as statisticians. We're really good at calculating something, but this is the hard part to earn your way to the table.

So very good communication skills, but as you pointed out, also very good listening skills and psychological skills, where does the other party come from, but, there is also a need for putting your foot down and, making sure that, others understand what statistical experts do is a contribution to strategic thinking. It's not just a subservient number crunching activity in the background, absolutely not.

And insisting that there be that, partnership, between clinical experts, translational science experts, regulators, and statistical and others, experts, is, very important. Yeah.

Imagine if development would have been different. Are there neuroprotectants that we missed, that we didn't take shots on goals? We got the wrong dose. Now, we're, we're, we're, we as an industry, we're developing really cool things. They're out there, but this is a really hard area where in some ways we haven't made tremendous progress. And does the development affect that?

And then I heard your dad, uh, Don Barry, uh, talk about platform trials and, you know, I've worked in different companies on individual projects. observing what the competition did. And it really, at times, drove me nuts how mistakes were reinvented without comparing notes and working together. Now Imagine that at the center of the universe was not, an individual, investigational compound, but the need of the patient.

And imagine that everybody was very keen to get to the right solution at the earliest time point. Of course, one would think about how to bring things together. And what I love to imagine are these integrated research platforms, where on one hand, on an ongoing basis, You captivate all learnings on how to observe patients in methodology like studies. But then you build on top of that the exploration of new pharmacological entities.

A little bit as is done in platform trials such as iSpy2 or the many others that have been developed by you guys. And so I feel So, that is the future. And, uh, there are some, uh, questions on how to achieve that. Um, but, hey, uh, that's where we need to go. Yeah.

The manager, if you did what everybody else did and the team lost, it was the player's fault. If you do something innovative and you lose, it's your fault. If you did something against the grain and all that. Uh, and it's the same in drug development. If you do what everybody else did, it's the drug's fault. But if you do something innovative, maybe it was my fault. Maybe I did it wrong and all that. The fascinating thing, of course, in baseball is analytics has completely changed the game.

And in 15 years, the way the game is played, the way it's set up, is entirely different. So, innovation completely changed it, but it's also done that in drug development. Platform trials, adaptive designs in 15 years. Now, if you don't do these things, maybe they'll say, Why weren't you doing that? Why weren't you doing that? And maybe it's a similar thing.

You know, a lot of people say, Oh, regulators don't like it. It's absolutely not my experience. My experience is that there have been so incredible interactions with health authorities that have helped shape on how to go about innovating.

Well, CRO is not going to like this, you know, and that's a bit of the slog of, uh, and the hard work in doing something different.