Episode 109: How Collaboration is Transforming Biotech and Drug Development – Inside the Critical Path Institute

In this episode, we're exploring the 4 C's of drug development: collaboration, cures, coffee, and the Critical Path Institute. You're listening to Bio from the Bayou, empowering biotech leaders with the tools, assets, and expertise to improve healthcare outcomes.

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Serving the entire Gulf South, but recorded in the heart of New Orleans. Welcome back to Bio from the Bayou. I'm your host, Dr. Elaine Hamm, the executive in residence at Tulane School of Medicine. And today's guest with me is Dr. Klaus Romero. He is the chief executive officer and chief science officer at the Critical Path Institute, otherwise known as CPATH. And I'm so thrilled to have you on the show today, Klaus.

Thanks, Elaine. I'm excited to be here.

Well, let's talk about CPATH, which, if you're in drug development and you don't know about Critical Path, get it together. You need to understand exactly all the things that Critical Path has been doing for now 20 years. You guys just celebrated your 20th anniversary in DC a couple of weeks ago. So, can you briefly explain the history of the organization and really how it's evolved over the last 2 decades now?

Yeah, I'm happy to. So, the history is also in the name. So, the Critical Path Institute was established in 2005. In direct response to the transformative and visionary white paper from FDA from a year prior, 2004, called the Critical Path Initiative. And that document was pretty transformational because the FDA came out to the world and said, hey, everyone, we have the mission to regulate the products. Companies have the mission to develop the products. Whose mission is it to make the process efficient for everyone?

Yeah.

It can't be just all FDA. It can't be individual companies on their own. So why don't we set up public-private partnerships to work together on fixing the process in an efficient way by removing bottlenecks so that all the boats rise?

Yeah.

And the process can be efficient for everyone. That's in essence what we do. We coordinate public-private partnerships that focus on removing bottlenecks through science and solid evidence so that the process can be more efficient and the time can be shorter, the certainty can be higher, and the whole process can be de-risked.

Incredibly important mission. And you guys have, have added additional programs. I know one of the ways that I've engaged with critical path is through some of the grant programs that you have. And it's— I sit on the grant review process, and it's really, one, it's a lot of fun because you get to see all of the great science that's up and coming. And when did that process start as well?

So 2 things.

Yes.

That program called the Translational Therapeutic Accelerator is one of the newer ones for us. And it's one of the exceptional ones. Let me take a step back and just describe the normal ones, so to speak, and then I'll describe Traxxa. So the public-private partnerships that we typically coordinate take 3 flavors. One flavor, indication or drug development area specific, but solution agnostic.

Yep.

Example, Alzheimer's disease, Parkinson's, type 1 diabetes, polycystic kidney disease. We take on the indication. We identify the bottlenecks in the process that are plaguing everyone.

Yeah.

Both industry and regulators. And then we provide a neutral ground with 3 pillars, the scientific infrastructure, the regulatory infrastructure, and the legal infrastructure to create a truly neutral ground where all the actors can come and share information that would be very hard to share otherwise. Right.

Right.

Point in case, the patient-level data from the trials from industry combined with patient-level data from the observational studies from academia, patient registry data from advocacy groups, and electronic health records. We have a unique data and analytics platform that is 720,000 individual records strong in a fully integrated manner, fully standardized. But we're not a data vendor.

Yeah.

We collaborate with a lot of data vendors. But the point about us integrating data is that we leverage the data to transform the data into solutions that remove the bottlenecks. So in those disease-specific but solution-agnostic collaborations, we take the data and we look at biomarkers, disease progression models, clinical trial simulators, new endpoints, Composites, you know, the whole spectrum of solutions that can remove bottlenecks. That's one flavor. There's another flavor that is solution-specific but indication-agnostic. Example, the Patient Reported Outcome Consortium.

Yeah.

It's all about developing new PROs that solve bottlenecks. And the third flavor are the ones that are both indication-agnostic and solution-agnostic, like our Rare Disease Data and Analytics Platform, which is all about the rare diseases and all about the solutions that can be built. Traxa is one of the newer ones.

Yeah.

That is intended to help those in academia that care about translating discoveries into actual medical products that need to navigate the valley of death. So in that very specific case, we provide Not just funding to those academic groups that have that interest, but very specific regulatory science guidance so that they can navigate that valley of death without dying in the valley, and the translation can be made more efficient. I hope that answered that question.

That's incredibly so. No, that's— and even then some. So I think that really helps give sort of the spectrum of all the different things that you guys have done. And, and we have— I mean, I've even, in addition to the grant reviewing, my own company Cadenza is developing a drug for endometriosis. And I got a chance to hear you on a panel in Chicago in June or something, um, where we really started to talk about the indication and the challenges with that specific indication, one of which is the primary endpoint for clinical trial is pain, and that doesn't capture all of the aspects of disease. And so We're trying to, as a drug developer, trying to understand how we can navigate that. But there's so many others in the industry, patients especially, that are hoping for better solutions. And it was really great to have that conversation and understand the ways that the Critical Path Institute can help, help us navigate that because we're a small company and the very thought of changing an endpoint just seems so overwhelming and insurmountable. But as a patient of endometriosis, I'm very keen to change that endpoint myself because pain is not my only problem either. So it's really great to see the work that you guys Yeah, no, that's the—

and thank you for sharing that very personal experience, Elaine, because you touched on something that is at the core of everything that we do. There's multiple terms for this. FDA calls it patient-focused drug development. Go beyond the slogan and the name. It's all about the living experience.

Yeah.

What is it that really matters to the people? That live with a number of conditions that require meaningful solutions for those clinically meaningful aspects of the conditions. And everything that we do starts with that. What are those things that matter to the people that stand to benefit from the new medical products, and what are the barriers? And by barriers, I also want to just put this plug in. It's not— people call it regulatory barriers.

Yeah.

I can tell you this, regulators want to innovate and they're very open to innovation and they're not putting up barriers.

Yeah.

We just need to make sure that the science and the evidence tracks. And that's the power of collaboration in that sense.

It's so important. And that, you know, we think of the FDA and they have these, the strict rules, and it's regulation, and checking the boxes. But at the end of the day, the FDA wants the drug to make patients feel better. Does the patient feel better is the thing that they care about the most. And so understanding the patient journey and being able to leverage the resources at Critical Path, I think, really helps share that journey from patients too.

Yes, and the transformation of the way to think about endpoints and trial design and how to select the right participants for the trials. It's all part of the same spectrum. And the proof is in the pudding, right? Because you can develop a lot of biomarkers. You can develop all kinds of sophisticated quantitative tools that may or may not include AI and—

Yeah.

—the new endpoints. So what? Did that actually move the needle in drug development? And so we have been very proud of the fact that we have transformed some really problematic areas in drug development. The first new drug and first new drug regimen in tuberculosis in more than half a century, that was made possible through the collaboration that we set up to generate additional innovative science in that field. Same for Friedreich's ataxia, devastating—

Yeah.

rare disease, polycystic kidney disease, type 1 diabetes prevention, Duchenne muscular dystrophy, Alzheimer's disease. Those were areas where there were no approvals for quite a long time. And thanks to the collaborations, now we're seeing the approvals, and that has a multitude of benefits. Number one, of course, people benefit from those novel treatments. Second, There's more interest in putting more new drugs through the pipeline. Because if you have an area that is problematic and there's no light at the end of the tunnel, people divest. And then people end up hurting in the end. And then the continuous generation of additional science that can help inform other areas. That's the connecting the dots theme that you hear us talk about a lot.

Yeah.

What we learned in TB, we applied it to Alzheimer's. What we learned from those 2, we applied in polycystic kidney disease. We applied that to type 1 diabetes prevention, et cetera.

That's fantastic. And talk about huge initiatives. I mean, the Alzheimer's piece, Parkinson's, all of these incredibly complex, very, very hard indications. The science itself is hard. I love that you guys are trying to make the process a lot, a lot easier. You mentioned the data, the shared data piece. Talk to me a little bit about that, because that's, you know, as I'm sure AI is the new sexy buzzword these days and data, data, data is all we can talk about, but that's a lot of different things to a lot of different people. Talk to me a little bit about your guys' effort in that space.

Yeah, absolutely. So as I was saying earlier, we don't integrate data for the sake of integrating data because everybody wants to look at data today. We've been doing this since our inception.

Yeah.

But we integrate the data that can support the generation of solutions that can actually accelerate drug development, de-risk the process, provide higher certainty, and facilitate regulatory reviews. Okay? So hope versus hype. Right? So for us, we're agnostic to what method is the method that will provide the solution.

Right.

But once we lock in on a solution, we know what method we need to use. Sometimes we just need rather simple statistics on well-integrated, well-curated data to provide an answer that transforms a drug development area.

Yeah.

Sometimes we need to get more sophisticated and have multivariate models with pharmacometrics approaches. Integrated into the whole thing. Other times we need to go to AI to identify interplay between variables that would not be able to be identified otherwise, interpreting imaging, type biomarkers, et cetera. But we're not married to one method or another. We're open to whatever is the right method that will answer the question at hand. So in order to get the data integrated, The first thing that you need to build is the trust from the data contributors that the data are going to be maximized in their utility, but with a lot of protections to the people that actually put in the effort to participate in the research.

Yeah.

And also understanding the context for the different data sharing exercises.

A deceptively simple statement. That's so hard though. That first step, I think people gloss over around of like, oh yeah, that's easy. No, trust is the very beginning stage if you're looking to do that. That's hard.

It is hard, but at the same time, if from our experience, so, and this is how we vet which areas to take on to deploy our public-private partnership model. What's the unmet need, and how to express that in really refined regulatory science language. That's essentially diagnosing what the problem is, not what the symptoms of the problem are. Right. So, what's the unmet need? Once you understand that, you can formulate what the solution needs to look like. Once you understand that, you understand what kind of data you need and what kind of analytics, AKA evidence, you need to generate to demonstrate The solution can solve the unmet need. What would be the value impact of solving that unmet need through the Envision solution? What is the regulatory strategy to move the solutions for their endorsement so that they can be deployed and applied? And budget and timelines. That's what we look at constantly.

Wow.

And so in gaining the trust of companies, and universities and patient groups and hospital systems is because we're very transparent with those factors and we walk them through how the solution is intended to be built. And we open up the processes that we have, and we have the legal process also very well documented. We're very transparent with that, and that's what eases the perceived barriers. And that's how we've been able to get all those data points into our data and analytics platform.

You guys might be the best cat corralers I've ever heard of. That's a lot of different, sometimes very angry, maybe wet cats that don't like to play well with each other. And so that's— it's really important to have the person that can guide and help everyone come to the sandbox, as it were.

Yes. So we use the term that, you know, cat herding.

Yeah.

But you put an inflection on it because it's aggravated wet cats that sometimes we need to work with. But once they see it's all about the value proposition of solving that unmet need.

Yeah. Well, looking ahead, what are some of— I mean, not that you have— you've already done an incredible amount in 20 years in solving some really challenging scientific problems. What does your 3 to 5 year outlook look like?

Oh, thank you for that question. So one question that we get is when people look at our portfolio and they, they see, well, you worked in 30 plus, almost 40 indications. How, how did you do that? Well, it's because we've been able to define 5 core competencies. Everything data, data science, data standardization, data management, data platforming, everything advanced analytics from statistics to pharmacometrics to mathematical modeling to QSP to AI, everything biomarkers.

Yeah.

Everything outcomes or clinical outcome assessments. And regulatory science. With those 5 core competencies, we're able to tackle any drug development area. The expertise in that area, we sometimes bring that in. We have concentration areas in neurology, rare diseases, pediatrics, metabolic. But we bring a lot of the strength through the collaboration. And the experts that we bring in each one of the areas But we're the experts in the 5 core competencies, and that's what allows us to be so portable. So where would I invest in the next— in making sure that the core competencies stay ahead of the curve to meet the challenges of 21st century drug development? Things like providing meaningful answers on how to use real-world data and transform that into actionable real-world evidence for drug development. The use of digital health technologies as drug development tools, the deployment and the understanding of where and when to deploy what type of AI tool to solve problems. Number 4, the transformation of translational sciences. So everything having to do with novel advanced methods, everything that links to the 3 Rs. Refine, reduce, and replace animal models in drug development. And then 5, all the new technologies, gene editing, oligonucleotides, cell-based therapies, gene therapies. Those are the 5 areas where the 5 core competencies we're investing in making sure that we can stay ahead of the curve and then let the indications come into that mix of what this modern drug development paradigm can look like.

I love that. That's very exciting stuff to look forward to and seeing coming out of Critical Path in the next few years. But hey, beyond a strong cup of coffee, what gets you out of bed every day, Klaus?

You know full well that I'm an avid double espresso drinker because you saw me in Chicago filling up on the double espressos. What gets me up every morning is the fact that we can meaningfully transform paradigms. paradigms that will ultimately benefit millions of people globally. And that we do that through collaboration, and that we do that through an amazing set of people that we have as employees at CPATH, but all the collaborators with the regulatory agencies, industry scientists, patient advocates, academicians, et cetera.

Fantastic. Well, thank you so much for sharing the work that you are doing, the work you have done, and the work that you're looking forward to. We'll be sure to keep an eye on the Critical Path Institute and your work in the future. I'm looking forward to working with you, hopefully on the endometriosis side. And as always, we will have Klaus's contact information and information about Critical Path Institute posted in our show notes. Make sure that you check them out to learn more. Thanks again for joining us, Klaus. Thank you.

Yeah, no, thank you, Elaine. This was a, a really super cool conversation. Thank you.

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