New Approach Methodologies in Oncology: From Concept to Use

Hello and welcome to CrownCast, a podcast brought to you by Crown Bioscience. I'm your host today, Michelle Dawn Mooney, and today we're discussing new approach methodologies, or NAMs, through the lens of Crown Bioscience's new participation in C-Path's NAMS Developer Coalition. The announcement highlights a shared focus on advancing the validation, qualification, and regulatory adoption of more human relevant research methods, and it also points to Crown's specific strengths in patient derived models, organoids, ex vivo tissue platforms, translational biomarkers, and bioinformatics. So, with that as context, I'd love to explore both the big picture direction of the field and what this collaboration could mean in practice, and we have two great guests for that conversation today. Graham Marsh is Director of the NAMs Developer Coalition at the Critical Path Institute, and Ludovic Bourré is Vice President of Research and Innovation for Crown Bioscience. Thank you both for being here today. Thank you. Looking forward to this conversation. Before we kind of dive in here, Graham, starting with you, could I have you give us a brief bio, please? Yeah. So thanks for having me. I'm Graham Marsh. I'm the director of the NAMs Developer Coalition at the Critical Path Institute. C-Path is a non for profit that's focused on on building consortia that are trying to advance regulatory science in meaningful ways for patient benefit, for improving the way that we develop drugs, and hopefully delivering medicines to people cheaper. And so the recent launch of the NAMs Developer Coalition is our mission to try to bring some of our regulatory expertise into this growing field to advance these tools as appropriate and useful and innovative methods for developing new drugs. And Ludovic, love to hear a little bio from you if we can get to learn a little bit more about you as well. Thanks, Michelle. So I'm Ludovic Bourré, I'm VP of Research and Innovation. So I'm leading the R&D effort at Crown Bioscience. So meaning all R&D efforts that are inside Crown, but also external partnerships and also joining consortium like we are discussing today with the NAMs DC. So very excited by the discussion and bringing more insight on what is the goal of the NAMs DC coalition. Yeah, a lot of exciting things to talk about today. So let's dive right in, but I want to start with really defining the field. NAMs has become a very broad umbrella term spanning organoids, organ on chip, in silico approaches, advanced in vitro systems, and much more. So how do each of you define the boundaries of what qualifies as a NAM? So I think it's helpful to think about NAMs in regulatory context because we have our established methods, our animal models, our 2D cell cultures, and when we're talking about NAMs, we're talking about new approach methodologies where we can use the innovative science, the emerging technologies to improve upon, supplement, or replace these existing methodologies with better science that provides more human relevant patient specific data to make these these important regulatory decisions. And so, yes, it spans an entire range from from complex in vitro models, organoids, 3D systems, micro physiological systems that have some some physiological flow or shear stress, even into the in silico computational AI tools that can provide some insight. But under this large umbrella, we're thinking about NAMs in terms of how are we collectively advancing the science and validating these tools and qualifying them in a way that will allow us to get that more human relevant data, to get that more patient specific information into the hands of the end users and decision makers to hopefully provide drugs that are more effective and safer to patients. So to elaborate on what Graham said, I fully aligned with this vision, in my perspective, my approach is really to improve human relevance and also to have better productivity compared to the existing models. We know that there is a lot of caveats today on the preclinical model that we use, we can do much better, particularly defining questions that can provide more mechanistic, biological, and toxicological insight. My view, the importance as well is not whether the platform is new, but whether it's really fit for purpose and showing evidence that it will help on the transitionality between preclinical and clinical. For example, we can use patient derived organoids that can help to prioritize compounds based on the response in diverse genetically diverse models. For ex vivo tissue platform, for instance, that can have some impact of the tumor microenvironment directly in fresh human tissue. So, it's really a matter of what model you use and what type of question you want to answer. This really is an important partnership, and one of the central themes in the announcement is not just scientific innovation, but validation, qualification, and then regulatory adoption. So, from your perspective, what can a coalition like C-Path's NAM's Developer Coalition do collectively that individual companies, technology developers, or CROs would struggle to do on their own? So maybe I can start for the Crown perspective. So by joining NAMs DC really is that on the Crown side, we want to contribute with our own expertise in model and platform development. So this is a big focus for Crown Bioscience to really push the NAMs development and application. But also, on the other side, it's really for Crown to learn as well from others joining this coalition. So from the biotech and pharma companies joining the coalition, the NAMs developers as well. There is a lot of different technologies now that are developed so to understand the environment and which platform makes sense to address some of the questions. And also, obviously, at the end is to have some acceptance from the regulatory body, which is very important to move, I would say, those technologies forward and after have some meaningful impact in drug development. So really, for Crown's side, it's really to learn from from different perspectives and help to advance the NAMs technology. Yeah and, I mean, from from the C-Path side, the reason that we're so excited, fortunate to have Crown in this coalition is that we really need partners that are investing the technology and and serious about moving them towards these important validation and qualification studies to to work with us to to really advance the field. I mean, thinking back to my days in grad school, you know, you build an organ on chip system or, you know, an NPS model, and you get the cells to twitch. And it's a fun party trick. But it's just, you know, the first step in a very long line of getting the tool qualified and ready for true pharmaceutical science. And so having partners like Crown that are really committed to the space and investing in these technologies, to think about how to build these robust, translatable packages of data that can show that these tools are human relevant, they are representative, and they are, can be fit for purpose or qualified for specific context of use to make these pharmaceutical decisions. And so that's where there's a lot of work to do. We're fortunate to have great partners, working on this, but, this is where these sort of coalitions, consortia are really important for the field because no one company, no single CRO is going to be able to tackle this this this daunting problem of qualification. And so having this pretty competitive collaboration, having scientists that are committed to the the technology and seeing it advance is incredibly important. And, you know, we have a lot of work to do, but we are making some important first strides with this new NAMs developer coalition. And Graham, you talked about kind of trip down memory lane in grad school. So I'm thinking about that, and I wanna ask about where the field is today. So where do you think this field sits today on the NAMs adoption curve? Are these approaches still being used mainly as exploratory tools, or are they beginning to influence real portfolio decisions, study design, and go/no go decision making in drug development? And maybe, Ludovic, if you want to start us off there. Yeah, sure. No, in my opinion, we are really moving beyond the point of exploration. So there is a strong element now using NAMs technology. We do see some increasing use to inform, for instance, on target prioritization, combination strategy, or to have a much more early go/ no go decision in the drug development process. So for example, an organoids panel can be used to notify patient population that are more suitable responders to some drugs and that can definitely inform to help on the clinical trial design and patient enrollment. So we do see a very strong adoption of those kind of technologies early now in the drug development process. Yeah and, I mean, I'll just add on that from a from a regulatory perspective, thinking about the the strides that the FDA and EMA have made recently with their announcements, with their guidances, with updating some of the language around the the preclinical models that can be used for these IND and NDA applications. There's there's lot of movement, a lot of support from stakeholders that are making these decisions in terms of trying to get these tools into the hands of decision makers to to provide more human relevant data for these for these packages. And so not just from the pharmaceutical side, we also have stakeholders coming in from the regulatory side that are really pushing to advance these tools. And yeah, it's really an exciting time because if we're thinking about you know, some of the antibodies, the ASOs, the gene therapies that are becoming more and more mainstream in terms of the therapeutic modalities that companies are developing, having these human relevant tools, having these patient specific disease models really does benefit their decision making process in terms of making sure that the human specific modality that you are developing can translate into the clinic in a meaningful way. I want to talk about Crown's specific contribution here. And Ludovic, I'd love to start with you, but Graham, I'd love to hear your thoughts on this as well. You know, the press release on this partnership highlights Crown's expertise across patient derived xenograft models, patient derived tumor organoids, ex vivo patient tissue platforms, translational biomarker analysis, and bioinformatics. Of those capabilities, where do you think Crown can make the most immediate and distinctive contribution to the coalition's goals? I guess we touched on already a bit this point. I think from our perspective, it is really to contribute with our expertise in patient derived models and also platforms. So we are very invested in organoids platform, for instance, ex vivo tissue platform, not to replace but to be complementary to our existing in vivo capabilities. And we do see as well this from our client discussions that they are using more and more those platforms very early in drug development process to help them to refine and go faster in the drug development. So this is a thing where by joining NAMs DC, we can bring more expertise in terms of discussion with the industry and how the industry, I would say, moves in that direction and how we should implement today, which will be definitely very different to what's going to happen in five or ten years. But I think this is the path that we do see where there is an increase on the NAMs DC adoption. Yeah. And and let me just add that, you know, I don't wanna narrow it on one specific technology here because from my perspective, Crown's contribution is yes to all because we really need the Crown expertise in all of these spaces. And one area that I think is really important, but we don't talk about it as much is thinking about the clinical translatability of NAMs. And looking at Crown's history of translational biomarker work, I feel like there's a real opportunity there to make some of these these translational decisions or build out these translational data packages that show that these organoids, these preclinical NAMs can really translate to human biology in clinic. And these data packages are are going to be very important for building confidence and the credibility of the data these models produce, and help to advance validation and qualification moving forward. And so really, you know, yes to all in terms of, what Crown is bringing to the table with this collaboration. And it really is such an exciting time and a big learning curve here because it's all so new. Patient derived models, organoids, PDX, humanized models sit in an interesting intersection right now of new approach and still needs an in vivo or ex vivo system. How do you think about where those fit in the NAMs conversation? So I feel sometimes that we approach NAMs as simply as animal free versus animal based methods, which is true, but I think we should approach this a bit differently and basically how well those models reflect the human biology and is it at the end translational to the clinic? So this is again why the context of use is critical to really understand if that makes sense to use this approach to address some questions. So I think this is what is really important to to integrate when we discuss NAMs and also how we approach this when we discuss with our clients in the drug development process. Yeah. Ludo is a 100% right there. The context of use for each of these applications is the most important aspect of of adopting a NAMs for a specific question of interest. And so identifying really where these tools can can have a domain of applicability, what data they will produce to either refine or replace or supplement existing methodologies and advancing that specific context of uses is really where we're seeing adoption right now. Hopefully, as we build on these data packages, this becomes an easier discussion and the context of use becomes broader and broader. But for right now, I mean, we're looking for these targeted applications that we can advance the NAMs, refine, replace animal experiments, and make that in vivo to in vitro jump where where applicable. And speaking of broader and broader, a lot of the broader discussion around NAMs tends to focus on toxicology and safety testing, but I want to take things beyond that. How do you see NAMs evolving beyond safety into efficacy studies, mechanism work, and broader decision making in oncology drug development? No, I fully agree. I think NAMs can and really do have much more potential compared to just the safety question. So, in oncology, for instance, they can support efficacy testing, understanding mechanism of resistance, and also helping on combination strategy and patient stratification. So, altogether, that really can help to de-risk earlier drug development, both on the efficacy side and also on the safety side. So it's very complementary. I think we should approach both questions. Obviously, there have been a lot of focus on the safety because it's a major concern and also a lot of drug failure due to the toxicity issue, but also the lack of efficacy is problematic in a lot of drug development. So, this is where NAMs also have a play in the drug development process. Yeah, and think to add on to that, thinking about the rare disease space or the well characterized mutations in some cancers, NAMs really do provide an ideal tool for investigating mechanism and efficacy in these types of systems. And so building out a NAM with with a specific mutation allows you to really dig into mechanism, understand the biology, and interrogate the efficacy of therapeutics in a way that animal models, frankly, don't. And so that's really where I see a big push in the future for building out these patient specific rare disease, rare cancer models so that we can really drive these efficacy decisions in meaningful systems and bring these therapies to patients. There are a lot of moving parts here, and I'm sure that the process is not as quick and swift as some of you would like, so biomarker discovery and validation is often the bottleneck in translating a NAM derived finding into something clinically actionable, which is what you want, right? So, how should sponsors be thinking about biomarker strategy alongside model selection? In my opinion, model and biomarker strategies need to be really taken along together very early in the process. Most often, it seems the biomarker strategies are more late in the development to have a question that brings a biomarker to have an intent application during the clinical trial, for instance, is really here, in my view, a game changer to first there is the drug development process, but also to have more impact at the end on the drug development. So this is where I think the challenge sits and this is where I think Crown is very well positioned with the preclinical models. We can define some hypothesis in terms of biomarkers. But also we have CLIA lab certification when we can run clinical samples. And this is where we can bring back those clinical samples in the loop and then verify some hypotheses that begins in preclinical. And this shortening the time of biomarker discovery between preclinical and clinical is really where NAMs can really help to close the gap and help to make the bridge that usually take a very long time to develop in the in the in the standard development process. Yeah. I don't have too much to add. That's exactly my view as well. And it's really why we're fortunate to have a company like Crown sitting on our NAMs developer coalition to help think about some of these biomarker translatable strategies that will really, you know, advance the data packages and drive the field forward. It's been a little bit missing in the loop in some of the initial conversations around qualification of NAMs at the FDA with some of the model developers and bringing in this this, you know, broader perspective from the CRO, like Crown Bioscience is really, really incredibly useful and is helping us move the the NAMs DC forward. I want to talk about the realistic near term impact in oncology. Oncology remains an area with very high attrition rates and persistent translational challenges, as we kind of referenced before, not always smooth sailing. Where do you see NAMs having the most realistic near term impact in closing that gap between preclinical findings and then clinical outcomes? Well, I think the near term impact is to reduce uncertainty earlier. So to have go/ no go decision much more early in the process, for instance, by identifying weak mechanisms, non-responsive patient population, poor combination strategy or some safety issue as we discussed as well on safety and not only on the efficacy. So the two together and this before running expensive preclinical or clinical study, and that can help also to make more investment very early in the earlier in the drug development process and reduce the risk of the maximum the failure in clinics. I think I'll add that I'm really excited about the potential for for these NAMs to provide some some safety data in the oncology space. I think that de-risking some of the GI, hepatotoxicity, you know, kidney toxicity that we see in a lot of oncology drugs to get safer medicines at appropriate doses into clinic faster is really where we can see some of these tools accelerate the drug development cycle. And I, you know, I think that that's going to be a win if we can set a more appropriate starting dose using these NAMs human relevant data, right off the bat, can shorten clinical trials, can get these medicines to patients faster, and I think we'll have a great benefit long term. What's your advice for sponsors that are genuinely interested in integrating NAMs into their development strategy, but they're not sure where to start? I think we need to start somewhere and really when we discuss with clients is to make some decision on where we should start based on the drug they are developing, what makes sense in terms of NAMs implementation, rather they want to change everything at once and replace everything by NAMs. I don't think this is realistic. So, we need to take like a stepwise approaches where we implement NAMs and also we show proof as well of the NAMs utility to the community to really show the translational ability again of using those NAMs and how they can help clients to fast track. So we discussed about safety, there is a lot of now tools that are used and that have been showing a very good transferability to predict toxicity. So, this is one aspect to this on the safety side. And also, as mentioned on the efficacy side is really to go faster and also identify, for instance, in organoids using organoids platform in oncology drug development, the right patient population, for instance, when we can screen a very large number of models that can represent the landscape of the of the population and then after really targets in the clinic the right patient population. One of the work streams that we've started in NAMs DC right now is trying to think about what sorts of validation data packages would help to convince sponsors that NAMs are appropriate for specific questions in their drug discovery funnel. And I think that that's really a key that's missing in the field right now is for the model developers, for the CROs that are that are trying to to scale these technologies, to have appropriate validation packages ready to go to not just convince, but like build confidence with the sponsors that these tools can replace some of their animal models for specific questions of interest. And so that's I think really where we are hoping this consortia can advance the field and sort of lift all boats by working with companies like Crown to identify what data exists currently that we are able to share, what gaps in those data exist, and how can we close them to really build out the confidence in these tools. And so I think that that's a question for us thinking about how we can advance to the sponsors. But then also sponsors, I think need to be more vocal about what their needs are in NAMs. I think that, you know, pharma companies, I worked in pharma for a little while, they're not necessarily the most open with with their questions that they have. And so really identifying what their problems are, where their gaps are, and working with them as a partnership to move this field forward is is something that that I hope that we can advance with the NAMs Developer Coalition. As we wrap up here, what's a NAMs application you are personally excited about that hasn't gotten much attention yet? So, I mean, I'll start. From my perspective at C-Path, I really think that a lot of rare diseases are underserved for a good reason. Like they're small patient populations, there aren't animal models to address them. And I'm really hopeful, excited, about the opportunity to use these these NAMS as stools for discovering new gene therapies and ASOs for these vulnerable patients and try to get them into clinic faster and help these patients. An area that I think we need a lot of work, some investment to build out these efficacy models to show that they are translatable and useful and we can apply these NAMs to this underserved patient population. But I really am hopeful in the next three - five years, we do see some gene therapies, some ASOs go into clinic with NAMs data primarily to advance these tools for these rare diseases. Yeah, no, I fully agree with Graham. I think in addition to the rare disease, think pediatric oncology have been underserved because it is a complex trial to run and also drug developers are hesitant to really go in that direction. And this is where NAMs can, I think, helps to have more models develop around those therapeutic areas, rare disease or pediatric indication. And also, the addition of the safety, I think a lot of the initial NAMs application were very focused on the safety. And that was also kind of the starting point from the FDA is to de-risk, there is the toxicology aspect. But beyond this, I think the efficacy is definitely something I'm very excited to have more tools and platform developed using NAMs for efficacy assessment of the different drugs and modalities. A lot of exciting things happening. More exciting things to come. Graham Marsh, Director of the NAMs Developer Coalition at the Critical Path Institute. Ludovic Bure, Vice President of Research and Innovation for Crown Bioscience. Thank you so much, both of you, for your time. As I said, very exciting things happening and really looking forward to what the future holds. Thank you being here today. Appreciate your time. Yeah, thanks so much. This was great. Thanks, Graham. And I want to thank all of you for tuning in and listening to the CrownCast podcast. Of course, you can subscribe to the podcast to hear more engaging conversations like the one you heard today. And if you'd like to learn more about Crown, you can visit crownbio.com. I've been your host, Michelle Dawn Mooney. Thanks again for joining us. We hope to connect with you on another podcast soon.