Off-Target, On-Point: How Retrogenix® Reduces Risk and Animal Use

Mark Aspinall-O'Dea:
Because the technology has been around for quite a number of years, it, it's been impactful both from a client perspective, , but also from a regulatory standpoint, It's changed the landscape that clients work towards within the biopharma space. Screening against the Retrogenix platform has identified previously unknown interactions for even quite late- stage molecules that would've had quite a significant impact on that drug had it gone into clinic. So from a de-risking standpoint, whether that's looking at something that's going first in human or not, it's quite a significant impact for the client.

Mary Parker:
I'm Mary Parker and welcome to Sounds of Science. Today we're joined by Charles Rivers, Nick Brown and Mark Aspinall-O’Dea to discuss the groundbreaking Retrogenix® cell microarray technology and its impact on drug development.

Mary Parker:
We'll explore how this innovative technology is changing the way we identify on-and off-target interactors, reducing animal testing and accelerating the drug approval process. We'll also dive into the FDA ISTAND pilot program and what this recognition means for the future of Retrogenix. Plus, we'll discuss its role in the shift towards more ethical drug development and what's next for this game changing platform. Let's jump in. Welcome to Sounds of Science. Nick and Mark, we are honored to have you both on the show.

Mark Aspinall-O'Dea:
It's nice to be here with you. Yeah.

Mary Parker:
So can you tell us a little bit about yourselves and your respective roles at Charles River? Nick, do you want to start?

Nick Brown:
Absolutely. Thank you. So, hi Mary. My name is Nick Brown. I'm group leader of the client services team that covers the Retrogenix platform. My primary role with this company is to ensure the platform studies are set up to optimize client results and also help to promote continued usage across the industry and also to help develop the platform to become more useful and more powerful for drug developers.

Mary Parker:
Excellent. Mark, what about you?

Mark Aspinall-O'Dea:
Hi, Mary. Yeah, my name is Mark Aspinall-O'Dea. I'm an associate director, Charles River and responsible broadly for the Retrogenix platform development and the work we do on behalf of our clients. In terms of the drug development work we undertake, primarily my responsibilities are looking at how we can further improve the offering that we already have with the platform, looking at novel areas that we can explore and how that could impact both novel drug development and different mortality types that come out and also support our standard client base that have been coming back to us for many, many years.

Mary Parker:
Well, it sounds like we have two of the perfect experts to discuss this topic, so let's get started.

Mary Parker:
So Nick, in June, 2022 you came on to the Vital Science Podcast to talk about Retrogenix. For our listeners who may have missed that episode, can you explain how this technology works and what sets it apart from previous methods in drug development?

Nick Brown:
Yes, absolutely. So this platform is an in vitro tool, essentially, and maybe a better way to describe it now is a NAM, a new approach methodology able to represent over 90% of the human plasma membrane and secreted proteins in human cells. So, effectively it’s a highly physiologically relevant way of capturing and essentially accessing proteins that cover the vast majority of the human proteome and allow drug developers to test their therapeutics in development against those proteins. So, a really good way of finding protein, protein interactions or test article protein interactions in vitro without using animals or humans essentially.

Mary Parker:
This isn't probably a number off the top of your head, but can you guesstimate how many drugs that are out there today focus on proteins either as a target or as the therapeutic itself?

Nick Brown:
Yeah, that's a great question. So I think almost all drugs I would say targets a protein of some kind either to block it or activate it or deregulate it or disrupt its effect essentially. And that is a way to actually cause an effect downstream in the cell or in the tissue to therefore treat the symptom or the drug itself. So it's really relevant to identify the protein or identify what the protein might be binding to against the proteome as this can be important for both efficacy but also safety and toxicology as well.

Mary Parker:
I kind of figured, so good to note. So what is an off-target screening and why is it so crucial in the early and late stages of preclinical drug development?

Nick Brown:
Sure. So I'll maybe start with defining an off-target. Essentially, this is, as we mentioned, the drugs are mainly designed to target a specific protein, which then causes a desired effect or either activating or disrupting. For example, an off-target is an unintended binding event. So it's a protein that the molecule binds to or the drug binds to which it shouldn't do or we weren't expecting it to or nobody was expecting it to. And that can cause deleterious effects essentially that can cause toxicity, it can cause binding to unexpected tissues, normal tissues for example, which can then cause toxicity, either a morbidity or actually a mortality in patients. So off-target screening is therefore the act of essentially taking the molecule and looking for these off-targets before they can cause these issues downstream, essentially.

Mary Parker:
Not to get you off track, but has it ever happened where an off-target binding actually turned into a new promising venue for a drug?

Nick Brown:
Yes, actually, great question. So we've had molecules accidentally uncover bispecific molecules that they weren't expecting, and actually the unexpected off-targets was a positive effect. It actually was also involved or related to the pathway, the actual target that they were originally intending to target. So that tends to be on the rarer side. I can't think of more than a handful of examples there across the many thousands of things we've screened. But yeah, sometimes it can be a good case, but in most cases these off-targets are things we want to mitigate against in terms of risk.

Mary Parker:
Well then how does this technology help identify both on-and off-target and how does that benefit drug developers?

Nick Brown:
Absolutely. So this platform as mentioned, encapsulates the vast majority of human proteins and actually non-human proteins more recently, but I'll let Mark talk about that maybe later in the show. We take all of these proteins, we express them in human cells so they're very relevant, they're very physiologically relevant, and then we can take the test article and screen them against all of these proteins and interrogate them against this library. And what we can do then is of course confirm that it binds to what it's supposed to and then pick out and identify what it's binding to that it shouldn't. And actually we find about 50% of large molecule therapies have at least one off-target binding events. So it's really critical that we identify these, figure out what they are and de-risk the program essentially. Just to kind of elaborate on that, we actually see, as I say, over 50% finding off-targets. So that means the other 50% are completely clean in our hands, which is also quite a nice stat to put out there. But it is important that these molecules are de-risked at some point in drug developments. And we can actually do this really early and really effectively and actually relatively cheaply considering the number of proteins that we're actually screening against, which stands at about 6,500 just over proteins in the human proteome.

Mary Parker:
It does sound like that would save a lot of money down the line knowing those things in advance.

Nick Brown:
Absolutely. It's a de-risking tool both scientifically and safety-wise, but also commercially and financially as well. So, rather than screening using very expensive late-stage assays and tools, we can do this at a really quite an early stage in each molecules development pipeline and get that data really early so, you can essentially fail non-viable candidates earlier and focus on the ones that are going to be best chance of success.

Mary Parker:
Fast forwarding two years or so in October, 2024, a new non-human protein library was launched.

Mary Parker:
Mark, can you tell us how this library works?

Mark Aspinall-O'Dea:
Yeah, that's not a problem Mary. So it might be helpful to take a little bit of a step back and talk about where the library came from as well and the reason why we actually created it. So over the course of the last, I'd say 10 years perhaps as companies around the globe have got more used to using the human library, there've been an increase in call to look at the creation of a non-human library. And that's effectively where this has come from. We tend to build things with the Retrogenix array that are client led, and this is no exception. The way the platform works is just the same as it is for the human equivalent. So we're working with plasma membrane proteins that are overexpressed on the soft surface of those cells and in essence what we are aiming to look at are the proteins that are most different or disparate to the human equivalent.

So if you look at an animal model versus the human genome, there will be a cohort of proteins that are completely different to in their structure to the human equivalent and in some cases may not be present in humans at all. What we're looking to address here is looking at that kind of cohort that are most significantly different. So if you look at the homologies between the two protein types, they'd have perhaps 90% homology or less. And that's what we've built. To narrow it down a little bit further, we've looked at specific domains within a protein. So if you think about the structure of a protein in the plasma membrane, there's multiple different forms of the protein that kind of sit across that membrane structure, one of which sits outside of the cell called the extracellular domain. This is a bit where molecules will tend to interact on the self surface. So that's the area that we focused on primarily for the first version of this library. And in essence, that allows us to then look to see if a molecule that will bind in the human setting will also bind in an animal setting and potentially look at specific off-targets that could present in the animal that could cause a problem if you're going to use that for further study.

Mark Aspinall-O'Dea:
As soon as we launched this non-human library, a lot of clients turned around to us pretty much straight away and said, brilliant, you've got this new system, can we have it in X species please, because we want to de-risk that one, and that actually presents us with a little bit of a headache because hard to build these things, it takes time. So we've actually brought out an alternative approach to this to allow clients to look at on-target and off-target assessments depending upon what stage in the development cycle they're at. So a lot of companies, particularly large pharmaceutical companies, will decide what kind of toxicity species they want to use at the very, very beginning of their product development pipelines and we can help them select that and that's beneficial in multiple ways, but not least you can de-risk the events of potential binding on target or off-target for those animal models, which reduces the need for repeating animal studies. But similarly, when we run the human array, if we find an off-target, we can de-risk that as well. So a client can effectively get to the point of doing clinical work, really, really comfortable in the knowledge that they've that molecule to the best ability that we can in terms of the biopharma industry at the moment.

Mary Parker:
How does it aim to reduce the need for animal testing or maybe refine it?

Mark Aspinall-O'Dea:
I think both in essence. If you're in a position where from the outset that a particular animal model isn't going to work because you've either found an off-target or that it won't bind, its on target, so you're not going to get the efficacy data that you want, that significantly reduces the use of animal models that would not be suitable for that particular drug. And there could be instances where they could be replaced. I guess that will depend on the weight of evidence that supports that particular development, but particularly in the antibody space, if it's a relatively routine design for that antibody, I can imagine that being the case in the future.

Mary Parker:
Can you walk us through the three-stage ISTAND qualification process and what it means for Charles River's role in drug development?

Nick Brown:
Absolutely, yeah. So I should maybe start by with this question by defining what ISTAND is.

Nick Brown:
So ISTAND stands for the innovative science and technology approaches for new drugs pilot program, just to define that. And as you say, it is a three-stage process. So the first stage is the submission of a letter of intent. This is a document prepared by the submission or the submitter to essentially outline what the drug development tool, which is essentially the qualification that we're looking for, what the drug development tool will solve in terms of an outstanding problem in the industry or in the process of developing a drug essentially. And the idea is that the FDA is accepting these submissions, accepting these requests or letters of intent, and we'll analyze them and look to see which are going to be the most interesting, the most useful for the industry and move forward with those drug development tools for further development essentially.

So once the letter of intent is submitted, the FDA will review it and then make a decision. Luckilywe were accepted onto the program, which was of course very exciting stage for us to get to. And it means we're now in stage two, which is the qualification plan. So this is now essentially a further detailed map of what we intend to do and how our tool or how our suggestion will help the industry and essentially more specificity on the detail of what that looks like and what paradigm shift will occur with the acceptance of that drug development tool. Once that has been submitted and reviewed with feedback from the FDA, it then moves to the final qualification plan, which is the final step, stage three. Once that is accepted as well, again, that's a further detail, further, further specificity, the rough edge is smoothed off completely in the final qualification plan, we'll then have the final plan in place. So it'll be then how that's in further detail again and further specificity. Once that's accepted, then the platform will be a qualified drug development tool. And of course that's what we're working towards. We expect that to be around one to two years in terms of start to finish that full process.

Mary Parker:
So just for my own clarification, even though it's not an official drug development tool, the data that you get from it can still be submitted as part of the ongoing process for drug development, it's just additional information.

Nick Brown:
Yes, absolutely. So again, I think we're over a hundred now in terms of the number of INDs that we know about that clients have submitted Retrogenix data in, and that goes across the FDA, EMA and other regulators, the NMPA and PMDA in China and Japan as well. So it's very widely used across pretty much all the major regulators across the world. And we know that the feedback from the regulators is usually very good. They like to see this data in the IND submissions and also BLA submissions as well for later stage programs because it does de-risk in a very high quality way against the full library as we've discussed previously.

Mary Parker:
Excellent. So how will this FDA recognition influence the regulatory review process and impact drug approval timelines?

Nick Brown:
Yeah, it's a great question. We're not exactly sure on the specifics, so I wouldn't want to comment too concretely here. But what we're expecting strongly is that it will speed up the regulatory review of any ID submission that contains genic data. And again, it's that refinements and reduction of animal testing as well we think will be a positive thing for the industry of course. And also is in keeping with both Charles Rivers and the industry and the FDA's commitment to novel approach methodologies and moving away from animal testing in a controlled and safe manner essentially. So tools like this will only improve the process we think, and speed up the drug approvals in a safe way.

Mary Parker:
So as you say, with over a hundred IND submissions worldwide, how has the Retrogenix platform impacted drug development to date and what kind of feedback have we gotten back from regulators?

Mark Aspinall-O'Dea:
Maybe that's one I can pick up Nick, as we've kind of alluded to, because the technology has been around for quite a number of years, it, it's been impactful both from a client perspective, certainly in terms of the feedback that we've had, but also from a regulatory standpoint, I think it's changed some extent. It's changed the landscape that clients work towards within the biopharma space. So, we know firsthand from discussions we've had with clients over the years that screening against the Retrogenix platform has identified previously unknown interactions for even quite late-stage molecules that would've had quite a significant impact on that drug had it gone into clinic. So from a de-risking standpoint, whether that's looking at something that's going first in human or not, it's quite a significant impact for the client. Now obviously there's a couple of ways of looking at that because you can look at it from the standpoint of well, that's potentially killed a drug that's been under development for a number of years.

But as Nick pointed to at the beginning of this podcast, it significantly reduces the cost burden of going into those types of latter stage safety assessment screens that can be very costly without knowing the full picture of how that molecule's going to behave. So that's certainly one aspect to it. From a regulatory standpoint, I think there's been a growing acknowledgement that platforms like the Retrogenix platform can have a very positive impact in terms of the safety assessment data that goes into developing a new drug. And so we know from, again, from client feedback that there have been instances where regulators have specifically asked for not necessarily the Retrogenix platform, but novel alternatives to perhaps more traditional screening tools to build that weight of evidence, particularly with some of the newer modalities. And that's perhaps where platforms like the Red change platform can really come into their own.

It's agnostic to the type of drug that you can use. So as long as you can visualize it, by some means, we can typically work with any drug on the array. It doesn't just have to be small molecules, it doesn't just have to be antibodies. It can be pretty much anything. And that's been true of cell therapeutics and gene therapies as well. So it really does give a greater level of flexibility, I think, to clients who are looking to build products, but also it gives the regulators an opportunity to evaluate something in a very controlled way and in a very safe way. As Nick has said.

Mary Parker:
Well, throughout history, especially the history of drug development, there's been a shift towards being more and more ethical, and especially recently globally, there's been a huge shift towards more ethical drug development. So how do you see retrogenes fitting into that, particularly reducing reliance on animal models?

Mark Aspinall-O'Dea:
Well, I'd like to think it'll have a major role to play. I guess if you look at where we've been in the past, take cell therapy as an example, there were some very early stage trials with cell therapies that went pretty badly when they went into clinical trial, and that predated the Retrogenix platform being able to operate in that space on the back, we saw a significant uptick in the number of cell therapeutics that were screened on the library, and that continues to date to this date. So from a human standpoint, it can have a very significant impact in reducing risk when you get into clinic, obviously coupled with a large weight of data from other assay. I'm not suggesting on its own it does that, but it's certainly part of that story. So I see no reason why it wouldn't be able to do the same from an animal standpoint, whether that's to significantly reduce the burden of animals that are used or potentially replace them in some instances. I think that's certainly a viable future for the platform. And I think as we develop with our ability to working with computing power and perhaps building in silico data, the more knowledge we generate from platforms like this, the more realistic that future outcome is. I think.

Mary Parker:
Well, thanks, Mark. So I'm assuming that FDA validation kind of enhances client confidence in Retrogenix, but how does it affect the drug discovery process? So not just development, but even figuring out new drugs?

Mark Aspinall-O'Dea:
That's a really good question. We hope that it accelerates things. Ultimately, one of the challenges that I think we faced, and Nick could probably comment on this more so than I can, is that even with the technology that's been around for 17 years, there's still people out there that have either not heard of it or not used it, and they can be slightly nervous about the prospect of putting a drug through our platform to determine based on how the regulators are going to see it. And it's a fairly routine question that comes up from clients who haven't used us in the past. So having an approval such as this will hopefully mitigate some of those fears. And it's particularly acute when we're going through market conditions as we are where money can be tighter and decisions can have very, very significant impacts on clients and the drugs they're trying to bring into market. But ultimately, if we can get to a point where clients have confidence in what we do, we generate data very quickly as a platform technology, it can only be a good thing to accelerate and de-risk future pipelines.

Mary Parker:
What do you think are some of the most exciting developments as a result of this technology's continued growth and adoption?

Mark Aspinall-O'Dea:
I think looking at what we've done over the course of the last, let's say 10 years, so from 2015 to 2025, the platform has shown to be highly flexible. So pretty much every new drug modality that's come out, as I've already mentioned, cell therapies, but gene therapies more recently, it has the ability to be molded in such a way that it can perform screens with those types of modalities. So there's really not a lot out there at the moment that we can't work with and in areas where we can perhaps work more effectively. That's the thing that excites me the most. How do we improve on what we already do? How do we build it bigger and better and generate clearer data for clients? And I think that's the bit that it's exciting at the moment, tying that in potentially in the future, as I've already mentioned with in silico data, so everyone references ai, but using computer modeling as some description to inform on the output that we generate and how that can impact on the biology of a drug once it's in the human body, that could be significant too. So there's lots of areas where I'd like to think this data will have a pivotal impact at least.

Mary Parker:
So this final question can be for both of you, but we'll start with Mark. What can we expect next for Retrogenix and how do you envision the platform influencing the future of drug development and patient care?

Mark Aspinall-O'Dea:
Ooh, that's a big question, isn't it? I think in the immediate future, more from us in terms of the non-human space and looking to help clients de-risk that perhaps looking at how we can position the platform in different ways. So Nick mentioned that we can do assessments quite early. There can be some challenges around doing it very early. So there's different ways in which we can make the technology accessible to clients depending upon how they want to build their drug pipelines into the future. And I think, again, we can probably both comments on this that no two clients do things the same way it would seem. So flexibility I think is a big key point for me into the future. And just being reactive, as I say, we react to the market. There's no point in us building something that people don't need or use. We'll always be reactive, we'll always listen, and that's one of the key messages for us, and hopefully it points to why we've been successful over the years. But Nick, is there anything else you want to add to that?

Nick Brown:
Yeah, I think I completely agree with your flexibility comment. I think we've always been really agile to what the markets needed, and the platform is incredibly versatile, so it lends itself really nicely to developments in different modalities, different therapeutic areas. And because we're using such an unbiased, broad-ranging library in many of our studies, again, it means that we're super versatile across the industry. I think the platform gives a really, or it helps with the development of even more interesting molecules, things like ADCs that are of course becoming a lot more popular these days. Really complex multi-specifics that activate T-cells, bring them towards cancer cells, that sort of thing.

I think we're, and the platform is uniquely positioned to help de-risk some of those really interesting, very effective, but potentially quite dangerous molecules if you find off-targets or other liabilities with the molecule, essentially. So that's what really excites me alongside all the other things, is being able to really develop the most useful, efficacious, interesting molecules that are actually going to help patients in the most effective ways, but actually de-risking them and make sure they're not going to cause issues and deleterious effects.

Mary Parker:
Oh goodness. A new acronym. What's an A DC? I haven't heard that one before.

Nick Brown:
Apologies. That's an antibody drug conjugate, so it's what you...

Mary Parker:
Have. Oh, right. Okay. Yes,

Nick Brown:
The antibody, you conjugate a sometimes quite a nasty cytotoxic payload to the antibody, and it means you get all of the advantages of targeting with the antibody, but with the efficacy of a small molecule drug that's really quite effective against cancer cells, for example. So combining those two things is super effective, super interesting. It's been shown, but of course, if you have that antibody moving towards a normal tissue, it can then cause damage that it shouldn't be doing, and that's really what we're trying to de-risk. So platform is regularly used for those sorts of molecules. I also mentioned, as I say, things like bites, bispecific T-cell engages where it's essentially a bispecific molecule that targets the T-cell and also the cancer cell. So it pulls the immune system towards the cancer cell and hopefully allowing the T cell to kill the cancer cell. Again, you don't want that happening to a normal tissue like cardiac tissue, heart tissue, for example. And again, we've seen unfortunately, quite tragic cases that has caused issues and tragedies in trials, for example. So the more we can do to de-risk that, and with all the advantages of NAMs, 3Rs moving away from animal testing. Yeah, that's why we're so excited about this platform.

Mary Parker:
Yeah, it definitely sounds like it could be very useful and for that exact situation. So thank you Nick and Mark for being part of sounds of Science. It's been a pleasure having you both on the show.

Nick Brown:
Thank you for having us.

Mark Aspinall-O'Dea:
Thanks very much.

Mary Parker:
Nick Brown, Group Leader Client Services, and Mark Aspinall- O’Dea, Associate Director, are both with Discovery Services at Charles River. Stay tuned for the next episode. Stay tuned for the next episode of Sounds of Science. Until then, you can subscribe to Sounds of Science on Apple Podcasts, Spotify, Stitcher, or wherever you get your podcasts. Thanks for listening.