Panel: The CAR Journey

Nicholas Ostrout (00:00:01):
All right. You guys ready?

Julia Sable (00:00:04):
Sure.

Nicholas Ostrout (00:00:04):
All right. That's good. All right. Welcome, everyone, to the CAR journey. I'm really excited to be moderating this panel. I hope you've enjoyed the day so far and you're not too tired after lunch. So if I see too many people nodding off, we might have to go down to the bar and get some drinks and do the panel down there. It's small enough group.

(00:00:27):
My name is Nicholas Ostrout. I am a senior director in our scientific services team within Charles River. Scientific Services is sort of a team that helps both external and internal stakeholders within Charles River navigate across all the cell and gene therapy workflows. Starting from early discovery all the way into commercial manufacturing. So we really sit with our clients no matter where you come in to Charles River and really help you navigate through the various service teams that you might need. So we really like to build it as a concept to cure and really work with you from discovery into safety, manufacturing and testing as well.

(00:01:18):
I'm excited to spend the next hour here. So we have our panel. I'll let them all introduce themselves, but we're just going to really focus on the different steps of the CAR journey. Although it's called CAR, we're really covering gene modified cell therapies in vivo and ex vivo. I think a lot of what we talk about will be generally applicable to CAR NKs or engineered TCRs. So I'm looking forward to it.

(00:01:48):
So I'll definitely start the conversation. I have a couple of things that I'd obviously love to talk about, but honestly, I always love when the audience gets involved in these panels as well. I think you guys provide a lot of interesting insights and many of you know field just as well as I do. So it's really great to get other perspectives into it as well. So I'll kick us off and we can kind of take breaks and let the audience join in as well. Okay. So let's go ahead and I'll let our panel introduce themselves. So maybe introduce yourselves, tell the audience a little bit about your area of expertise and what you've been doing in the cell therapy space, and then we'll dive into some of the topics.

Manu Kohli (00:02:32):
Sure, I guess ...

Nicholas Ostrout (00:02:34):
Yep, it's on.

Manu Kohli (00:02:36):
Is it on? Yeah, so if I fall asleep and you understand I'm getting a food coma. So I actually am part of the science advisory services at Charles River. I've been in this role for about two and a half years, but I've been in the field for over 20 years. I've been leading drug discovery teams in early discovery oncology, both actually quite a different number of areas, in small biotech, mid-size biotech, pharma, as well as in government, and now a CRO. So I've seen a lot of different backgrounds in those different venues or in different spaces.

(00:03:14):
Got my PhD way back in the day in biochemistry, molecular biology, with again, heavy focus on oncology. I spent a lot of time on looking at DNA damage responses and signal transduction and cancer genetics. Then I moved on to more biologics, antibody engineering, leading programs in antibody discovery, and then cell and gene therapies. So thank you very much. Very happy to be here.

Julia Sable (00:03:41):
Thank you, Manu. Hi, everybody. I am Julia Sable. I am the director of CMC Project Management for now Kite Therapeutics. I worked for Community Therapeutics. We were acquired as of last Thursday, so ignore my name tag. If you guys aren't familiar with Community, it is a project from Bruce Levine and Carl June, Jim Riley and Chu, really productive academic partnership. So my role at Community is like any small biotech is like a 5FER, so I am their CMC expert for plasmid lenti and analytical. So anything that we do with our CDMO.

(00:04:28):
I am the alliance management person for Penn. I work with things from binder discovery out through getting the data together and putting together the module two, module three portions for Penn sponsored and funded INDs. We also bring those same data in and leverage them for Community products. And prior to that I was at Legend Biotech, so I built out their tech ops lenti space for viral vector. Again, Community's solid and heme, same thing at Legend. So had an experience there. Worked with a lot of CDMOs. They had an interesting approach of taking the same products to multiple CDMOs and looking at that and then ultimately leveraging all that knowledge to build some in-house capability.

(00:05:22):
The nice thing is obviously to watch that BLA go out for [inaudible 00:05:28], so learned a lot from working with the J&J collaboration from the vector side and from the cell therapy side. So before that I was at Merck running an oncolytic virus program and that was great to watch a new asset come in and go through full process development. I had 20 years before that academically, so it was a really big juxtaposition to go from boutique AV, rabies lenti making to full scale 500 liter or larger kind of production.

(00:05:59):
So yeah, I'm by nature a toolmaker, a virus maker and an imaging person. Liked a lot of the talks I heard today about PATs and other things. You could talk your face off about them. And I think very deeply, I think about the analytical challenges that we're going to face specifically in cell therapy as we start to not only go from autologous and allo but as we start to take things like autologous and go from a nine day or seven day to a three day or a one day. So that's my bag.

Alex Sargent (00:06:33):
Hello everybody. Can you guys hear me without the microphone? My name is Alex Sargent. Most people-

Nicholas Ostrout (00:06:41):
Sarge, they do want you speaking in the mic just for the video.

Alex Sargent (00:06:45):
My name is Alex Sargent. Most people, I'd say 95% know me as Sarge. People call me other things, but nothing I can repeat here. I'm currently the director of process development here at Charles River. A bit about me, I'm a neuroimmunologist by training. I actually started in mesenchymal stem cells back when they were going to cure every disease known to man. I was unfortunately disabused of that notion at some time and started my work in CAR T-cell therapies.

(00:07:19):
I started at Lonza, another CDMO. I have an undying love, shall we say, with allogeneic CAR T therapies and allo cell therapies in general. So a lot of time working at those. After Lonza, I went to another company where they were launching their CAR T pipelines, early clinical into clinical and IND enabling. That was for autologous first. So some experience building out from the ground zero. The story I like to tell about that experience is when I got there, they were growing their CAR T cells in shake flasks and they said, "Well, why? What else are we supposed to grow them in?" And I said, "I found the right place." After there, I got the wonderful opportunity to work here at Charles River where I get to work on a wide range of different technologies, pipeline projects, all stages, but still very passionate about CAR T-cells and happy to talk to you about that today.

Christian Cobaugh (00:08:17):
Hi, I'm Christian Cobaugh, the founding CEO of Vernal Biosciences, which is an mRNA manufacturing company based in northern Vermont. You might be wondering why would an mRNA manufacturer be on this esteemed panel of cell and viral development? And we're seeing an increasing amount of interest in mRNA as a critical raw material in the cell therapy space, and that's a difficult problem. The economics of that don't really add up, GMP for a raw material and cell therapy, which is also an order of magnitude more expensive.

(00:09:03):
I've been in mRNA medicines in various ways since 2013 when I was doing antibody discovery at Lexicon Pharmaceuticals and was part of the partnership that we formed with Moderna. From there, I went on to lead the mRNA program at Arcturus out in San Diego and then I spent several years at Translate Bio running their process development process analytics and drug discovery. It was there where I started to see how this new modality could really scale in terms of manufacturing.

(00:09:45):
When I left T Bio to go to Omega Therapeutics, unfortunately we had to outsource manufacturing. I say unfortunately because it was really challenging, which is ultimately what led me to start Vernal Biosciences, which is to solve some of the business and technical problems that we were seeing outsourcing at Omega. So the concept of scaling with quality is sort of what we started to do, but now we're starting to think about scale down with quality and to do that economically to serve all the new and exciting use cases for mRNA, whether that's personalized cancer vaccines where you got to go fast needle to needle or cell therapies where you might be making the same raw material for a program, but again, in a way that's cost-effective for the rest of the process.

Nicholas Ostrout (00:10:42):
Wonderful. Thanks guys. I've got a mic. So yeah, Manu can have it though if you want. I'll start with you anyway. I think Palani had a great line in his presentation this morning where he said he's just going to raise a bunch of issues but not really tell you the solutions. So when we think about cell therapies, it seems like a very integrated approach from the very beginning. There's things that you have to get right from discovery, particularly when you're developing your critical process parameters and your critical quality attributes that are going to then carry you through into your clinical trials.

(00:11:23):
So Manu, being on the scientific advisory services and really having that perspective, seeing clients come in at the early stages of their therapeutic development, what are some of the real critical roadblocks that you've seen or maybe give us an example of something and then maybe a solution that we're able to provide either within Charles River or elsewhere?

Manu Kohli (00:11:49):
Yeah, that's a great question. One of the major challenges I've seen many times with clients is how do they actually execute their IND enabling programs? And one thing that's interesting is that cell therapies don't follow traditional paths. So if you think about development of a small molecule or a biologic, there's very conventional paths that are usually executed. You do your optimization, you do SCR. If it's a small molecule, you do in vitro ADME, and then you do your IND enabling tox. For example, doing it like relevant species.

(00:12:24):
But cell therapies don't follow that because they're very complex modalities and one of the major problems is that there's no relevant species to actually test their efficacy and safety. And so a lot of times when clients come, they say, "How do we do this?" They have a great concept of their molecule, of their cell, they show efficacy in vitro and they say, "Well, how do we actually translate this?" And it is a problem and the FDA realizes this because these are very, very unique modalities with different ways you can transform. You can use lentivirus, transposons, mRNA, a lot of different things. They're living drugs, they're cells and it is not a straightforward path to actually take it to the next level.

(00:13:12):
And so that's the biggest challenge and that's one of the reasons we also say is to engage with the FDA and other regulatory agencies very early on to make sure that the path you're moving forward with makes sense. A lot of these programs are case by case, so I cannot say, okay, you have to do it this way. This is the best way to do it, because every modality is different. They have different parameters. Maybe if it's a bispecific CAR, if it's an in situ CAR, if you're taking lentivirus and injecting it or a nanoparticle in vivo, they all have different development paths. And so everything has to be customized based upon what you think is the best way to do it. So a lot of it comes to just thinking about what is the pharmacology, what are the safety considerations that you have to build out on?

(00:14:05):
The other thing too is that when you talk about early discovery, so a lot of the optimizations for cell therapies, especially for binding domains like CAR Ts happens very early on. You're looking at single chain variable fragments, VHHs, other types of things. Those optimizations have to happen very, very early before you even get to manufacturing and potency assets and things like that. And so those considerations are very important. Does ESCP aggregate? Is it humanized? Does it express adequately so you can actually scale?

(00:14:40):
These optimizations can be done at the sequence level of the SCFE of your binding domain, and those are very, very important in the early discovery phase that make sure that you have humanization, make sure that you have optimal expression, you have consistent expression, you don't have any downregulation or some spotty expression so forth. But what are the sources of your cells? Are you choosing high quality donors that have been characterized? That'll affect eventually the scale as well. I think that all these questions can be addressed very early. I think the biggest challenge that many people have is those optimizations, both in the binding domain and also determining how to move the therapy forward in the IND enabling studies.

Nicholas Ostrout (00:15:26):
Great, thanks. Julia, how about you? You've got a lot of experience from early R&D all the way into CMC, so maybe talk about one or two hurdles that you have come across.

Julia Sable (00:15:39):
There's so many.

Nicholas Ostrout (00:15:40):
Give some advice on how to prevent others from doing the same.

Julia Sable (00:15:44):
Okay, I'll ping to something he said. So when you're locked in at your construct level, whatever that might be, you have to make choices about where you're going to manufacture it, how you're going to manufacture it, do you even bother with tech transfer? And I've worked in situations in different companies where you just scrap everything that you don't even look at the R&D work, you just say, we're starting from zero, let's go.

(00:16:14):
I am a big advocate of trying to make sure that you can leverage R&D work and translate it into your CMC side and it's like two different languages to me. A lot of ways, and I'm sure he can add to this, but when you are making viral vector as a good example, most people will go the default way that they're used to making it inherent. It's got serum, it's got a lot of things. As a virus maker, I can tell you that that particle's going to be different than the one that you make in a stir tank reactor, and it's also going to be different than one you make in a fixed bed reactor. Do you have the capabilities of looking at all three of those? Do you have a runway to do that? Do you have time to do that?

(00:16:55):
My advocate situation would say, please spend some time on it because inherent is never going to get you to commercial scale. If you do, it's going to be an incredibly expensive and painful place to be. Most people assume that there's pros and cons and trade-offs. I would say from looking at the last five years, people have come up with really interesting production cells, additives, media formulations that have resolved some, maybe not all of the issues and there's a trade off. So if you do decide to go with an inherent platform and you're moving forward that way and you get really good proof of concept stuff in your early phase one, as you move into suspension or fixed bed, you want to start to think about your specifications are going to change.

(00:17:43):
And for those of you guys who don't speak CMC language, specifications kind of keep you up at night because what was really good at the beginning with one kind when you make it this way on a platform is going to be a completely different headache when you move to another side. I'm giving generalities, but I've seen this across a fairly broad range of CARs for autologous work and I'm assuming that it's probably something that fits into the other modality. So I might just hand this to you and tag team because I feel like you have a lot that you could add.

Alex Sargent (00:18:18):
There were a couple of good points brought there. The first is the manufacturability of your program. When you think about scale up and scale out, I've heard the word automate and automation a lot and I especially think for CAR Ts with the number of technologies that are available today and that list continues to grow, the rationale for automating, for closing up your process earlier and earlier is becoming stronger and stronger for programs. And so that's something I would definitely say it's good to think about at least early on.

(00:18:48):
Another thing that I often see neglected and touched upon this in earlier conversations is the assays. The number of CAR T programs I've seen where they don't even have a transduction or transection assay, they can't even speak to how many or what percentage of CAR T cells they're making is still quite astounding concerning that where we are at as a field. So I would say don't neglect either of those things even early on in R&D or preclinical pipeline. Oh, you have a mic.

Christian Cobaugh (00:19:20):
I got a mic. So coming from the raw material side, particularly in mRNA, one of the things we really struggle with is that there's very little purpose-built equipment for what we're trying to do. We're actually borrowing extensively from the cell therapy field. I recently hired a head of process development and he showed up with a giant chem glass reactor and said, "Why don't we just use these and throw them away after every use?" It was a pretty interesting take on the whole thing, but we're often overbuilt on what we're using. Thank goodness for single use technology though, because it's really decreased the burden on your quality and your validations team. Validate it once and then validate your cleaning, your change over procedures. And so getting creative as the CAR field evolves from cell type to cell type, you may not find the right process equipment for some of these emerging cell types.

(00:20:29):
We've also heard about the challenges of analytics and focusing on that. That was really the first thing that our company did was developed a QC package before we started producing anything. There's just no way to do proper QBD without being able to iterate off of your QC data. And again, many of us are kind of borrowing from other biochemical fields. It could be protein analytics, whether it's HPLC or even immunoassays. So keeping a real open mind about the types of people that you bring on board, they can readily transfer over from the protein space, from the antibody space into a fully integrated company that's working in the advanced therapeutics space. So really keeping an open mind. It's a lot of fun, it's very rewarding, but the vendors and technology providers have not really, I think, kept pace as fast as they should be, and part of that's just market driven. They're very conservative, but this cell and gene therapy is clearly here to stay and it's time for technology to catch up a little bit.

Nicholas Ostrout (00:21:49):
So it's actually a great segue. Each of you kind of talked about process characterization and analytical process analytics. Where are you seeing the conversion of people fully characterizing their product early versus the evolution that the product almost evolves as they're moving through in vitro and then in vivo and then even in a phase one? Maybe, Manu, you can start here in terms of what are you kind of seeing from the regulatory bodies in saying, this is when your assays need to be locked down and we're not going to allow you to go into even phase one unless you do X, Y, and Z versus how early the process characterization needs to occur?

Manu Kohli (00:22:41):
Yeah, so it's interesting because if you look at cell therapies compared to other types of therapies, a lot of times they fail because of efficacy or safety and so forth. But this is actually a little bit of reverse for cell therapies. Yes, there's issues with efficacy and safety, but more and more it's a lot of issue with CMC and potency and so forth compared to other types of modalities.

(00:23:05):
Typically, for example, potency assay is not needed until registration or after the BLA and so forth. But we are realizing that because there's variability in manufacturing and the quality of the cells and the lack of a quantitative potency assay, we want to move this much, much earlier. In fact, the FDA and other regulatory bodies have suggested that as early as possible you should start thinking about your CMC and your potency. And that makes a lot of sense because these are things that basically stop development and prevent it from actually coming into the market. But you want to have a way to ensure that you have good quality starting material, that you have as much characterization as you can in the very beginning and that you're thinking about the potency as soon as you start some of your discovery work. And so I think that we see that now shift much earlier than it was historically, and I think it is because a lot of them are failing for that reason that these assays are not in place.

Nicholas Ostrout (00:24:16):
Give it to Julia. I know she has some thoughts on this. You said something great in our early-

Julia Sable (00:24:22):
Let's just be honest about potency assays. The FDA is no joke coming in pre-phase one and saying you need them, you need them for every piece. You have a tricistronic, good luck. You're going to have to come up with three different assays. And what I've noticed so far is that we're all kind of skirting around the same idea. And I'll be a lot more blunt about this because I watched the FDA CBER talks and I'm like, just say what you're doing because we're all doing the same things. It's ridiculous at this point. There's no crazy novel modality. We're doing co-cultures, we're doing a proxy readout for a given set of things. If you decide to go with IL-2 versus interferon gamma or something like that, what subsets are you getting?

(00:25:10):
We can have a dialogue I think at this point to say that IL-2 has pros and cons because you're going to get CD4 and CD8, you're going to talk about interferon gamma, their potency assays are not correlated and they're not used for release. And there's a reason why, because your numbers are like Powerball numbers sometimes. You look at your output and go, what in the world is happening at my QC lab that something is coming out with this type of variability? We have to be honest about that because that's not just a problem in my company or my past companies. That is everyone's problem.

(00:25:53):
That said, a lot of these are flow-based methods. A lot of these are heavily raw material dependent in terms of what you're using. I'm a bigger molecular analytic advocate. We just don't have that in our toolkits right now. We do for specific things for clinical release, drug product release, most people are using qPCR. Advocate we should all just bite it and go to ddPCR because it's cleaner, the percent CV is nuts.

(00:26:27):
So within all of that, when you're doing a co-culture method, there's just not very much literature out there to help you support it if you're trying to go that way. It's heavily proprietary whatever. If you develop one and you know what you're going to do when you're going to a CDMO as a good example, do you own it? Can you tech transfer it? Can you bring it somewhere else? Those are all questions that people should be asking before you sign a contract, you should know this. Who owns it? Where are you taking it? What are you going to do with it later on? And what does the evolution of it look like?

(00:27:06):
If you've got a plan and you're going to give three outputs, all three of those outputs probably have to have plan A, plan B, hopefully not plan C. And then over time, if you get enough data, what can you throw out? It's iterative. It's like editing. You need to be able to go back and say, all right, I gave you the kitchen sink of where I'm going to go with this. By the time I get to commercial release, I want you to agree, gentleman's agreement, I don't know, wrong term, but I want you to agree that if I give you this now that you will be, I guess accommodating for me coming in with a reduced panel that's not going to ridiculously absorb all my product.

(00:27:52):
And this really gets back to when you are doing a process that's seven or nine days and it's really efficient, you have tons and tons of excess material, this is not your problem. You go to a three day process, you lost half your cells in that process, you still have to get all that release done. You still have to do all those other things. So from my end as a field, we have to just keep the pressure on the FDA to say, I have strong feelings about RCL with third generation lentis, we should not do those. We just don't. There's not been a case that's ever shown up. When do you get rid of that? How does that affect patient pain to vein time? These are normal conversations I want to see happening more frequently. So it's kind of why I agreed to step up here, and I'm probably going to get-

Nicholas Ostrout (00:28:40):
Well, we're glad you did.

Julia Sable (00:28:41):
... some email for that statement, but I feel like that's the way that we move ourselves.

Speaker 7 (00:28:46):
Do you mind repeating that? I actually missed your point.

Julia Sable (00:28:50):
What?

Speaker 7 (00:28:51):
The provocative statement.

Alex Sargent (00:28:55):
You're on record now.

Julia Sable (00:28:58):
I think we should get rid of RCL assays. I don't like them. I think that because the third generation, fourth generation lentis specifically, there's other modalities that have replication considerations. We should have a faster molecular assay than the current readout. RCL assay hasn't changed in 60 years. It takes too long for lenti, and we test at multiple points. If you test at the lenti and you're willing to take a 53 day whatever for that, that should be sufficient to not have it. And having an academic partnership really shows me what an academic institution is capable of doing in terms of a release versus us. And it's almost like a ... I appreciate it, but it's so frustrating because I look at what they do and I cringe because I know that I'm never going to be able to get away with that.

Nicholas Ostrout (00:29:53):
Your comment in one of our pre-sessions was, "They get away with murder."

Julia Sable (00:30:00):
They save a lot of people, but I asked Peter Marks outside of the conference when he finished, I said, "Does that mean you raise the standards of an academic institution to be closer to what commercial ... and inform them that's an education program that you have to give them so that they know what their expectations are? Or do you lower some of ours on the commercial side and not commercial, but the business side of things?" He said, "It's a delicate balance." We'll see.

Nicholas Ostrout (00:30:35):
Very political.

Julia Sable (00:30:36):
I think that's going to be one of our biggest challenges to getting things released to patients faster is the analytical landscape. To your point earlier, you have to think outside the box and get people to come in and just give them the same problem and let them leverage what they were doing in an R&D space or a PD space because that's where I find innovation and technology development. It just doesn't make it to the end.

Speaker 8 (00:30:59):
Why do you think those conversations are happening with people?

Julia Sable (00:31:06):
I think they're happening with people who have leverage to get rid of things. I know that the CBER talk, they talked about being able to get rid of things with enough data.

Speaker 8 (00:31:16):
That's been my experience too. If you can bring enough data, if you can validate against testing culture supernegative instead of testing cells [inaudible 00:31:31]

Julia Sable (00:31:31):
I'm team retain. I want to say you can keep all that and if you feel like at some point we have to go back and look, we keep them.

Speaker 8 (00:31:40):
You don't, for example, release on products tested on supernegative for example, rather than plus supernegative for certain kinds of assays. Well anyway, that's probably specific. I found that as long as one can bring a compelling data set, whether you're academic or industry, they're pretty open-minded, but you have to be able to show them the three.

Julia Sable (00:32:12):
And I think that's where if you're a large pharma and you can afford to do that or even a mid-size or just have a depth of product data, you could do that. But if you are a smaller biotech, how in the world are you ever going to get enough data to support that? You don't. You can get to phase one, maybe even a pivotal, but as a small company, you're going to need a partner to really drive home the reduction of those assets.

Speaker 8 (00:32:41):
This is probably [inaudible 00:32:45] but we'll come back to that later.

Nicholas Ostrout (00:32:47):
Sounds like a conversation.

Alex Sargent (00:32:50):
I will back you up on that. Seeing the academic centers come in, they do get away with a lot of things that we at CRL could never think of getting away with, and that is very challenging to translate then from an academic center into a GMP manufacturing facility into a CDMO. One thing I will add to that is an open-ended question of, should cell therapy be taken out of the manufacturing centers? Out of the academic centers? When should they be? How should they be? Someone once raised the point to me, biologics aren't being produced right at academic centers. Why are cell therapies being produced at the academic centers? Is that part of the failure of the industry or is it simply a matter of how we've made this model of producing cell therapies decentralized versus centralized for instance? So these are very tough questions that I think the industry has to reckon with.

Christian Cobaugh (00:33:50):
So on the raw material side, the number one CQA that we have to have locked down is identity. But beyond that, we're trying to give ourselves sufficient headspace as our client's programs move through development to show improvement in the specifications and the acceptance criteria. And sometimes that's through the evolution of the methods themselves. I want to come back to the potency assay though. I've happened to work on the same disease, the same gene four different times dating back to 2013 for clients and different companies. And first of all, what struck me as being more evolved in the advanced therapeutic space was the need to have cell potency assays, even for a phase one.

(00:34:47):
Jesse, I don't know if you recall in antibodies, but really we didn't even think about a cell-based potency assay until usually about phase three. If you had one before, then fine, but not always required. So we've really benefited from encouraging our clients or the companies that we work for to leverage a discovery-based asset to move that just straight into your cell-based potency assay and perhaps even use that as a discovery tool. But the demands have gotten higher and higher, even for phase one assets. Used to be with a gene transfer platform like mRNA, all you had to show was that on a Western blot you were making the protein that you said you were trying to make and you had to validate the antibodies that you were using to detect that.

(00:35:37):
And then it became, well, you have to show that that protein is active. So you extract it and show that it's enzymatically active, and now you have to show that it actually has a pharmacologic effect in those cells. That it's processing the substrate into the products and you have to use a heavy isotopically labeled substrates to demonstrate that. And eventually, I'm guessing by phase three and even commercial, that cell-based assay has to show exactly what's happening in your patients. So again, I can't emphasize enough building that connection between the development and the manufacturing team all the way back to the early stage discovery and being involved early so that you don't have to spend nine months in putting your programs on hold because you don't have an appropriate cell-based assay. These things take years to develop in some cases.

Alex Sargent (00:36:29):
And I'll add too, I may be a stickler here, but is it potency without clinical data, without a clinical readout, or is it really a functionality assay?

Nicholas Ostrout (00:36:39):
Well, I know I promised time for the audience, but I do have one more point that I want to raise with them real quick, the panel. We're already, gosh, 40 minutes into it, but I promise that I'll give the audience a chance here in just a second. So Peter Marks and Sarge, you and I have talked a lot about this previous, but Peter Marks said that you'd really have to think about manufacturing early and we hear about it all the time. Think about it with the end in mind. So we've heard a lot about build it yourself or outsource it. There's obviously different opinions, but a lot of cell therapy companies have built their own facilities and I think this has to do a lot with them being able to really get into that manufacturing nitty-gritty from a very early stage. Would you agree with that sentiment? Is that something that you see particularly working in Charles River now having manufacturing and the early discovery that you think is a real big benefit within CRL?

Alex Sargent (00:37:37):
It's definitely a big benefit, and I've been on both sides of the aisle. I've sat across from the CDMOs trying to get the external manufacturing contract when the company I was with really wanted to go towards internal manufacturing. So what does external manufacturing with the CDMO get you? And one thing to consider is it gets you the initial investiture and the capital and the experience and the equipment.

(00:38:04):
We talk about the process is the product. How well do you understand your process? Do you have the high throughput screening systems, the capabilities to really delve into your process and understand just fundamental aspects of the biology of what you're making? I think it's very interesting that out of everything I've seen, knocking out checkpoint inhibitors, fundamentally altering CAR construct design, is it possible that in the 10 year sense approval, the most significant advance in the CAR T field is something as simple as reducing the time you're culturing the cells? And why didn't somebody test that earlier on and say, huh, maybe we should look at that?

(00:38:50):
If you come to a place that has those resources, that has those systems and capabilities, that has that expertise, they may be able to early on guide the program to something that ultimately is more successful or at the very least is more well understood. So I would say the benefit of that cannot be outweighed if you're thinking about going with an external partner.

Manu Kohli (00:39:13):
Yeah, I completely agree with that. I think that because these are very complex modalities, as much as you can understand your CAR T product, from discovery through the development path, it really helps to have that in one place to really understand your product. So I think that one of the things that Charles River has tried to do is integrate a lot of these things under one roof, and I think that would really help optimize and ensure that you're getting a quality product in the end because everything is well characterized and well understood.

Nicholas Ostrout (00:39:48):
What I think Julia can talk about it from time at Legend and Community, I believe both of these companies had manufacturing internal, but I think that's maybe one of the differences with CRL versus other CDMOs is that you have that opportunity to do manufacturing and discovery in a single entity, whereas you don't with a lot of other CDMOs.

Julia Sable (00:40:09):
I was genuinely surprised when, what I hear from the two of you guys is that you're talking about FIO characterization data for your drug product, and those panels can be crazy complex. And I would say that at Legend they had two or three people who were really trying to leverage their manufacturer, the Raritan facility data that they were able to have. These aren't things that are released dependent, but if you build it in and you have a database of FIO work that you can really leverage at a manufacturing site, also at your PD site as you're building things out, I think that, again, standardization across companies will just happen because of the way that we mix.

(00:40:55):
People come and go in and out of CDMO and manufacturing roles kind of fluidly. That said, one FIO panel for one company might not be the same as the next. I've seen really, really complex and I've seen pretty straightforward. Both are valuable. It just depends on what you want to do with it when you go to present to the FDA, I think, because eventually that's where that FIO data becomes super important. It's characterization of your product over time, but anytime you do make any significant changes to your manufacturing process, et cetera, you have to have something to go back to.

(00:41:39):
So I'm speaking almost exclusively of flow-based methods, which have their pros and cons, but I feel like a lot of companies do do that from the R&D side through, and that seems to be what I see as an investment is even if you don't have in-house manufacturing, you do have some analytical capabilities that will allow you to validate the things that you think are important, even if you're not tech transferring them somewhere else.

Nicholas Ostrout (00:42:07):
All right, great. Well, with 15 minutes left, I do want to ask the audience if you have a topic that you want to raise and looks like we've got one already.

Speaker 7 (00:42:15):
One quick question. Thank you. Is the FDA asking for leukopak characterization at all? Are they starting to ask about how well characterized is your starting material? Because I'm seeing some companies pop up like leukopak processing, cleaning and kind of pre-treatment before a CAR T process actually starts.

Julia Sable (00:42:41):
I think there's a lot of variability in how you process your cells, what your start point is if you're fresh versus cryo. I've seen manufacturing CDMOs that have both options. Again, to your point, my understanding is if you cryo, you're going to probably add a day or two to your cell process, which eventually will make perhaps maybe not the best product.

(00:43:05):
So yeah, it's crazy when you look at leuk collection and even, I don't know if you guys know this, but Be The Match basically announced that they're no longer doing any autologous support, they're only doing allogenic. But they're the people who are responsible for doing site trainings at all of your clinical sites. So their absence is going to have a far effect and it's going to perhaps maybe regress or amplify the problem because you no longer have a standard centralized-

Nicholas Ostrout (00:43:42):
It's an opportunity for [inaudible 00:43:46].

Alex Sargent (00:43:46):
Gotta mention that.

Julia Sable (00:43:47):
Well, when we asked them who was going to be the ... Do they have a recommendation? They were like, "No, we're going to be done with this."

Nicholas Ostrout (00:43:55):
I was looking for Luca, but I don't think she's in here.

Alex Sargent (00:43:57):
I think to your point, Julia, some places get away with things that other places don't. We know this, especially in terms of leukopak characterization as a prime example. The question I would raise is just because the FDA isn't asking for it yet, should you be asking about it? And in my mind, if you want to understand the process, if you want to understand what you're making and putting into patients, then why not? At least in our facility and with our capabilities, that's a fairly easy thing to do at CRL and that's not burdensome in terms of time or cost. So why not do that if it's ultimately going to help your process and your product?

Speaker 8 (00:44:41):
I think fundamentally that's the answer to ... Thank you. I think fundamentally that's the answer to a lot of the characterization questions. It's not really so much a matter of is FDA interested in this or not? It's a matter of you really need this information in order to be able to really make your process work properly. You might not need it at phase one, and you might not need it if you're an academic center manufacturing for phase one two, but even at phase one, it's really, really useful to know this is the percent mononuclear cells, this is the degree of platelet and red blood cell contamination, and these are the ranges that we get. And if we do collections on the spectra Opvia things go well. But if we use fill in the blank name of other, things don't always go so well. That's information that's valuable, again, even at phase one. And it's trivially easy to get because any place that does an apheresis collection will have an automated hematology analyzer capable of giving you that information in exchange for a half note-

Julia Sable (00:45:53):
Yeah, basically. Things you can and can't get, if you ask, depending on your clinical site.

Manu Kohli (00:46:01):
Yeah, I completely agree with that. I think that one of the problems a lot of companies ask is what is needed by the FDA? But what they should be asking is what does the patient need? What is the level of validation or studies to say that this is efficacious and safe? So I think that if you think about in that way, then it makes everything else a little bit more clear. What does it need for this drug? And unfortunately, a lot of people don't think that way. They think that, okay, we have to do this because that's what's required. And that's very true for safety assessment for cell therapies. If you look at, for example, formally the guidance for tissue cross reactivity is not required for oncology products, but these are cell therapies that are long-lived. If you don't know what the cross reactivity is, there's toxicity that you cannot anticipate. So it makes a lot of sense to do it. And so I think that's the fundamental question is what is the right thing to do?

Speaker 9 (00:47:02):
How much of this fundamentally changes with the move to allo versus autologous?

Alex Sargent (00:47:10):
I would say, for instance, on the issue of donors, if you're an allo program, you better really understand your donor characteristics and what you want because that can make or break your allo program. It can be very expensive upfront, be honest with that. It can take some time, but especially for an allo program, it is so worthwhile.

Julia Sable (00:47:35):
I would just plug from a virus perspective, we are not considering as a field what the total cost of allo programs are going to be with the amount of virus. If you're using a virus, sorry, other modalities. If you're going to go with a virus, you're going to have to really consider, again, I'm not plugging a particular company, but supplementation or some other form of ... We're going to have to figure out how to make our producer cells' antiviral defenses turn down to get enough virus out of them to use the traditional vectors that we are well characterized and happy with because your starting material in a reactor is so much larger when you do allo versus it's the scale up approach. It would scale up or scale out. I don't care. You're just going to have to have enough vector to do that, and we don't. We could, it would be heroic effort, but the cogs on the total process like product cost would be really, really high.

Speaker 9 (00:48:47):
Well, does the scale at the allo side shift the effort towards using a CRO as opposed to bringing it in-house? Or is that a big enough change to really make that difference?

Julia Sable (00:48:58):
From a vector side or from a cell side?

Speaker 9 (00:49:00):
From the whole QC side.

Alex Sargent (00:49:04):
I think especially for large allo programs, it makes a certain amount of sense to go to a CRO/CDMO.

Julia Sable (00:49:12):
You make a choice. You go on, you say, I'm going to make my vector in the stir tank reactor. I'm going to make one that I can maybe scale up to a specific amount, but modular design or not, you're not going to have all of the flavors that you want. So the benefits of looking at A CDMO are how fast can you take a program across a 20, a 50, a 250 big enough? Do they have fixed bed and suspension that you can look at? To my earlier point, just what do you do with that and knowing what kind of products you get out of it.

(00:49:51):
So it's a complicated ask. I would argue that as we shrink or we try to go to shorter days of processing on drug product, it becomes the allo program because you're starting material could start for a seven, nine day process. You can start with 50 million cells and get where you need to be. If you're doing a three day process, you're looking at billions of cells. It's the same problem in autologous. Just to add in a little more fun there.

Nicholas Ostrout (00:50:24):
We have a couple more minutes left, so I guess I will open up another topic. Christian, something we've seen a lot coming down, at least for vector now, is the need for high quality or GMP even earlier in your safety studies. mRNA is relatively new to the game, but are you seeing that request come already or is RUO still sufficient?

Christian Cobaugh (00:50:52):
Well, right now, I think the regulatory guidance is pretty clear that whatever we're adding to a cell process, in our case with mRNA it's often gene editing. It's there to help get donor templates or some type of CAR or knockouts, immunogenic determinants. But the FDA has made it really clear that even though not a single atom of the mRNA is to get into the patient, it's treated as drug substance.

(00:51:34):
And so therefore, whatever phase appropriateness it's going to be GMP for now. We'd like to see some evolution there because it's just so difficult when we come back with a million dollar price tag on a raw material. It's a custom raw material. It's just not palatable for most companies. They have a certain amount that they can spend on raw materials, again, on a relatively expensive process. So there are ways for us to do this cheaper to go into the high quality arena that we've seen been used successfully with pDNA, but I just think to drive more innovation for different types of raw materials, our clients and the FDA are going to really have to sit down and work on this.

(00:52:36):
We certainly can play our part by giving support around how we do things, and even though it's perhaps done in a high quality way and not a GMP way, but there's still full traceability of raw materials. The process is highly controlled. It's just not running a $10,000 a day clean room. You just can't scale that way. So I'd like to see a little bit more thought put into the regulatory regimes around the things that are pretty distant from the patient.

Nicholas Ostrout (00:53:16):
Great. Well, we have five minutes left. We can start another topic if you want or we can take a five minute break before the campfires start. How's the audience feeling? I only see a few heads nodding, so do you have a question?

Speaker 10 (00:53:33):
Yeah.

Nicholas Ostrout (00:53:33):
All right.

Speaker 10 (00:53:34):
It'll only take 30 seconds.

Nicholas Ostrout (00:53:34):
We got four minutes left.

Speaker 10 (00:53:40):
Some of you mentioned the need for technology that is purposefully built and that is innovative. What are you excited about that is coming down the pipeline that is maybe not ready, that can be used in the process that would make your life easier?

Alex Sargent (00:53:57):
I would say me just briefly, we're switching from in cell therapy where there is, say, one technology, maybe two technologies for a given unit operation, a cruise unit operation to multiple options now. And so I'm excited to see that one, for competition, but two, I think we're going to be able to have better processes for cell therapy because we have more options in terms of technology.

Julia Sable (00:54:26):
I fully agree with that. I think in terms of closing up your process, there's a lot more things that are coming. And I think within, just to use Miltenyi as an example, they considered the fact that they didn't have a fill finish and they're bringing that on. I think it's out, I don't know. And they listen and they thought about it. You don't have to do container equivalency studies anymore because their little unit makes these little bags. So it reduces the barrier to long-term stability studies and stuff like that. So I think that's a good innovation.

(00:55:02):
From a lenti side or viral vector side period, there are so many exciting things that can be put onto PATs. There's Raman, there's Capacitance that is just getting to be way more large scale and they're doing a better job of showing the correlation. For biophysical characterization, Video Drop. I have no interest in any of these companies, I just think that they're really fun. High throughput things where you can basically get information not only about your virus but even the cells that are, in the case of an OV that I worked on, what's an OV look like at hour one, two, three, eight, et cetera? And they do that using just straight optics and you use a training set. So as you get better things like that, you can move them from offline into inline.

(00:56:00):
So for me, I feel like, yeah, if you're making viruses, I'd want to know about my batch as early as I can. I don't want to wait, sorry to analytical folks, three months for a plaque assay to come back and have me guess what I just did. I want to know instantaneously. And so that's one of those places, I'll use Merck as an example. In the process development side, we were able to put a full robotic system in and make a high throughput TCID, high throughput fluorescence based assays. None of those will make it to commercial product because as Luca Benetti, if you guys know him, he told me, he goes, "I need people in the field who can execute, and they're probably going to have a high school ..." Across the world. "They're going to have the equivalent to you of a high school degree." And he's not downgrading those people. He was just saying that the technologies that we develop that are helping us understand our processes are going to be very separate from the release assays that we use.

(00:57:04):
That said, as we miniaturize these things, as the cost of goods goes down on those things, I think you're going to see a shift in five to 10 years of light-based microscopy things or very manual operator subjective things, moving hopefully offline.

Speaker 10 (00:57:23):
Thank you.

Christian Cobaugh (00:57:31):
I would second Raman spectroscopy. It's got huge potential from the moment you get a raw material on the loading dock to the moment you're understanding your process.

Julia Sable (00:57:38):
I used to make fun of my friends who were in Raman at Columbia. I'm like, what does this thing do now? I'm like, oh, now I understand why it's useful.

Nicholas Ostrout (00:57:49):
Great. Well, thank you. Brian, I'll let you go if you can do it in a minute.

Brian (00:57:56):
Just yes or no, is there any room for modeling or AI or machine learning in any of these processes? Yes or no?

Julia Sable (00:58:05):
No.

Speaker 12 (00:58:05):
[inaudible 00:58:12].

Julia Sable (00:58:12):
What?

Speaker 12 (00:58:12):
[inaudible 00:58:14].

Julia Sable (00:58:14):
Yeah, no. Yeah, of course there is, but what's your training set?

Christian Cobaugh (00:58:22):
Well, but this is where CDMO I think really helps is the oceans of data that we sit on and relating the critical process parameters to that data. That's where I think obviously as a CDMO, we benefit from that, but all of our customers benefit from it, and we're very open with our customers about that. The data that has gone before you is being used in your project, and we have to explain that a little bit from a legal perspective, but there's no way that an innovator company can generate the amount of data that Charles River Labs has on certain unit ops. And so I think that if your CDMO is kind of focused on particular platforms as opposed to clean rooms for hire, then you should be asking how do you leverage the data that you've been collecting over the last several years since your inception?

Alex Sargent (00:59:24):
And I'll echo that. Everybody loves Raman spectroscopy. Everybody loves machine learning. Everybody loves DOE, but you need somebody that has the capability, somebody that has the size, somebody that has the data, and that's where a partner, a CDMO like CRL you can really leverage that.

Julia Sable (00:59:43):
I'll just put a plug from finishing a capacity search. There's a lot of big places that are CDMOs that don't have platforms and can't do that to your point. Because every single product they make is something specific to [inaudible 00:59:57]

Nicholas Ostrout (00:59:57):
Try to keep us on time and now we went over. So best laid plans. But thank you all for coming very much. Really appreciate the panel. Great insights. Grab a beer at the networking session with them. If you want to talk more and enjoy the campfires.