Overcoming Challenges With Preclinical Modeling for Cell Therapy in Autoimmune Disease

Tiffany Chen, PhD
Credit: GentiBio

Over the past year or so, there has been a rapidly growing interest among companies and academic institutions in bringing cell therapy modalities like chimeric antigen receptor T-cell (CAR-T) therapy and T-regulatory (T-reg) cell therapy from oncology to the field of autoimmune disease. One of the challenges with this however is the lack of well-established preclinical models for some autoimmune diseases and the general challenges of testing autologous cell therapies in animal models.

Tiffany Chen, PhD, the vice president of discovery at GentiBio, participated in a panel focused on these challenges at the Cell Therapy for Autoimmune Disease Summit, held November 28-30 in Philadelphia, Pennsylvania. Shortly after the panel, which was entitled “Developing Effective Pre-Clinical Models for Autoimmune Disease”, CGTLive® sat down with Chen to learn more.

CGTLive: Can you give some background context about the panel you spoke on?

Tiffany Chen, PhD: Prior to the panel, there were 2 seminar talks on preclinical models which was really nice to see. One presented on mouse models of systemic lupus erythematosus and how cell therapies could have impact there. The other talk was on nonhuman primate models and how cell therapies could have impact there, too. The objective of our panel was actually to talk about preclinical models and how they are related to the clinic and when moving different cell therapies into the clinic how we would weigh preclinical models and use that in our designs for either clinical trials or the products that we’re moving forward.

What were the key points discussed on the panel?

There was a lot of different pieces that were shared. I think an overarching thought was that preclinical models—they are just models—can give us a glimpse of something. One input that I had was it really helps us understand some of the pathophysiology of the disease and how our therapies could have impact there—but they are models and so they might not actually be directly translated to clinic. We have to take it with a grain of salt. Then depending on the risk tolerance of the organization that is moving a cell therapy to clinic, you can determine how much you would actually weigh preclinical models and preclinical model data.

What would you say are the main takeaways from the discussion for the healthcare community?

There's some diseases that have really well-established models such as lupus; there's very well established lupus models and for type 1 diabetes, also. So for certain different cell therapy companies, early proofs of concept are being generated there that could give a glimpse of hope. There's other disease indications that are quite difficult that might not actually have preclinical models established already. Based on that, the way we try to move cell therapies into clinic there is trying to figure out the best pharmacology package to do so. At a high level, there is a general sense of trying to weigh how much of those preclinical model data there is to take into there.

I think [another] aspect that physicians will find very important is the safety of these cell therapies since that has become a big question as a whole for cancer. The risk tolerance is just better there because patients have cancer—they have limited time—and so they're willing to take these. [For] autoimmune disease patients, that might not necessarily be the case. As such, ensuring there's really good safety in these cell therapies is very important. That's a different aspect that we did briefly cover. One thought is we do utilize a lot of the CAR-T history in this space and the safety that they have demonstrated to help support the other types of cell therapies that move forward. Then the specific type that my company works on, T-regs, may actually have a different type of safety profile compared to CAR-T therapies. A lot of that is just sharing the difference in mechanism of action and why we would potentially not have some of the safety risks that other cell therapies have.

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What are some of the challenges of preclinical modeling in this field right now?

I think one of the major challenges is how translatable these models are into clinic. As I mentioned, certain diseases indications have well-established models, but they [only] demonstrate the pathophysiology. They don't necessarily say “if I treat this model at this time, I can treat this patient this time”. That's probably one of the biggest challenges overall, between the preclinical models and also in clinic. The other aspect that's a really big challenge for cell therapy specifically is that the preclinical models for autoimmune diseases are mostly in mouse systems. You would need a mouse cell as a surrogate to demonstrate that. That's not necessarily reflective of the actual therapy that will go into humans so that's also a big challenge, too: What can you draw from mouse biology and equate it to human biology? There's other aspects: other companies have gone about using human cells in different types of mouse models, but they might not be as representative of the disease. There's these discrepancies as a whole that the field is working towards and understands that these are challenges.

Is there anything else you would like to share?

As a whole, I would say cell therapies in autoimmune diseases are very promising. The really great thing is we can harness a lot of the work that has been done in the oncology space to help expedite a lot of the work. Also, specifically for T-regs, there's very unique mechanisms that T-regs can utilize to help dampen down autoimmune disease that show a lot of promise. As a whole, I think we're at the cusp of it and for physicians and healthcare workers, as a whole, I would say welcoming them to ask the different companies or the different academic institutions that are working on this how they could benefit the disease indications that they're working with would be great because the community is always willing to share. There's a lot of learnings that have already been learned and could help support and bring new therapeutics to those fields.

This transcript has been edited for clarity.