Next-generation allogeneic cell therapies are inherently complex, but also hold advantages over autologous cell therapies. Namely, allogeneic cell therapies allow the manufacture of multiple therapies from a single healthy donor. These can be stored in a cell bank until needed by a patient. This process allows patients to receive the therapy quickly rather than needing to wait weeks for the manufacture of autologous cell therapy.
However, the complexity of allogeneic cell therapies cannot be minimized. This article will explore the challenges cell therapy developers encounter when setting up cell banks, strategies to reduce the complexity of human leukocyte antigen (HLA) matching in the development of allogeneic cell therapies, and keys to maximizing population coverage.
The HLA challenge
Allogeneic cell therapies rely on a healthy donor providing cells that will be infused into a patient. Physicians have used allogeneic cell therapies for decades in hematopoietic stem cell transplantation (HSCT), which does not require stem cell modification before patient infusion.
Allogeneic HSCT requires HLA matching to avoid donor cells attacking recipient cells, resulting in graft-versus-host disease (GVHD). This process also prevents recipient cells from attacking donor cells, which results in graft rejection.
This HLA challenge also exists with allogeneic cell therapies currently in development.
Two key reasons for the HLA challenge
The sheer diversity of HLA makes setting up an allogeneic cell bank to cover large populations of people problematic. On average, most people will not be the same at any HLA.
This is true in allogeneic HSCT. Even with tens of millions of potential donors on registries across the world, like Be The Match Registry®, an 8 of 8 match does not exist for every patient who needs HSCT.
Allogeneic HSCT requires a match for one patient from one donor. As such, allogeneic cell therapy developers are trying to build cell banks that target the population of an entire country or even the entire world.
The complexity of HLA typing is the second challenge for allogeneic cell therapy developers. Unambiguous HLA does not exist. There will always be a gap between what we know about a person’s phenotype and their actual phenotype.
Strategies to reduce the complexities of HLA
Allogeneic cell therapy developers can utilize strategies developed for allogeneic HSCT to reduce the complexities of HLA that will always be there.
One of those strategies is to use population genetics to make predictions about a specific individual. For example, the National Marrow Donor Program® (NMDP)/Be The Match® developed a matching algorithm—called HapLogicSM—that makes predictions based on haplotype frequencies to find donors or cord blood units for patients who need HSCT.
Existing data in global registries was gathered over long periods of time during which technologies have changed. HapLogic uses an imputation method for matching to normalize the data by looking at the complexity, context, and technologies used for typing to make educated guesses to more easily identify a match.
For example, a potential donor on the registry is only typed at three of five genes. HapLogic uses data from the collective to predict the variance at the two missing genes. A similar imputation method can be applied when building an allogeneic cell therapy bank to determine population coverage.
Additionally, cell therapy developers can use population genetics and frequency data to predict what patients might look like in the future in order to build a bank that would cover 95% of patients. However, these predictions are becoming more difficult because long-held principles of population genetics are no longer true. Using Be The Match Registry as an example, today more than one in five of the donors recruited answer categorically two different groups for race and ethnicity. The recent U.S. census shows this trend continuing.
Prediction methods must continue to evolve to meet the challenge of building a bank for the future patient.
New HLA goals in allogeneic cell therapies
It is important to note that new allogeneic cell and gene therapies are moving beyond traditional HLA matching. HLA goals today include functional targeting and avoiding, rejecting, and inducing specific immune functions.
However, HLA remains and having an 8 of 8 matches for every patient is not feasible. The goal must be to develop a therapy that mismatches in a manner that does not lead to rejection by most patients.
Gene-editing’s role in overcoming the HLA problem
Gene-editing technology is an essential part of any conversation about maximizing population coverage. However, this technology is not the answer to the HLA challenge, but another variable in the allogeneic cell therapy model.
Some gene editing could expand the number of patients covered by a treatment. Removing a gene, however, could introduce a new problem for certain HLA types. These issues can be factored into simulations for population coverage.
For example, a cell therapy developer may recommend removing three specific HLA genes to expand coverage. A simulation could show the match rates increase greatly by removing HLA-A. It may show, however, that the same is not true when removing HLA-B or HLA-C because variants of those two genes tend to stay together. Therefore, removing one of these two genes will impact coverage differently.
While gene editing will be a useful tool, gaining a better understanding of the genetic diversity of the world is the key to maximizing population coverage. Predictions are only as good as the data used. Understanding global diversity creates the potential for more precise predictions if we can model the HLA frequencies effectively for the global population.
A new challenge likely to emerge
One of the biggest challenges over the next five to 10 years may be for the health care providers administering allogeneic cell therapies, not for the developers.
Physicians will need to navigate a very complicated space. The pharmaceutical industry must provide a neutral way for physicians to access the menu of cellular therapies that may be suitable for their patients and, importantly, back it up with outcomes data.
This is an area where the donor registry community can help. For example, the CIBMTR® (Center for International Blood and Marrow Transplant Research®) has collected outcomes data for HSCT for 50 years. The organization expanded its efforts to develop a Cellular Therapy Registry that collects outcomes data on every FDA-approved CAR-T therapy as well as other cellular therapies. Physicians can use this evidence-based data to fuel their clinical decisions.
During this period of tremendous growth in the allogeneic cell therapy industry, cell therapy developers and companies with historical HLA experience must work together to overcome the HLA challenge. Their combined knowledge can accelerate the development of new therapies and bring them to patients sooner.