A Transcriptome-based model for improved CART Therapy

Performance Period: 3/15/2019 to 5/2/2021

An estimated 10-20% of CAR-T batches fail due to slow growth rates of Tcells during the expansion step of the process. Furthermore, the starting material for every batch differs in many ways including the distribution of phenotypes in the Tcell population, yet the final product specification is fixed. Tcell growth rates can be affected by levels of cytokines and different Tcell phenotypes respond differently to growth factors.

This project then aims to evaluate how levels of key cytokines affect the growth rate of important Tcell phenotypes, so as to promote a more consistent final product. To accomplish this, a properly scaled-down “bioreactor” must be used. Preliminary work will evaluate the capabilities of Redbud Technologies’ magnetic posts for providing mixing and improved oxygen transfer to Tcells growing on 96 well plates. With a cost per treatment of approximately $500K, preventing 20 batches per year from failing protocol growth specifications could result in a cost avoidance of $10M. The proposed approach of using microbioreactors and a transcriptomics-based mathematical model to optimize levels of cytokines for CART patients is at MRL level of 4-5 now and will proceed to level 6-7 with the hand-off to clinicians at the end of this project.