"Several currently approved cancer therapeutics are based on the use of monoclonal antibodies (mAbs). Current downstream processing of mAbs based on protein A chromatography is expensive and novel separations techniques can lead to significantly reduced costs. We have demonstrated efficient separation using a precipitation-based laboratory process, including developing systems engineering techniques to provide improved data for analytics and scale-up.
Efforts to develop CAR-T based therapeutics for cancer face several manufacturing challenges. The autologous CAR-T ""vein-to-vein"" manufacturing process includes leukapheresis, isolation of lymphocytes, T-cell enrichment, activation, transduction, CAR-T expansion, quality control and infusion. For autologous treatment, the donor variability represents a major uncertainty.
We review the sequence of unit operations that lead to the final therapeutic and the differences in manufacturing costs due to level of automation. The major objective of our effort is to develop advanced automated analytics and decision-making techniques to reduce clinical trial and treatment time and increase the number of patients that can be treated simultaneously. Different bioreactors for T-cell expansion can lead to different T-cell differentiation states and thus reduced exhaustion and better efficacy.
We encourage the development of decision support tools that integrate data from lab studies, clinical trials, and real-world treatment, and include the immune system and microbiota, for enhanced treatment decision-making. Continuous updates as more patient data is made available can lead to better treatment recommendations and outcomes."