Best practices for the development, analytical validation and clinical implementation of flow cytometric methods for chimeric antigen receptor T cell analyses.

Chimeric Antigen Receptor (CAR) T cells are recognized as efficacious therapies with demonstrated ability to produce durable responses in blood cancer patients. Regulatory approvals and acceptance of these unique therapies by patients and reimbursement agencies have led to a significant increase in the number of next generation CAR T clinical trials. Flow cytometry is a powerful tool for comprehensive profiling of individual CAR T cells at multiple stages of clinical development, from product characterization during manufacturing to longitudinal evaluation of the infused product in patients. There are unique challenges with regard to the development and validation of flow cytometric methods for CAR T cells; moreover, the assay requirements for manufacturing and clinical monitoring differ. Based on the collective experience of the authors, this recommendation paper aims to review these challenges and present approaches to address them. The discussion focuses on describing key considerations for the design, optimization, validation and implementation of flow cytometric methods during the clinical development of CAR T cell therapies.

Best practices for optimization and validation of flow cytometry-based receptor occupancy assays.

In the development of therapeutic compounds that bind cell surface molecules, it is critical to demonstrate the extent to which the drug engages its target. For cell-associated targets, flow cytometry is well-suited to monitor drug-to-target engagement through receptor occupancy assays (ROA). The technology allows for the identification of specific cell subsets within heterogeneous populations and the detection of nonabundant cellular antigens. There are numerous challenges in the design, development, and implementation of robust ROA. Among the most difficult challenges are situations where there is receptor modulation or when the target-antigen is expressed at low levels. When the therapeutic molecules are bi-specific and bind multiple targets, these challenges are increased. This manuscript discusses the challenges and proposes best practices for designing, optimizing, and validating ROA.