Lot-to-lot reproducibility, stability and life cycle management of antibody reagents for flow cytometry.

The increasing number of biopharmaceuticals, gene and cell therapies in development has seen a growing use of flow cytometry to measure biomarkers, generate pharmacokinetic data, assess immunogenicity and investigate target engagement. The importance of these data types and their inclusion in regulatory submissions mean that flow cytometry analyses are now expected to demonstrate robust performance and comply with both regulatory and scientific recommendations during their validation and subsequent use in sample analysis. The control of the 'critical reagents' commonly used in flow cytometry presents some specific challenges, particularly when an assay is required for use over a long period of time across different phases of a drug development program, or where it is deployed in complex, multisite clinical studies. This paper highlights some key challenges in flow cytometry reagent management with some of the strategies employed to control and monitor flow cytometry critical reagents.

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.