Statistical Methodology for Qualification of a Non-Clinical Risk Assessment Peptide:T Cell Proliferation Assay to Support Decision Making

Abstract

Antibody- and cell-mediated immune responses against biologics, should they occur, can impact treatment efficacy and potentially pose severe risks to patient safety. Therefore, developers have focused on advancing strategies to mitigate such unwanted immunogenicity. Opportunities to address immunogenicity early in the development process, particularly during the drug design phase, have been identified. In vitro and in silico tools that facilitate the identification and removal of sequence liabilities have been established. For example, human cell-based in vitro T cell assays can be used to identify and remove CD4+ T cell epitopes, which are known to play a critical role in the development of anti-drug antibodies against recombinant proteins products as well as the transgenes of gene and therapy. Despite their widespread use in the industry, most of these assays lack thorough characterization, which undermines confidence in the results and comparability across laboratories. In this study, concepts of immunogenicity bioanalytical assay validation for study design and analysis were applied to characterize an internal CD4+ T cell proliferation assay as fit-for-purpose. A statistical path was applied to establish data acceptance criteria for handling of replicates, positivity and negativity of a signal, and donor cohort size. A Bayesian analysis was also performed and is proposed as an approach for sequence de-risking decision making. The in-depth characterization of the CD4+ T cell proliferation assay described here allows for accurate interpretation of the assay outcomes, thereby enhancing confidence in using this approach for mitigating the immunogenicity of biologics by design.