Recommendations for Systematic Statistical Computation of Immunogenicity Cut Points

Today, the assessment of immunogenicity is integral in nonclinical and clinical testing of new biotherapeutics and biosimilars. A key component in the risk-based evaluation of immunogenicity involves the detection and characterization of anti-drug antibodies (ADA). Over the past couple of decades, much progress has been made in standardizing the generalized approach for ADA testing with a three-tiered testing paradigm involving screening, confirmation, and quasi-quantitative titer assessment representing the typical harmonized scheme. Depending on a biotherapeutic's structural attributes, more characterization and testing may be appropriate. Unlike bioanalytical assays used to support the evaluation of pharmacokinetics or toxicokinetics, an important component in immunogenicity testing is the calculation of cut points for the identification (screening), confirmation (specificity), and titer assessment responses in animals and humans. Several key publications have laid an excellent foundation for statistical design and data analysis to determine immunogenicity cut points. Yet, the process for statistical determination of cut points remains a topic of active discussion by investigators who conduct immunogenicity assessments to support biotherapeutic drug development. In recent years, we have refined our statistical approach to address the challenges that have arisen due to the evolution in biotherapeutics and the analytical technologies used for quasi-quantitative detection. Based on this collective experience, we offer a simplified statistical analysis process and flow-scheme for cut point evaluations that should work in a large majority of projects to provide reliable estimates for the screening, confirmatory, and titering cut points.