Immunogenicity assays are biomarker assays: is the 3-tiered paradigm fit-for-purpose? An illustrative case study.

This perspective highlights challenges associated with implementation of the 3-tiered paradigm over the past two-plus decades. A case study is used to illustrate re-analysis of anti-drug antibody (ADA) data from a Phase 1 clinical study of a monoclonal antibody, applying a biomarker-oriented approach. Unlike traditional analyses that focus on "positive" responses defined by statistical cut points, this approach incorporates all data, including "negative" responses, to characterize complete response profiles.By leveraging signal-to-noise (S/N) and raw signal data from the screening tier, the analysis provides a more granular, contextualized view of immunogenicity. Placebo data further inform longitudinal variability within the study population. This approach demonstrably clarifies apparent baseline positivity, distinguishes true treatment-emergent responses, and reveals that some subjects classified as ADA-positive under the traditional paradigm reflect biological variability or low-level, clinically irrelevant responses.Continuous readouts such as S/N enhance interpretation relative to titers and enable earlier insight into response dynamics without requiring additional assay tiers. Collectively, these findings underscore limitations of the current paradigm, including potential inflation of incidence, loss of clinical context, and mischaracterization of program risk. A biomarker-based framework offers an opportunity to generate more informative immunogenicity data more efficiently, supporting improved decision-making and facilitating timely regulatory evaluation.