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.

Authors

Publication Details

Journal
Bioanalysis
Published
2026-05-27
DOI
https://doi.org/10.1080/17576180.2026.2677736
Primary Topic
Biosimilars and Bioanalytical Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Lauren Stevenson
Bioanalysis
Biosimilars and Bioanalytical Methods
article

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

Lauren Stevenson
article en

Abstract

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.

Bioanalysis
Peace, Justice and strong institutions
Openalex Percentile: Top 10%
Biosimilars and Bioanalytical Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.