ArticleBioanalysis2026
From tiers to truth - a biomarker-based framework for clinically relevant immunogenicity assessment.
Article in Bioanalysis, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Immunogenicity is a biological response to pharmacologic therapeutic intervention and therefore fits squarely within established definitions of a biomarker. Yet, unlike most biomarker assays, where analytical performance is tailored to context of use, anti-drug antibody (ADA) testing has converged on a largely uniform, three-tiered paradigm built around statistically derived cut points and titer reporting. This perspective argues that this approach arose from understandable, risk-averse responses to rare, high-impact safety events, combined with early analogies to the vaccine field, rather than from first principles thinking aligned with drug development needs.As a result, immunogenicity datasets are often reduced to binary classifications that discard biological context, inflate reported incidence, and complicate efforts to relate immune responses to clinically meaningful outcomes such as pharmacokinetics, pharmacodynamics, efficacy, or safety. Titer-based readouts, while appropriate for large vaccine-like responses, are frequently insufficiently granular to capture the full spectrum of response magnitudes relevant to contemporary biotherapeutic modalities.Reframing immunogenicity as a context-of-use-driven biomarker measurement leverages complete, continuous response profiles (e.g. screening-tier signal-to-noise) alongside pharmacokinetic/pharmacodynamic (PK/PD), and clinical outcomes to identify clinically relevant immunogenicity thresholds. This approach preserves nuance, improves interpretability and stakeholder communication, and focuses attention on clinical impact most relevant to patients and regulators.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.