ReviewThe AAPS journal2025
Assessment of Neutralizing Antibody Activity in Clinical Studies: Use of Surrogate Measurements Instead of Stand-alone Assays.
Review in The AAPS journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Impact of Immunogenicity on Clinical Outcomes in Patients With Moderate-to-Severe Inflammatory Bowel Disease Receiving Subcutaneous Infliximab: A Post Hoc Analysis of the LIBERTY Trials.United European gastroenterology journal · 2026Trial
- Advanced assay design for characterizing anti-drug antibody responses in clinical serum samples.Bioanalysis · 2026Review
- Rethinking immunogenicity: an integrated approach reveals the PK/PD impact of pre-existing and drug-sustaining ADA.Bioanalysis · 2026Article
- Immunogenicity assessment for vidutolimod: a risk-driven approach for a simplified 1-tiered, singlicate anti-drug antibody testing strategy.Frontiers in immunology · 2026Article
- 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
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neutralizing antibodies (NAbs) to protein therapeutics have traditionally been assumed to be the most impactful subset of anti-drug-antibodies (ADA). NAbs can block the biotherapeutic from engaging its target impacting efficacy and may also cause serious safety events. Stand-alone NAb assays have been employed to detect neutralizing responses, often with reconfigured versions of other assays. These methods have historically been implemented in registrational trials for all molecules, and in early-stage studies for high risk biotherapeutics. However, data has demonstrated that NAb response and ADA magnitude are highly correlated. Additionally, the use of other markers to identify clinically relevant immunogenicity, such as apparent impact on pharmacokinetics (PK) or pharmacodynamics (PD), has been increasing. This manuscript reviews the available data on clinically meaningful immunogenic responses to biologics and proposes a risk-based strategy to determine if and when to employ a stand-alone NAb assay. For molecules with a high risk of safety consequences of immunogenicity (e.g., biological mimics) a NAb assay is recommended. However, for lower-safety risk molecules a stand-alone NAb assay does not enhance the interpretation of clinical data and is likely not needed. A combination of other assessments including ADA status, magnitude and persistence, PK, and PD (and efficacy) can be used as a surrogate for NAb assay data. Integration of data from all clinical evaluations is recommended by Health Authorities and can provide a more accurate overall assessment of neutralizing activity. This approach identifies clinically impactful downstream readouts of neutralizing activity without the need for a stand-alone NAb assay.
Indexed as
Identifiers
40804295What OpenQuestion holds
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.