Evidence map›Paper›PMID 42390068›Full record

ArticleBioanalysis2026

ADA assays for high-dose biologics: redefining drug tolerance through clinical insights.

Manisha Saxena, David Janik, Carsten Krantz, Annie St-Pierre, Maria Jadhav, Lydia Michaut, Florent Bender

Abstract read
In one paragraph

Article in Bioanalysis, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Manisha SaxenaNovartis Biomedical Research, PK Sciences, Basel, Switzerland.
David JanikNovartis Biomedical Research, PK Sciences, East Hannover, NJ, USA.
Carsten KrantzNovartis Biomedical Research, PK Sciences, Basel, Switzerland.
Annie St-PierreNovartis Biomedical Research, PK Sciences, Basel, Switzerland.
Maria JadhavNovartis Biomedical Research, PK Sciences, Cambridge, MA, USA.
Lydia MichautNovartis Biomedical Research, PK Sciences, Basel, Switzerland.
Florent BenderNovartis Biomedical Research, PK Sciences, Basel, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The validation of anti-drug antibody (ADA) assays is vital in biologics development, with regulatory bodies like EMA and FDA emphasizing drug tolerance. In patient care, drug tolerance assessments should reflect actual clinical use. We developed an ADA assay for a fully human monoclonal antibody used in oncology, addressing the challenges posed by high circulating drug levels and target biology. Various assay formats were tested using multiple positive controls and drug concentrations that mimic real-world exposure and drug-to-ADA ratios. Assessing different positive controls at various concentrations was key to characterizing sensitivity and drug tolerance. An assay initially showing low drug tolerance with one monoclonal control performed adequately with others. Rather than limiting assessments to a single sensitivity level, we evaluated assay performance using clinically relevant drug and ADA concentrations. This approach ensures the assay's sensitivity and drug tolerance are meaningful for patient management and therapeutic decisions. Early and ongoing collaboration with health authorities supported alignment of clinically relevant performance criteria and interpretation strategies. Ultimately, this patient-oriented strategy guarantees ADA results that inform patient safety and treatment effectiveness for high-dose biologic therapies.

Indexed as

Antibodies, MonoclonalBiological ProductsDrug ToleranceHumansAntibodies, MonoclonalBiological Productsanti-drug antibodyassay drug toleranceBiologicsNIS793target interferenceTGFβ

Identifiers

PMID42390068
PMCPMC13557555

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.