Evidence map›Paper›PMID 39663329›Full record

ArticleThe AAPS journal2024

Challenging the Standard Immunogenicity Assessment Approach: 1-Tiered ADA Testing Strategy in Clinical Trials.

Ching-Ha Lai, Mu Chen, Sasha Fraser, Jessica Wang, Sean McAfee, Emma Speaks, Nicholas Simeone, Jacqueline Rodriguez, Colin Stefan, Lisa DeStefano and 7 more

Abstract read
PubMed Publisher
In one paragraph

Article in The AAPS journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
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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

17 authors.

Ching-Ha LaiRegeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Road, Tarrytown, New York, 10591, USA. ching-ha.lai@regeneron.com.ORCID 0009-0008-4735-3926
Mu ChenRegeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Road, Tarrytown, New York, 10591, USA.
Sasha FraserRegeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Road, Tarrytown, New York, 10591, USA.
Jessica WangRegeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Road, Tarrytown, New York, 10591, USA.
Sean McAfeeRegeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Road, Tarrytown, New York, 10591, USA.
Emma SpeaksRegeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Road, Tarrytown, New York, 10591, USA.
Nicholas SimeoneRegeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Road, Tarrytown, New York, 10591, USA.
Jacqueline RodriguezRegeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Road, Tarrytown, New York, 10591, USA.
Colin StefanRegeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Road, Tarrytown, New York, 10591, USA.
Lisa DeStefanoRegeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Road, Tarrytown, New York, 10591, USA.
Chinnasamy ElangoRegeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Road, Tarrytown, New York, 10591, USA.
Matthew D AndisikRegeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Road, Tarrytown, New York, 10591, USA.
Giane SumnerRegeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Road, Tarrytown, New York, 10591, USA.
An ZhaoRegeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Road, Tarrytown, New York, 10591, USA.
Susan C IrvinRegeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Road, Tarrytown, New York, 10591, USA.
Albert TorriRegeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Road, Tarrytown, New York, 10591, USA.
Michael A PartridgeRegeneron Pharmaceuticals, Bioanalytical Sciences, 777 Old Saw Mill River Road, Tarrytown, New York, 10591, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ADA testing strategy for protein therapeutics was established almost two decades ago when assay methodologies were rudimentary, and serious immunogenicity-related safety issues had recently been observed with some biotherapeutics. The current testing paradigm employs multiple tiers and stringent cut points to minimize false negatives, reflecting a conservative stance towards ADA analysis. The development of highly sensitive ADA assay platforms and technologies such as humanized or fully human monoclonal antibody (mAb) drugs has put the traditional, resource-intensive 3-tiered testing approach under scrutiny. ADA data from clinical studies for three different mAb programs were re-assessed to explore the feasibility of a simplified 1-tiered ADA testing strategy with a 1% false positive cut point versus the traditional 3-tiered approach. The analysis demonstrated moderate to strong correlations between screening results (signal-to-noise, S/N) and those of confirmation and titer results, with the vast majority of samples (~ 97%) across all studies having the same ADA positive/negative classification with either testing approach. Furthermore, at the subject level, over 92% had the same ADA category (pre-existing, treatment-emergent, treatment-boosted) under both testing approaches. The re-categorized subjects had low titer ADA responses with no observed clinical implications on pharmacokinetics, efficacy, or safety. Finally, the treatment-emergent ADA incidences were comparable between the 1-tiered and 3-tiered approaches. The results demonstrate that the 1-tiered testing strategy is suitable for ADA assessment in these programs and is likely more widely applicable. Additionally, the 1-tiered approach could expedite data delivery and reduce resource needs in clinical development without compromising data quality or clinical interpretation.

Indexed as

Clinical Trials as TopicAntibodies, MonoclonalHumansAntibodies, MonoclonalADA incidenceADA testing approachAnti-drug antibodies (ADA)Immunogenicity

Identifiers

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.