Evidence map›Paper›PMID 39009791›Full record

ArticleThe AAPS journal2024

Immunogenicity of Atezolizumab: Influence of Testing Method and Sampling Frequency on Reported Anti-drug Antibody Incidence Rates.

Maxime Usdin, Valerie Quarmby, James Zanghi, Coen Bernaards, Laura Liao, Joel Laxamana, Benjamin Wu, Steven Swanson, Yuan Song, Patty Siguenza

Erratum issuedAbstract 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. An erratum has been issued. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Maxime UsdinGenentech Research and Early Development (gRED) Computational Sciences, Genentech, Building 45, 620 E Grand Ave, South San Francisco, California, 94080, USA.
Valerie QuarmbyIndependent Consultant, South San Francisco, California, USA.
James ZanghiIndependent Consultant, South San Francisco, California, USA. zanghij@gene.com.ORCID http://orcid.org/0000-0002-7457-6411
Coen BernaardsProduct Development Data Sciences, Genentech, Building 40, 600 E Grand Ave, South San Francisco, California, 94080, USA.
Laura LiaoProduct Development Data Sciences, Genentech, Building 40, 600 E Grand Ave, South San Francisco, California, 94080, USA.
Joel LaxamanaProduct Development Data Sciences, Genentech, Building 40, 600 E Grand Ave, South San Francisco, California, 94080, USA.
Benjamin WuClinical Pharmacology, Genentech, Building 46, 640 E Grand Ave, South San Francisco, California, 94080, USA.
Steven SwansonBioAnalytical Sciences, Genentech, Building 47, 660 E Grand Ave, South San Francisco, California, 94080, USA.
Yuan SongBioAnalytical Sciences, Genentech, Building 47, 660 E Grand Ave, South San Francisco, California, 94080, USA.
Patty SiguenzaBioAnalytical Sciences, Genentech, Building 47, 660 E Grand Ave, South San Francisco, California, 94080, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Measurement of anti-drug antibodies (ADA) to assess the incidence of ADA in a clinical trial is a critical step in immunogenicity assessment during the development of a protein therapeutic. We developed novel graphical approaches to illustrate clinical trial ADA data for the PD-L1 inhibitor atezolizumab (Tecentriq) that included a systematic analysis of the impact of the timing of ADA sampling and ADA assay drug tolerance on reported ADA incidence. We found that approaches used across the industry for ADA incidence analysis provide a limited view of immunogenicity in oncology studies, where ADA detection may be confounded by both drug dosage and patient attrition. Moreover, these approaches can miss important temporal information about the immune response. Our results demonstrated that the methodology of ADA assessment for the atezolizumab program was specifically designed to capture most ADA responses to ensure accurate reporting of ADA incidence. We further showed that the use of sparse sampling and/or ADA test methods with insufficient drug tolerance may result in a significant underreporting of ADA incidence. We conclude that the comparison of ADA incidence between different drugs can be highly misleading and that a test method with appropriate sensitivity in the presence of the drug and a clinical sampling scheme that is aligned with ADA responses to a drug is required to accurately report ADA incidence.

Indexed as

Antibodies, Monoclonal, HumanizedAntibodiesDrug ToleranceHumansImmune Checkpoint InhibitorsAntibodiesAntibodies, Monoclonal, HumanizedatezolizumabImmune Checkpoint Inhibitorsanti-drug antibodiesatezolizumabbiotherapeuticsdrug toleranceimmunogenicity

Identifiers

What OpenQuestion 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 OpenQuestion graph.