Evidence map›Paper›PMID 34432389›Full record

ArticleClinical and translational science2022

Evaluation of atezolizumab immunogenicity: Clinical pharmacology (part 1).

Benjamin Wu, Nitzan Sternheim, Priya Agarwal, Julia Suchomel, Shweta Vadhavkar, Rene Bruno, Marcus Ballinger, Coen A Bernaards, Phyllis Chan, Jane Ruppel and 4 more

Abstract read
In one paragraph

Article in Clinical and translational science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 3 pooled it
–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

35 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  12. Structure-activity relationship ofEJNMMI radiopharmacy and chemistry · 2025
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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

14 authors.

Benjamin WuDepartment of Clinical Pharmacology, Genentech Inc., South San Francisco, California, USA.
Nitzan SternheimProduct Development Regulatory, Genentech Inc., South San Francisco, California, USA.
Priya AgarwalDepartment of Clinical Pharmacology, Genentech Inc., South San Francisco, California, USA.
Julia SuchomelDepartment of Clinical Pharmacology, Genentech Inc., South San Francisco, California, USA.
Shweta VadhavkarDepartment of Clinical Pharmacology, Genentech Inc., South San Francisco, California, USA.
Rene BrunoClinical Pharmacology, Genentech-Roche, Marseille, France.
Marcus BallingerProduct Development Oncology Clinical Sciences, Genentech Inc., South San Francisco, California, USA.
Coen A BernaardsProduct Development, Biostatistics, Genentech Inc., South San Francisco, California, USA.
Phyllis ChanDepartment of Clinical Pharmacology, Genentech Inc., South San Francisco, California, USA.
Jane RuppelBioAnalytical Sciences, Genentech Inc., South San Francisco, California, USA.
Jin JinDepartment of Clinical Pharmacology, Genentech Inc., South San Francisco, California, USA.
Sandhya GirishDepartment of Clinical Pharmacology, Genentech Inc., South San Francisco, California, USA.
Amita JoshiDepartment of Clinical Pharmacology, Genentech Inc., South San Francisco, California, USA.
Valerie QuarmbyBioAnalytical Sciences, Genentech Inc., South San Francisco, California, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Baseline patient characteristics and prognostic factors are important considerations in oncology when evaluating the impact of immunogenicity on pharmacokinetics (PK) and efficacy. Here, we assessed the impact of anti-drug antibodies (ADA) on the PK of the immune checkpoint inhibitor atezolizumab (an anti-PD-L1 monoclonal antibody). We evaluated data from ≈ 4500 patients from 12 clinical trials across different tumor types, treatment settings, and dosing regimens. In our dataset, ~ 30% of patients (range, 13-54%) developed treatment-emergent ADA, and in vitro neutralizing antibodies (NAb) were seen in ~ 50% of ADA-positive (+) patients. Pooled time course data showed a trend toward lower atezolizumab exposure in ADA+ patients, which was more pronounced in ADA+/NAb+ patients. However, the atezolizumab concentration distributions overlapped, and drug concentrations exceeded 6 µg/ml, the target concentration required for receptor saturation, in greater than 95% of patients. Patients had sufficient exposure regardless of ADA status. The dose selected to allow for dosing over effects from ADA resulted in a flat exposure-response relationship. Analysis of study results by ADA titer showed that exposure and overall survival were not affected in a clinically meaningful way. High tumor burden, low albumin, and high CRP at baseline showed the greatest association with ADA development but not with subsequent NAb development. These imbalanced factors at baseline can confound analysis of ADA impact. ADA increases atezolizumab clearance minimally (9%), and its impact on exposure based on the totality of the clinical pharmacology assessment does not appear to be clinically meaningful.

Indexed as

Pharmacology, ClinicalAntibodies, Monoclonal, HumanizedAntibodies, NeutralizingClinical Trials as TopicHumansImmune Checkpoint InhibitorsNeoplasmsAntibodies, Monoclonal, HumanizedAntibodies, NeutralizingatezolizumabImmune Checkpoint Inhibitors

Identifiers

PMID34432389
PMCPMC8742635

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Registered trials

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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.