Evidence map›Paper›PMID 38790133›Full record

ArticleCPT: pharmacometrics & systems pharmacology2024

Comparison of dose selection based on target engagement versus inhibition of receptor-ligand interaction for checkpoint inhibitors.

Sarah A Head, Carter Johnson, Saheli Sarkar, Andrew Matteson, Diana H Marcantonio, Fei Hua, John M Burke, Joshua F Apgar, David Flowers

Abstract readComparative StudyCase Reports
In one paragraph

Article in CPT: pharmacometrics & systems pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Anti-PD-(L)1 Antibodies: Insights From QSP-Based Meta-Analysis.CPT: pharmacometrics & systems pharmacology · 2026
    Pooled it
  2. Article
  3. Article
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

9 authors.

Sarah A HeadCertara, Concord, Massachusetts, USA.ORCID 0000-0002-8942-7785
Carter JohnsonCertara, Concord, Massachusetts, USA.ORCID 0000-0002-1599-4453
Saheli SarkarCertara, Concord, Massachusetts, USA.
Andrew MattesonCertara, Concord, Massachusetts, USA.
Diana H MarcantonioCertara, Concord, Massachusetts, USA.
Fei HuaCertara, Concord, Massachusetts, USA.ORCID 0000-0001-7728-2155
John M BurkeCertara, Concord, Massachusetts, USA.
Joshua F ApgarCertara, Concord, Massachusetts, USA.ORCID 0000-0002-3396-1874
David FlowersCertara, Concord, Massachusetts, USA.ORCID 0000-0002-7382-8461

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immune checkpoint inhibitors block the interaction between a receptor on one cell and its ligand on another cell, thus preventing the transduction of an immunosuppressive signal. While inhibition of the receptor-ligand interaction is key to the pharmacological activity of these drugs, it can be technically challenging to measure these intercellular interactions directly. Instead, target engagement (or receptor occupancy) is commonly measured, but may not always be an accurate predictor of receptor-ligand inhibition, and can be misleading when used to inform clinical dose projections for this class of drugs. In this study, a mathematical model explicitly representing the intercellular receptor-ligand interaction is used to compare dose prediction based on target engagement or receptor-ligand inhibition for two checkpoint inhibitors, atezolizumab and magrolimab. For atezolizumab, there is little difference between target engagement and receptor-ligand inhibition, but for magrolimab, the model predicts that receptor-ligand inhibition is significantly less than target engagement. The key variables explaining the difference between these two drugs are the relative concentrations of the target receptors and their ligands. Drug-target affinity and receptor-ligand affinity can also have divergent effects on target engagement and inhibition. These results suggest that it is important to consider ligand-receptor inhibition in addition to target engagement and demonstrate the impact of using modeling for efficacious dose estimation.

Indexed as

Antibodies, Monoclonal, HumanizedImmune Checkpoint InhibitorsDose-Response Relationship, DrugHumansLigandsModels, TheoreticalAntibodies, Monoclonal, HumanizedatezolizumabImmune Checkpoint InhibitorsLigands

Identifiers

PMID38790133
PMCPMC11179697

What OpenQuestion holds

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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.