Anti‐ <scp>PD</scp> ‐(L)1 Antibodies: Insights From <scp>QSP</scp> ‐Based Meta‐Analysis

Checkpoint inhibitors that target PD-1 or PD-L1 have had a profound effect in a variety of cancers, both as a single therapy and in combinations. Meta-analyses suggest that monoclonal antibodies (mAbs) targeting PD-1 may yield better survival outcomes compared to anti-PD-L1 mAbs, however these conclusions are limited by a lack of direct clinical comparisons between the two classes. There is a shared hypothesis for the mechanism of action of these drugs: inhibition of the PD-1:PD-L1 signaling pathway through binding to either target. Using a Quantitative Systems Pharmacology (QSP) model-based analysis, we test whether differential inhibition of PD-1:PD-L1 complex formation (a surrogate for inhibition of the signaling pathway) is sufficient to explain the efficacy difference between anti-PD-1 and anti-PD-L1 mAbs observed in clinical meta-analyses. The model predicts that high levels of PD-1:PD-L1 complex inhibition are achieved by all the considered mAbs at their clinical dosing regimens, but it does not indicate that anti-PD-1 mAbs yield higher inhibition over anti-PD-L1s, in contrast to the meta-analyses. Significant model parameter variability and a bootstrap sampling analysis mirroring the comparison from Duan et al. (2020) do not change this conclusion. This suggests that anti-PD-1 and anti-PD-L1 mAbs are not differentiable based on PD-1:PD-L1 complex inhibition alone, and that the hypothesized shared mechanism of action of the two classes of drugs is incomplete.

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Publication Details

Journal
CPT Pharmacometrics & Systems Pharmacology
Published
2026-02-01
DOI
https://doi.org/10.1002/psp4.70195
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
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article

Anti‐ PD ‐(L)1 Antibodies: Insights From QSP ‐Based Meta‐Analysis

Sarah A. Head, Joshua F. Apgar, Diana H. Marcantonio, Andrew Matteson et al.
CPT Pharmacometrics & Systems Pharmacology
Cancer Immunotherapy and Biomarkers
article

Anti‐ PD ‐(L)1 Antibodies: Insights From QSP ‐Based Meta‐Analysis

Sarah A. Head, Joshua F. Apgar, Diana H. Marcantonio, Andrew Matteson, C. Johnson, David Flowers, John M. Burke, Deborah A. Flusberg, Georgi I. Kapitanov
article en

Abstract

Checkpoint inhibitors that target PD-1 or PD-L1 have had a profound effect in a variety of cancers, both as a single therapy and in combinations. Meta-analyses suggest that monoclonal antibodies (mAbs) targeting PD-1 may yield better survival outcomes compared to anti-PD-L1 mAbs, however these conclusions are limited by a lack of direct clinical comparisons between the two classes. There is a shared hypothesis for the mechanism of action of these drugs: inhibition of the PD-1:PD-L1 signaling pathway through binding to either target. Using a Quantitative Systems Pharmacology (QSP) model-based analysis, we test whether differential inhibition of PD-1:PD-L1 complex formation (a surrogate for inhibition of the signaling pathway) is sufficient to explain the efficacy difference between anti-PD-1 and anti-PD-L1 mAbs observed in clinical meta-analyses. The model predicts that high levels of PD-1:PD-L1 complex inhibition are achieved by all the considered mAbs at their clinical dosing regimens, but it does not indicate that anti-PD-1 mAbs yield higher inhibition over anti-PD-L1s, in contrast to the meta-analyses. Significant model parameter variability and a bootstrap sampling analysis mirroring the comparison from Duan et al. (2020) do not change this conclusion. This suggests that anti-PD-1 and anti-PD-L1 mAbs are not differentiable based on PD-1:PD-L1 complex inhibition alone, and that the hypothesized shared mechanism of action of the two classes of drugs is incomplete.

CPT Pharmacometrics & Systems PharmacologyVol. 15(2)
C4 Therapeutics (United States) (US)
Openalex Percentile: Top 66%
Cancer Immunotherapy and Biomarkers
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Anti‐ <scp>PD</scp> ‐(L)1 Antibodies: Insights From <scp>QSP</scp> ‐Based Meta‐Analysis — Sarah A. Head, Joshua F. Apgar, et al. · CPT Pharmacometrics & Systems Pharmacology (2026) | TGRS Research Map | TGRS