Comparison Across Anti-PD-1 Antibodies - Insights from QSP-Based Meta-Analysis

Poster Abstract


Check-point inhibitors have dramatically changed the field of immuno-oncology. Targeting PD-1 in particular has had a profound effect in a variety of cancers, as a single therapy and in combinations [1]. Currently, four anti-PD-1 antibodies have been approved by the FDA  - pembrolizumab, nivolumab, cemiplimab [2], and dostarlimab [3], with several others in development [4]. A model-based analysis comparing the level of target occupancy (TO) these antibodies achieve at their efficacious doses can provide insights into their efficacy profiles and guidelines for future anti-PD-1’s in the discovery and development stages.


A three-compartment (central, peripheral, and tumor) model with literature-informed PD-1 target burden and turnover was constructed. Besides pembrolizumab, nivolumab, cemiplimab, and dostarlimab, several other therapeutics were included in the analysis, among which vopratelimab, spartalizumab, camrelizumab, toripalimab, MGA012, and  MEDI0680. For each antibody of interest, dosing regimen in different indications, pharmacokinetics, and binding affinity were taken from the literature. TO at the tumor was compared across the molecules of interest. An “ideal” molecule with standard pharmacokinetics and optimized affinity and dosing regimens was identified and its TO was simulated and compared to the current therapeutic field of anti-PD-1s.


According to the model, high levels of TO are achieved by the approved molecules at their current dosing regimens. Sensitivity analysis indicates that the different dosing regimens necessary to achieve efficacy for different indications using the same antibody are likely dependent on disease-specific PD-1 expression and level of tumor penetration.


It would be challenging for a newly developed anti-PD-1 to achieve a higher TO than what is shown by the currently approved therapeutics. Differentiation by a niche indication, unique combination/modality, subcutaneous dosing, or price, should be considered during the discovery/development stages.


[1] Alsaab HO, Sau S, Alzhrani R, et al. PD-1 and PD-L1 Checkpoint Signaling Inhibition for Cancer Immunotherapy: Mechanism, Combinations, and Clinical Outcome. Front Pharmacol. 2017;8:561. Published 2017 Aug 23. doi:10.3389/fphar.2017.00561

[2] Twomey, J.D., Zhang, B. Cancer Immunotherapy Update: FDA-Approved Checkpoint Inhibitors and Companion Diagnostics. AAPS J 23, 39 (2021).


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