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Prediction and comparison of PD-1 receptor occupancy in the tumor after treatment with immune checkpoint inhibitors
Poster Title: Prediction and comparison of PD-1 receptor occupancy in the tumor after treatment with immune checkpoint inhibitors
Submitted on 06 Jul 2020
Author(s): Dmitry Shchelokov, Oleg Demin Jr
Affiliations: InSysBio, Moscow, Russia
This poster was presented at AACR Virtual Annual Meeting II
Poster Views: 218
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Poster Information
Abstract: Background: Measurements of receptor occupancy (RO) are believed to provide the necessary information on the pharmacodynamic efficacy of immune checkpoint inhibitors. However, only blood data are often available, whereas virtually nothing is known about RO at the site of action due to difficulties in tumor/tissue sampling. Besides, analysis of clinical data revealed highly controversial results of RO measurements for the same antibodies (e.g., maximal PD-1 occupancy by nivolumab 70-80% or 100% at the same doses) that raise the question about experimental procedures of RO determination and interpretation of the results. This work aims to predict and compare RO in the tumor for several anti-PD-1 therapeutics (nivolumab, pembrolizumab, INCMGA00012 (MGA012), dostarlimab (TSR-042), MEDI0680, sintilimab (IBI308), cemiplimab (REGN2810)) based on the previously developed PBPK/RO model.
Methods: Developed PBPK/RO model describes biodistribution of antibodies (mAb) within body fluids, detailed transport across endothelial barrier, two-step binding with membrane-bound PD-1 receptor (taking into account target expression level, number of cells expressing target receptor and internalization process), linear and non-linear clearance of mAb (via uptake by endothelium and internalization of mAb:PD-1 complexes, respectively). Physiological parameters were taken from literature, while other parameters were identified on the basis of available in vitro and in vivo data. Clinical data on PK of anti-PD1 mAbs, RO in blood and tumor were used only for model validation.
Results: Clinical PK data at various doses and regimens of anti-PD1 mAbs are captured by the model without any fitting. Moreover, the model allows to correctly describe heterogeneous data on RO in plasma using two different approaches: normalization to baseline quantity of receptor and normalization to the total quantity of receptor at each time point during measurements. To evaluate the impact of binding parameters (Kd, koff) on predicted trough PD-1 occupancy in tumor simulations were conducted over the wide range of Kd values at 3 mg/kg IV dosing Q3W. The model shows that mAbs against PD-1 receptor with a dissociation constant less than 3 nM demonstrate trough RO ≥ 90% at the chosen dosing regimen. Nevertheless, a direct comparison of approved doses for nivolumab (240 mg Q2W) and pembrolizumab (200 mg Q3W) revealed that predicted trough RO in the tumor is quite similar (93.98% vs 92.57%, respectively) despite the almost 100-fold difference in Kd values.
Conclusions: The proposed PBPK/RO model is able to predict PK of anti-PD-1 mAbs and RO in blood and tumor without the prior fitting of clinical data. Moreover, predictions of PD-1 occupancy in the tumor may be used for informed dose selection or explanation of clinical trial results. This approach can be expanded for mAbs targeting other receptors including bi- or multispecific antibodies with different structures and properties.
Summary: Structure of PBPK model was developed on the basis of published minimal PBPK model with additional modifications. Block
describing dynamics of membrane-bound target (PD-1) was implemented in the current model to
describe receptor occupancy (RO) in plasma and tumor compartment. Thus, PBPK/RO model was
developed to describe/predict PK of PD-1 inhibitors and was validated against clinical data on nivolumab,
pembrolizumab, MGA012, TSR-042, MEDI0680, IBI308, JS-001,
SHR-1210, AGEN
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