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EP38830
Abstract: Objectives: 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. The aim of this work is to predict RO in the tumor for anti-PDL1 antibodies (mAbs) using PBPK/RO modeling.
Methods: Developed PBPK/RO model describes the main features of mAbs disposition: intravenous administration, distribution within body fluids, fluid-phase uptake by endothelial cells, competition for neonatal Fc receptor (FcRn) binding with endogenous IgG in endosomal space, FcRn-dependent transcytosis and recycling by endothelial cells, degradation of unbound mAbs within endothelial cells, convective and diffusive transfer across blood vessel wall, binding with PDL1 receptor expressed on the surface of T cells and further internalization of the complex. Clinical data on four anti-PDL1 mAbs were used for model validation: atezolizumab, durvalumab, avelumab, BMS-93655.
Results: The model adequately described the PK profile of all tested drugs, as well as target receptor occupancy in plasma, without any additional parameter fitting. For instance, the predicted mean PDL1
occupancy on the T cells in the blood at the end of the cycle of 1 mg/kg of avelumab Q2W was 75%, whereas clinical data showed 76% [1]. Simulated trough PDL1 occupancy in the tumor for atezolizumab
840 mg Q2W, durvalumab 10 mg/kg Q2W, 800 mg Q2W avelumab were 99.75%, 99.9%, 99.95%, respectively. The results can be explained by similar Kd values and applied doses of these three approved anti-PDL1 mAbs.
Conclusions: PBPK/RO model for anti-PDL1 mAbs was developed and successfully validated against clinical data. Receptor occupancy in the tumor was predicted. This model can be used as a tool for the prediction of PDL1 RO for the other mAbs targeting PDL1 and to optimize dose, regimen at the early stages of drug development.Summary: PBPK/RO model for anti-PDL1 mAbs was developed and successfully validated against clinical data. Receptor occupancy in the tumor was predicted. This model can be used as a tool for the prediction of PDL1 RO for the other mAbs targeting PDL1 and to optimize dose, regimen at the early stages of drug development.References: [1] Heery et al. Lancet Oncol. 2017 May;18(5):587-598
Methods: Developed PBPK/RO model describes the main features of mAbs disposition: intravenous administration, distribution within body fluids, fluid-phase uptake by endothelial cells, competition for neonatal Fc receptor (FcRn) binding with endogenous IgG in endosomal space, FcRn-dependent transcytosis and recycling by endothelial cells, degradation of unbound mAbs within endothelial cells, convective and diffusive transfer across blood vessel wall, binding with PDL1 receptor expressed on the surface of T cells and further internalization of the complex. Clinical data on four anti-PDL1 mAbs were used for model validation: atezolizumab, durvalumab, avelumab, BMS-93655.
Results: The model adequately described the PK profile of all tested drugs, as well as target receptor occupancy in plasma, without any additional parameter fitting. For instance, the predicted mean PDL1
occupancy on the T cells in the blood at the end of the cycle of 1 mg/kg of avelumab Q2W was 75%, whereas clinical data showed 76% [1]. Simulated trough PDL1 occupancy in the tumor for atezolizumab
840 mg Q2W, durvalumab 10 mg/kg Q2W, 800 mg Q2W avelumab were 99.75%, 99.9%, 99.95%, respectively. The results can be explained by similar Kd values and applied doses of these three approved anti-PDL1 mAbs.
Conclusions: PBPK/RO model for anti-PDL1 mAbs was developed and successfully validated against clinical data. Receptor occupancy in the tumor was predicted. This model can be used as a tool for the prediction of PDL1 RO for the other mAbs targeting PDL1 and to optimize dose, regimen at the early stages of drug development.Summary: PBPK/RO model for anti-PDL1 mAbs was developed and successfully validated against clinical data. Receptor occupancy in the tumor was predicted. This model can be used as a tool for the prediction of PDL1 RO for the other mAbs targeting PDL1 and to optimize dose, regimen at the early stages of drug development.References: [1] Heery et al. Lancet Oncol. 2017 May;18(5):587-598
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