Physiologically based Pharmacokinetic Model Validated to Enable Predictions Of Multiple Drugs in a Long-acting Drug-combination Nano-Particles (DcNP): Confirmation with 3 HIV Drugs, Lopinavir, Ritonavir, and Tenofovir in DcNP Products

基于生理的药代动力学模型经验证可用于预测长效药物组合纳米颗粒 (DcNP) 中多种药物的药代动力学:以三种 HIV 药物(洛匹那韦、利托那韦和替诺福韦)在 DcNP 产品中的药代动力学为验证

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Abstract

Drug-Combination Nanoparticles (DcNP) are a novel drug delivery system designed for synchronized delivery of multiple drugs in a single, long-acting, and targeted dose. Unlike depot formulations, slowly releasing drug at the injection site into the blood, DcNP allows multiple-drug-in-combination to collectively distribute from the injection site into the lymphatic system. Two distinct classes of long-acting injectables products are proposed based on pharmacokinetic mechanisms. Class I involves sustained release at the injection site. Class II involves a drug-carrier complex composed of lopinavir, ritonavir, and tenofovir uptake and retention in the lymphatic system before systemic access as a part of the PBPK model validation. For clinical development, Class II long-acting drug-combination products, we leverage data from 3 nonhuman primate studies consisting of nine PK datasets: Study 1, varying fixed-dose ratios; Study 2, short multiple dosing with kinetic tails; Study 3, long multiple dosing (chronic). PBPK validation criteria were established to validate each scenario for all drugs. The models passed validation in 8 of 9 cases, specifically to predict Study 1 and 2, including PK tails, with ritonavir and tenofovir, fully passing Study 3 as well. PBPK model for lopinavir in Study 3 did not pass the validation due to an observable time-varying and delayed drug accumulation, which likely was due to ritonavir's CYP3A inhibitory effect building up during multiple dosing that triggered a mechanism-based drug-drug interaction (DDI). Subsequently, the final model enables us to account for this DDI scenario.

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