Physiologically Based Pharmacokinetic Modeling of 3 HIV Drugs in Combination and the Role of Lymphatic System after Subcutaneous Dosing. Part 2: Model for the Drug-combination Nanoparticles

• Published in: Journal of pharmaceutical sciences 2022-03, Vol.111 (3), p.825-837
• Main Authors: Perazzolo, Simone, Shen, Danny D., Ho, Rodney J.Y.
• Format: Article
• Language: English
• Subjects: Drug Combinations; HIV; HIV Infections - drug therapy; Humans; Lopinavir; Lymphatic System; Lymphatic transport; Models, Biological; Nanoparticle; Nanoparticle delivery; Nanoparticles - chemistry; Nonhuman primates; PBPK; Quantitative systems pharmacology; Ritonavir; Subcutaneous pharmacokinetics; Tenofovir
• ISSN: 0022-3549; 1520-6017; 1520-6017
• DOI: 10.1016/j.xphs.2021.10.009

We previously developed a mechanism-based pharmacokinetic (MBPK) model to characterize the PK of a lymphocyte-targeted, long-acting 3 HIV drug-combination nanoparticle (DcNP) formulation of lopinavir, ritonavir, and tenofovir. MBPK describes time-courses of plasma drug concentration and has provided an initial hypothesis for the lymphatic PK of DcNP. Because anatomical and physiological interpretation of MBPK is limited, in this Part 2, we report the development of a Physiologically Based Pharmacokinetic (PBPK) model for a detailed evaluation of the systemic and lymphatic PK of drugs associated with DcNP. The DcNP model is linked to the PBPK model presented earlier in Part 1 to account for the disposition of released free drugs. A key feature of the DcNP model is the uptake of the injected dose from the subcutaneous site to the adjacent lymphoid depot, routing through the nodes within and throughout the lymphatic network, and its subsequent passage into the blood circulation. Furthermore, the model accounts for DcNP transport to the lymph by lymphatic recirculation and mononuclear cell migration. The present PBPK model can be extended to other nano-drug combinations that target or transit through the lymphatic system. The PBPK model may allow scaling and prediction of DcNP PK in humans.