A Physiologically Based Pharmacokinetic Model to Predict Pegylated Liposomal Doxorubicin Disposition in Rats and Human

Abstract The use of nanoparticles (NPs) can support an enhancement of drug distribution, resulting in increased drug penetration into key tissues. Experimental in vitro data can be integrated into computational approaches to simulate NP absorption, distribution, metabolism, and elimination (ADME) processes and provide quantitative pharmacokinetic predictions. The aim of this study is to develop a novel mechanistic and physiologically based pharmacokinetic (m-PBPK) model to predict the biodistribution of NPs focusing on Doxil.The main processes underpinning NPs ADME were represented considering molecular and cellular mechanisms such as stability in biological fluids, passive permeability, and uptake activity by macrophages. A whole-body m-PBPK rat and human models were designed in Simbiology v. 9.6.0 (MATLAB R2019a).The m-PBPK models was successfully qualified across doxorubicin and Doxil® in both rat and human since all PK parameters AUC0 − inf, Cmax, t1/2, Vd and Cl were within 2-fold, with an AUC0 − inf absolute average-fold error (AAFE) value of 1.23 and 1.16, and 1.76 and 1.05 for Doxorubicin and Doxil® in rat and human, respectively. The time to maximum concentration in tissues for doxorubicin in both rat and human models was before 30 minutes of administration, while for Doxil® the tmax was after 24 hours of administration. The organs that accumulate most NP are spleen, liver, and lungs, in both models.The m-PBPK represents a predictive platform for the integration of in vitro and formulation parameters in a physiological context to quantitatively predict the NP biodistribution.