Quantitative prediction of human pharmacokinetic drug-drug interactions and drug clearance using humanized liver chimeric mice: a review
Abstract
Humanized liver chimeric mice, including hu-PXB, hu-FRG, and hu-TK-NOG mice, have emerged as valuable tools for predicting human pharmacokinetics in drug discovery and development. These models, featuring human hepatocytes transplanted into immunodeficient mice, bridge the gap between traditional preclinical models and clinical studies by enabling direct evaluation of human drug disposition in vivo. This review comprehensively examines the quantitative assessment of drug-drug interactions (DDIs) and clearance using these models. For metabolism-mediated interactions, humanized mice accurately reproduce the cytochrome P450 (CYP)3A, CYP2C9, and UDP glucuronosyltransferase-mediated DDIs observed in humans, enabling precise estimation of fraction metabolized values even for low-clearance compounds, although the amount of validation data is limited. For transporter-mediated interactions, studies demonstrate comparable organic anion transporting polypeptide1B and P-glycoprotein-mediated DDI magnitudes between the humanized mice and humans, with accurate prediction of hepatic fraction transported values. Drug elimination studies show strong correlations in drug clearance between humanized mice and humans when accounting for physiological differences. Despite limitations including residual murine metabolic activity and physiological abnormalities, humanized liver chimeric mice provide mechanistic and quantitative predictions of human pharmacokinetics. These models support compound selection, dose optimization, and clinical trial design throughout drug discovery and development.
Fields of Study & Subjects
Pharmacogenetics and Drug Metabolism
Drug Transport and Resistance Mechanisms
Receptor Mechanisms and Signaling
Publication details
- Journal / source
- Drug Metabolism and Pharmacokinetics
- Publisher
- Elsevier BV
- Volume
- 67
- Pages
- 101517–101517
- Publication date
- 8 January 2026
- Language
- EN