Quantitative prediction of CYP2C9-mediated drug disposition using humanized mice

Drug clearance and drug-drug interactions (DDIs) are important in the pharmacokinetic assessment of investigational drugs, yet predicting in vivo fraction metabolized (f_m) and DDI intensity remains challenging, particularly for low-clearance compounds. This study demonstrates how human liver chimeric mice (hu-PXB mice) can predict CYP2C9-mediated drug disposition for low-clearance compounds in humans. To estimate human in vitro CYP2C9 fraction metabolized (f_{m,CYP2C9,in vitro}), 3 CYP2C9 substrates (phenytoin, tolbutamide, and warfarin) were incubated in human hepatocytes with or without sulfaphenazole (CYP2C9 inhibitor). The f_{m,CYP2C9,in vitro} was calculated based on hepatic intrinsic clearance. For in vivo estimation (f_{m,CYP2C9,in vivo}), clinical DDI data obtained using CYP2C9 inhibitors were analyzed to calculate f_{m,CYP2C9,in vivo} based on observed clearance changes. To evaluate human DDI predictability, the 3 drugs were administered intravenously to hu-PXB and SCID mice with or without CYP2C9 inhibitors (sulfaphenazole or tienilic acid). Clearance changes were calculated and compared among humans, hu-PXB mice, and SCID mice. Results showed that f_{m,CYP2C9,in vitro} values for phenytoin and tolbutamide were overestimated compared to f_{m,CYP2C9,in vivo}, whereas warfarin could not be evaluated under current conditions. Hu-PXB mice demonstrated a better correlation with humans in both clearance changes and absolute values compared to SCID mice. Notably, hu-PXB mice predicted CYP2C9-mediated DDI magnitude within 15% of clinical values and predicted clearance for CYP2C9 substrates within 2-fold of clinical values. These findings establish hu-PXB mice as a reliable preclinical model for predicting human CYP2C9-mediated drug disposition. SIGNIFICANCE STATEMENT: Human liver chimeric mice can accurately predict the clearance and magnitude of drug-drug interaction for CYP2C9 substrate drugs. Findings from humanized mice enable the selection of better candidates in drug discovery and facilitate the design of efficient clinical trials for investigational drugs.