Physiologically-based pharmacokinetic modeling of rosuvastatin in Chinese: Predicting the impact of SLCO1B1 and ABCG2 genetic variants and hepatic impairment on drug exposure.
AI interpretation is pending for this paper.
Open original publication →What the AI sees
Not AI summarized yet.
Research significance
Pending deeper interpretation.
Source abstract
BACKGROUND: Although rosuvastatin is widely prescribed in China, its pharmacokinetic profile shows substantial interindividual variability, primarily due to polymorphisms in drug transporters (SLCO1B1 and ABCG2) and variations in hepatic function. Existing physiologically based pharmacokinetic (PBPK) models, primarily developed for Caucasian populations, may lack predictive accuracy in Chinese patients, highlighting the need for population-specific models to support precision dosing. METHOD: A PBPK model was developed using PK-Sim® software (Version 12.0) and validated using clinical pharmacokinetic data within the 5-20 mg dose range. Key transporter parameters were mechanistically optimized to reflect the functional impacts of SLCO1B1 c.521T>C and ABCG2 c.421C>A variants. The model was subsequently applied to simulate pharmacokinetic alterations associated with hepatic impairment. RESULTS: The model demonstrated robust predictive performance, with fold errors (FE) for primary pharmacokinetic parameters (Tmax, Cmax, and AUC0-t) ranging from 0.54-1.83-fold relative to observed values. The impact of genetic polymorphisms was accurately characterized, with FE values ranging from 0.62- to 1.33-fold. In patients with Child-Pugh class C cirrhosis, systemic exposure (AUC0-t) increased 3.13-3.16-fold compared with healthy subjects, indicating clinically significant hepatic accumulation. CONCLUSION: This is the first Chinese-specific PBPK model for rosuvastatin that successfully integrates genetic and hepatic covariates, allowing for the prediction of exposure differences due to SLCO1B1/ABCG2 polymorphisms and hepatic impairment. This model provides a valuable tool to guide future clinical dose adjustments in Chinese populations.