Using physiologically based pharmacokinetic modelling to optimize repaglinide and irbesartan dosing in Chinese population with SLCO1B1 polymorphism.

AIM: The first aim of this study was to develop physiologically based pharmacokinetic (PBPK) models for irbesartan (IRB) and repaglinide (REP) and then apply the REP/IRB PBPK model to describe the drug-drug interaction (DDI) of REP and IRB in the population with SLCO1B1 c.521 T > C gene polymorphism. Second, the REP/IRB model was used to predict REP exposure under different administration protocols and provide dose adjustment recommendations for the population with SLCO1B1 c.521 T > C gene polymorphism. METHOD: The PBPK model was developed from literature and laboratory data, some parameters in the PBPK model were optimized and data from published clinical studies were used to evaluate the PBPK model. RESULT: The REP/IRB PBPK model showed good performance for accurately describing the plasma concentration-time profiles, area under the plasma concentration-time curve (AUC), maximum plasma concentrations (Cmax) and peak times (Tmax). The REP/IRB PBPK model predicted that, compared to the population with SLCO1B1 c.521TC genotype, in the population with SLCO1B1 c.521TT genotype, co-medicating with IRB significantly increased the exposure of REP. When co-administered with 300-mg IRB in patients with the SLCO1B1 c.521TT genotype, REP should be given either 2 h earlier or 4 h later (AUC0-∞ ratio: 0.90-0.97), or at 60-70% of the initial dose (AUC0-∞ ratio: 0.99-1.10), depending on available dosage strengths. CONCLUSION: A PBPK model was built for REP and IRB and used to predict DDI for the population with SLCO1B1 c.521 T > C gene polymorphism. Moreover, the model was applied to provide individualized drug recommendations for the SLCO1B1 c.521TT genotype population.