PURPOSE: To investigate the effect of OATP1B1 genotype as a covariate on repaglinide pharmacokinetics and drug-drug interaction (DDIs) risk using a reduced physiologically-based pharmacokinetic (PBPK) model. METHODS: Twenty nine mean plasma concentration-time profiles for SLCO1B1 c.521T>C were used to estimate hepatic uptake clearance (CLuptake) in different genotype groups applying a population approach in NONMEM v.7.2. RESULTS: Estimated repaglinide CLuptake corresponded to 217 and 113 μL/min/10(6) cells for SLCO1B1 c.521TT/TC and CC, respectively. A significant effect of OATP1B1 genotype was seen on CLuptake (48% reduction for CC relative to wild type). Sensitivity analysis highlighted the impact of CLmet and CLdiff uncertainty on the CLuptake optimization using plasma data. Propagation of this uncertainty had a marginal effect on the prediction of repaglinide OATP1B1-mediated DDI with cyclosporine; however, sensitivity of the predicted magnitude of repaglinide metabolic DDI was high. In addition, the reduced PBPK model was used to assess the effect of both CYP2C8*3 and SLCO1B1 c.521T>C on repaglinide exposure by simulations; power calculations were performed to guide prospective DDI and pharmacogenetic studies. CONCLUSIONS: The application of reduced PBPK model for parameter optimization and limitations of this process associated with the use of plasma rather than tissue profiles are illustrated.
PURPOSE: To investigate the effect of OATP1B1 genotype as a covariate on repaglinide pharmacokinetics and drug-drug interaction (DDIs) risk using a reduced physiologically-based pharmacokinetic (PBPK) model. METHODS: Twenty nine mean plasma concentration-time profiles for SLCO1B1 c.521T>C were used to estimate hepatic uptake clearance (CLuptake) in different genotype groups applying a population approach in NONMEM v.7.2. RESULTS: Estimated repaglinide CLuptake corresponded to 217 and 113 μL/min/10(6) cells for SLCO1B1c.521TT/TC and CC, respectively. A significant effect of OATP1B1 genotype was seen on CLuptake (48% reduction for CC relative to wild type). Sensitivity analysis highlighted the impact of CLmet and CLdiff uncertainty on the CLuptake optimization using plasma data. Propagation of this uncertainty had a marginal effect on the prediction of repaglinideOATP1B1-mediated DDI with cyclosporine; however, sensitivity of the predicted magnitude of repaglinide metabolic DDI was high. In addition, the reduced PBPK model was used to assess the effect of both CYP2C8*3 and SLCO1B1 c.521T>C on repaglinide exposure by simulations; power calculations were performed to guide prospective DDI and pharmacogenetic studies. CONCLUSIONS: The application of reduced PBPK model for parameter optimization and limitations of this process associated with the use of plasma rather than tissue profiles are illustrated.
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