Physiologically-based pharmacokinetic model-based translation of OATP1B-mediated drug-drug interactions from coproporphyrin I to probe drugs

Abstract

The accurate prediction of OATP1B-mediated drug-drug interactions (DDIs) is challenging for drug development. Here, we report a physiologically-based pharmacokinetic (PBPK) model analysis for clinical DDI data generated in heathy subjects who received oral doses of cyclosporin A (CysA; 20 and 75 mg) as an OATP1B inhibitor, and the probe drugs (pitavastatin, rosuvastatin, and valsartan). PBPK models of CysA and probe compounds were combined assuming inhibition of hepatic uptake of endogenous coproporphyrin I (CP-I) by CysA. In vivo K_i of unbound CysA for OATP1B (K_i,OATP1B ), and the overall intrinsic hepatic clearance per body weight of CP-I (CL_int,all,unit ) were optimized to account for the CP-I data (K_i,OATP1B , 0.536 ± 0.041 nM; CL_int,all,unit , 41.9 ± 4.3 L/h/kg). DDI simulation using K_i,OATP1B reproduced the dose-dependent effect of CysA (20 and 75 mg) and the dosing interval (1 and 3 h) on the time profiles of blood concentrations of pitavastatin and rosuvastatin, but DDI simulation using in vitro K_i,OATP1B failed. The Cluster Gauss-Newton method was used to conduct parameter optimization using 1000 initial parameter sets for the seven pharmacokinetic parameters of CP-I (β, CL_{int, all} , F_a F_g , R_dif , f_bile , f_syn , and v_syn ), and K_i,OATP1B and K_i,MRP2 of CysA. Based on the accepted 546 parameter sets, the range of CL_{int, all} and K_i,OATP1B was narrowed, with coefficients of variation of 12.4% and 11.5%, respectively, indicating that these parameters were practically identifiable. These results suggest that PBPK model analysis of CP-I is a promising translational approach to predict OATP1B-mediated DDIs in drug development.

FIGURE 1

Blood concentration time profiles of CysA and blood concentration time profiles of CP‐I under base line conditions, or after CysA administration. (a) CysA was given to participants 3 h or 1 h before probe drug administration in the clinical study. Time zero was set when baseline CP‐I was determined (−3.5 h before probe drug administration). Then, CysA was administered at 0.5 h (−3 h) for 75 mg (blue), and 20 mg or 75 mg CysA (green and red, respectively) was given at 2 h on the same time scale. The solid lines represent the lines calculated using the fitted parameters (summarized in Tables 1 and 2). (b) Pharmacokinetic parameters (CL_int,all,unit) of CP‐I, and K_i,OATP1B were optimized by simultaneous optimization using the all data sets (20 and 75 mg [−1 h], and 75 mg [−3 h]). The solid lines represent the lines calculated using the fitted parameters. The optimized parameters are summarized in Tables 1 and 2

FIGURE 2

Simulation of dose‐dependent and dosing interval effects of CysA on the blood concentration time profiles of pitavastatin (a) and rosuvastatin (b). (a, b) Using K_i,OATP1B optimized for the CP‐I data, the dose‐dependent and dosing interval dependent effects of CysA were simulated using the PBPK models of pitavastatin a and rosuvastatin b given orally (0.2 and 1 mg, respectively) combined with the PBPK model of CysA. Pitavastatin or rosuvastatin was given 3 h or 1 h after CysA administration. Solid lines represented fitted lines, and broken lines represent the simulated lines. (c, d) C_max, C_maxR, AUC, and AUCR of pitavastatin c and rosuvastatin d were calculated by connecting their PBPK models to the CysA PBPK model using the three different K_i,OATP1B; K_i,OATP1B (CP‐I), optimized for CP‐I data; K_i,OATP1B (PTV or RSV), optimized for PTV or RSV data; K_i,OATP1B (CP‐I, corrected), optimized for CP‐I corrected by the in vitro K_i,OATP1B1 ratio. Blood concentration time profiles calculated using the K_i,OATP1B (PTV or RSV) are shown in Figure S1A, and those calculated using the K_i,OATP1B (CP‐I, corrected) are shown in Figure S1C. Values of C_max, C_maxR, AUC, and AUCR are summarized in Table S1 AUC, area under the plasma concentration time curve; AUCR, area under the plasma concentration time curve ratio; C_max, maximum plasma concentration; C_maxR, maximum plasma concentration ratio; CP‐I, coproporphyrin I; PBPK, physiologically‐based pharmacokinetic; PTV, pitavastatin; RSV, rosuvastatin

FIGURE 3

Time‐ and dose‐ dependency of OATP1B inhibition by CysA. (a) Time profiles of OATP1B inhibition by CysA were simulated at doses of 20, 75, 300, and 600 mg. The blood concentration time profiles of CysA at the doses of 20 mg and 75 mg were validated (Figure 1). Linearity in the pharmacokinetic parameters of CysA was assumed to calculate the blood concentration time profiles at 300 and 600 mg. (b) Simulation of CysA impact on the AUCR and C_maxR of pitavastatin and rosuvastatin. CysA is assumed to be administered at doses of 20, 75, 300, and 600 mg before 2 h to after 5 h of probe administration. AUCR, area under the plasma concentration time curve ratio; C_maxR, maximum plasma concentration ratio

FIGURE 4

CGNM analysis of the CP‐I plasma concentration with or without CysA administration, and distribution of parameter values of the initial and corresponding optimized values. (a) Summary of the plasma concentration time profiles of CP‐I using the optimized parameters generated in 1000 cases. The green lines represent the profiles using the parameter sets accepted based on the chi‐square distribution of SSR and elbow method (Figure S2A). (b) Violin plots of the initial and optimized parameters in the selected 546 parameter sets. In each plot, a gray area indicates the distribution of the parameter values, a black dot in the center indicates the median, a vertical bar indicates interquartile range, solid lines stretched from the bar indicate the 25 percentile and 75 percentile values, and broken lines indicate the lower and upper adjacent values. The units of values are shown in Table S2. CGNM, Cluster Gauss–Newton method; CP‐I, coproporphyrin I; SSR, sum of squares residual

FIGURE 5

Scheme of the workflow for predicting OATP1B‐mediated DDIs using an endogenous OATP1B biomarker in drug development. DDIs, drug–drug interaction