(W-066) PHYSIOLOGICALLY BASED PHARMACOKINETIC MODELING OF PIOGLITAZONE: EVALUATING THE EFFECT OF THE CYTOCHROME P450 2C8*2 SINGLE NUCLEOTIDE POLYMORPHISM

Daniel Gonzalez, Clinical Pharmacologist – Associate Professor in Medicine, Division of Clinical Pharmacology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina;, Division of Duke University School of Medicine, Durham, North Carolina;; Christina Aquilante, Clinical Pharmacy – Professor Director of Pharmacogenomics for the Colorado Center for Personalized Medicine, Department of Pharmaceutical Sciences, Colorado University/University of Colorado Health, Skaggs School of Pharmacy, Aurora, Colorado, Colorado University/University of Colorado Health, Skaggs School of Pharmacy, Aurora, Colorado; Klarissa Jackson, PhD,Assistant Professor, Division of Pharmacotherapy and Experimental Therapeutics – Assistant Professor, Division of Pharmacotherapy and Experimental Therapeutics, Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina

Objectives: Pioglitazone is approved for the treatment of type II diabetes mellitus. Pioglitazone is mainly metabolized by cytochrome P450 (CYP) 2C8. CYP2C8 single nucleotide polymorphisms (SNPs) show unique distributions across ancestry populations. The CYP2C8*2 allele, occurring in up to 28% in African Americans (AA), is associated with decreased CYP2C8 function and may impact the pharmacokinetics of pioglitazone.1 The purpose of this study was to develop a physiologically based pharmacokinetic (PBPK) model of pioglitazone in a population of AA carriers of CYP2C8*2.

Methods: We leveraged a published PBPK model of pioglitazone disposition in Caucasian carriers of CYP2C8*3,2 occurring in up to 23% in people of European ancestry, to assess pioglitazone drug-gene interactions in a population of AA carriers of CYP2C8*2. The model integrates in vitro and in vivo drug specific data and accounts for the abundance of enzymes. The model assumes that pioglitazone is metabolized by CYP2C8 only. CYP2C8*2 and CYP2C8*1 alleles were incorporated into the model, assuming that the Michaelis Menten parameter Km changes within sub-populations, to account for the differences in metabolism for the AA population. The model was evaluated using 204 observations collected from 16 healthy AA volunteers given a single oral 15 mg dose of pioglitazone, as reported previously by Aquilante et al.1 Seven participants were CYP2C8*1/*1 genotype, and nine were CYP2C8*2 carriers. Individual simulation prediction was compared to the observed data. Pioglitazone gene interaction was evaluated by comparing the predicted parameters of CYP2C8*2 vs. CYP2C8*1/*1 in AA.

Results: For the CYP2C8*1/*1 genotype, the mean simulated versus observed AUC0-48 and Cmax were 6510 vs. 7075 ng*h/ml and 811 vs. 777 ng/ml, respectively. For the CYP2C8*2 carriers, the mean simulated versus observed AUC0-48 and Cmax were 9318 vs. 10187 ng*h/ml, and 860 vs. 809 ng/ml, respectively. For CYP2C8*1/*1, the simulated total plasma clearance was 0.61 ml/min/kg and the calculated intrinsic clearance was 31.14 ml/min/mg microsomal protein. For the CYP2C8*2 carriers, the simulated total plasma clearance was 0.43 ml/min/kg, and the calculated intrinsic clearance was 18.52 ml/min/mg microsomal protein. Compared to CYP2C8*1/*1, CYP2C8*2 carriers had 40% lower hepatic intrinsic clearance (Vmax/Km) and 30% lower simulated total plasma clearance.

Conclusions: The developed PBPK model allowed for the comparison of pioglitazone clearance in both CYP2C8*1/*1 and CYP2C8*2 allele carriers in the AA population. The parameter estimates matched the observed values reported by Aquilante et al.

Citations: [1] Aquilante CL, Wempe MF, Spencer SH, Kosmiski LA, Predhomme JA, Sidhom MS. Influence of CYP2C8*2 on the pharmacokinetics of pioglitazone in healthy African American volunteers. Pharmacotherapy. 2013;33(9):1000-1007.
[2] Türk D, Hanke N, Wolf S, et al. Physiologically Based Pharmacokinetic Models for Prediction of Complex CYP2C8 and OATP1B1 (SLCO1B1) Drug-Drug-Gene Interactions: A Modeling Network of Gemfibrozil, Repaglinide, Pioglitazone, Rifampicin, Clarithromycin and Itraconazole. Clin Pharmacokinet. 2019;58(12):1595-1607.