Physiologically-based pharmacokinetic modeling of gemfibrozil drug-drug interactions with the CYP2C8 victim drugs repaglinide and pioglitazone
Denise Tuerk (1), Nina Hanke (1) and Thorsten Lehr (1)
(1) Clinical Pharmacy, Saarland University, Saarbruecken, Germany
Objectives: Physiologically-based pharmacokinetic (PBPK) modeling is a valuable tool to describe and predict the extent of drug-drug interactions (DDIs) and to investigate the influence of perpetrator drugs on the pharmacokinetics (PK) of victim drugs. The lipid-lowering drug gemfibrozil [1] is recommended by the U.S. Food and Drug Administration (FDA) as a strong CYP2C8 inhibitor for the application in DDI studies [2]. The gemfibrozil phase-II metabolite gemfibrozil 1-O-β-glucuronide is the main cause of this strong inhibition, inactivating CYP2C8 in a mechanism-based manner [3]. Co-administration of gemfibrozil with the CYP2C8 victim drugs repaglinide and pioglitazone leads to 8.1-fold [4] and 3.4-fold [5] increases in the area under the curve (AUC) of repaglinide and pioglitazone, respectively. The objectives of this study were to develop a PBPK model of gemfibrozil and to predict the DDIs of gemfibrozil with repaglinide and pioglitazone.
Methods: A whole-body PBPK model of gemfibrozil was established with PK-Sim® modeling software (Version 7.2.0) [6,7]. Drug-dependent parameters and plasma concentration-time profiles of 23 clinical studies of gemfibrozil (oral application, single and multiple dosing, dosing range 30-900 mg) were taken from literature. Optimization of parameters that could not be informed from literature was accomplished using the studies of the internal data set, followed by evaluation of the predictive performance of the model by comparison of predicted and observed plasma profiles of the studies belonging to the external data set. Parameters describing the competitive inhibition of CYP2C8 by gemfibrozil and the mechanism-based inhibition of CYP2C8 by its glucuronide [8,3], as well as the competitive inhibition of OATP1B1 by both [9], were added to the gemfibrozil model. Lastly, the gemfibrozil model was coupled to previously developed models of repaglinide and pioglitazone [10].
Results: To mechanistically describe the strong inhibition of CYP2C8 by gemfibrozil, a parent-metabolite model was established. The gemfibrozil model includes an active uptake into hepatocytes, metabolism by UGT2B7 to form gemfibrozil 1-O-β-glucuronide and glomerular filtration. The gemfibrozil 1-O-β-glucuronide model applies an active uptake into hepatocytes via OATP1B1, transport via MRP3, a biliary clearance and glomerular filtration. The quality of the gemfibrozil model can be described by AUC ratios (AUC predicted / AUC observed), which show a low geometric mean fold absolute deviation (GMFE) of 1.15 (range 1.02-1.39, n=18). Application of the newly developed gemfibrozil model for DDI prediction shows that the plasma concentration-time profiles of the victim drugs (repaglinide and pioglitazone) are well predicted in case of gemfibrozil co-administration. Predicted vs. observed DDI AUC ratios (AUC DDI / AUC control) show a GMFE of 1.59 (range 1.07-3.27, n=13) for the gemfibrozil-repaglinide DDI and of 1.06 (range 1.03-1.08, n=2) for the gemfibrozil-pioglitazone DDI, indicating an adequate predictive performance of the PBPK models.
Conclusions: A PBPK model of the CYP2C8 inhibitor gemfibrozil including its metabolite gemfibrozil 1-O-β-glucuronide has been successfully established. The model precisely describes plasma concentration-time profiles of gemfibrozil over a wide dosing range. Furthermore, the model accurately predicts different co-administration scenarios of gemfibrozil with repaglinide and of gemfibrozil with pioglitazone and is a useful tool to investigate the DDI potential of CYP2C8 victim drugs or to inform the design of clinical DDI studies.
References:
[1] Saku K, Gartside PS, Hynd BA, Kashyap ML. Mechanism of action of gemfibrozil on lipoprotein metabolism. J Clin Invest (1985) 75(5): 1702-12.
[2] U.S. Department of Health and Human Services, Food and Drug Administration Center for Drug Evaluation and Research (CDER). Clinical drug interaction studies - Study design, data analysis, and clinical implications. (2017).
[3] Ogilvie BW, Zhang D, Li W, Rodrigues AD, Gipson AE, Holsapple J, Toren P, Parkinson A. Glucuronidation converts gemfibrozil to a potent, metabolism-dependent inhibitor of CYP2C8: implications for drug-drug interactions. Drug Metab Dispos (2006) 34(1): 191-7.
[4] Niemi M, Backman JT, Neuvonen M, Neuvonen PJ. Effects of gemfibrozil, itraconazole, and their combination on the pharmacokinetics and pharmacodynamics of repaglinide: potentially hazardous interaction between gemfibrozil and repaglinide. Diabetologia (2003) 46(3): 347-51.
[5] Deng LJ, Wang F, Li HD. Effect of gemfibrozil on the pharmacokinetics of pioglitazone. Eur J Clin Pharmacol (2005) 61(11): 831-6.
[6] Eissing T, Kuepfer L, Becker C, Block M, Coboeken K, Gaub T, Goerlitz L, Jaeger J, Loosen R, Ludewig B, Meyer M, Niederalt C, Sevestre M, Siegmund HU, Solodenko J, Thelen K, Telle U, Weiss W, Wendl T, Willmann S, Lippert J. A computational systems biology software platform for multiscale modeling and simulation: integrating whole-body physiology, disease biology, and molecular reaction networks. Front Physiol (2011) 2: 4.
[7] www.open-systems-pharmacology.org
[8] Kajosaari LI, Laitila J, Neuvonen PJ, Backman JT. Metabolism of repaglinide by CYP2C8 and CYP3A4 in vitro: effect of fibrates and rifampicin. Basic Clin Pharmacol Toxicol (2005) 97(4): 249-56.
[9] Hirano M, Maeda K, Shitara Y, Sugiyama Y. Drug-drug interaction between pitavastatin and various drugs via OATP1B1. Drug Metab Dispos (2006) 34(7): 1229-36.
[10] Tuerk D, Hanke N, Lehr T. Physiologically-based pharmacokinetic (PBPK) modeling of the CYP2C8 substrate pioglitazone. PAGE 26 (2017) Abstr 7107.