Semiphysiologically based pharmacokinetic models for the inhibition of midazolam clearance by diltiazem and its major metabolite.
Prediction of the extent and time course of drug-drug interactions (DDIs) between the mechanism-based inhibitor diltiazem (DTZ) and the CYP3A4 substrate midazolam (MDZ) is confounded by time- and concentration-dependent clearance of the inhibitor. Semiphysiologically based pharmacokinetic (PBPK) models were developed for DTZ and MDZ with the major metabolite of DTZ, N-desmethyldiltiazem (nd-DTZ), incorporated in the DTZ model. Enzyme kinetic parameters (k(inact) and K(I)) for DTZ and nd-DTZ were estimated in vitro and used to model the time course of changes in the amount of CYP3A4 in the liver and gut wall, which in turn, determined the nonlinear elimination of MDZ and DTZ, and the corresponding DDI. The robustness of the model prediction was assessed by comparing the results of the prediction to published DTZ pharmacokinetic and DTZ/MDZ interaction data. A clinical study was conducted to further validate the predicted increase of MDZ exposure after DTZ treatment. The model predicted the nonlinear disposition of DTZ after single and multiple oral doses. The clinical study showed that DTZ treatment resulted in 4.1- and 1.6-fold increases in MDZ exposure after oral and intravenous MDZ administration, respectively, suggesting that the DDI in the gut wall plays an important role in the DTZ/MDZ interaction. The semi-PBPK model incorporating the DDI at the gut wall, and the effect of nd-DTZ successfully predicted the nonlinear disposition of DTZ and its interaction with MDZ. Moreover, model simulation suggested that both DTZ and nd-DTZ contributed to the overall inhibitory effect after DTZ administration, and the values of the in vitro estimated inhibition parameters and CYP3A4 turnover rate are critical for the prediction.
Department of Pharmacy Practice, School of Pharmacy and Pharmaceutical Sciences, Purdue University, Indianapolis, Indiana, USA.
Xin
X
Zhang
Sara K
SK
Quinney
J Christopher
JC
Gorski
David R
DR
Jones
Stephen D
SD
Hall
D000284:Administration, Oral; D000328:Adult; D001711:Biotransformation; D003198:Computer Simulation; D051544:Cytochrome P-450 CYP3A / Q000378:metabolism; D065692:Cytochrome P-450 CYP3A Inhibitors; D004110:Diltiazem / Q000008:administration & dosage / Q000031:analogs & derivatives* / Q000097:blood / Q000493:pharmacokinetics*; D004347:Drug Interactions; D004791:Enzyme Inhibitors / Q000008:administration & dosage / Q000097:blood / Q000493:pharmacokinetics*; D005260:Female; D006801:Humans; D007262:Infusions, Intravenous; D007408:Intestinal Absorption / Q000187:drug effects; D007422:Intestines / Q000187:drug effects* / Q000201:enzymology; D008099:Liver / Q000187:drug effects* / Q000201:enzymology; D008297:Male; D008874:Midazolam / Q000008:administration & dosage / Q000097:blood / Q000493:pharmacokinetics*; D008954:Models, Biological; D017711:Nonlinear Dynamics; D011446:Prospective Studies; D015203:Reproducibility of Results; D055815:Young Adult
D065692:Cytochrome P-450 CYP3A Inhibitors; D004791:Enzyme Inhibitors; D051544:Cytochrome P-450 CYP3A; C510163:CYP3A4 protein, human; D004110:Diltiazem; C052825:N-monodemethyldiltiazem; D008874:Midazolam