Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, China; Department of Drug Metabolism and Pharmacokinetics, Hutchison Medipharma Ltd., Shanghai, China.
Eur J Pharm Sci. 2013 Nov 20;50(3-4):290-302. doi: 10.1016/j.ejps.2013.07.012. Epub 2013 Jul 31.
Verapamil and its major metabolite norverapamil were identified to be both mechanism-based inhibitors and substrates of CYP3A and reported to have non-linear pharmacokinetics in clinic. Metabolic clearances of verapamil and norverapmil as well as their effects on CYP3A activity were firstly measured in pooled human liver microsomes. The results showed that S-isomers were more preferential to be metabolized than R-isomers for both verapamil and norverapamil, and their inhibitory effects on CYP3A activity were also stereoselective with S-isomers more potent than R-isomers. A semi-physiologically based pharmacokinetic model (semi-PBPK) characterizing mechanism-based auto-inhibition was developed to predict the stereoselective pharmacokinetic profiles of verapamil and norverapamil following single or multiple oral doses. Good simulation was obtained, which indicated that the developed semi-PBPK model can simultaneously predict pharmacokinetic profiles of S-verapamil, R-verapamil, S-norverapamil and R-norverapamil. Contributions of auto-inhibition to verapamil and norverapamil accumulation were also investigated following the 38th oral dose of verapamil sustained-release tablet (240mg once daily). The predicted accumulation ratio was about 1.3-1.5 fold, which was close to the observed data of 1.4-2.1-fold. Finally, the developed semi-PBPK model was further applied to predict drug-drug interactions (DDI) between verapamil and other three CYP3A substrates including midazolam, simvastatin, and cyclosporine A. Successful prediction was also obtained, which indicated that the developed semi-PBPK model incorporating auto-inhibition also showed great advantage on DDI prediction with CYP3A substrates.
维拉帕米及其主要代谢物去甲维拉帕米被鉴定为 CYP3A 的机制基础抑制剂和底物，并在临床上报告具有非线性药代动力学。在人肝微粒体中首次测定了维拉帕米和去甲维拉帕米的代谢清除率及其对 CYP3A 活性的影响。结果表明，S-对映异构体比 R-对映异构体更优先代谢，对 CYP3A 活性的抑制作用也具有立体选择性，S-对映异构体比 R-对映异构体更有效。建立了一个半生理基于机制的药代动力学模型（半-PBPK），用于描述基于机制的自动抑制作用，以预测单次或多次口服剂量后维拉帕米和去甲维拉帕米的立体选择性药代动力学特征。获得了良好的模拟，表明所开发的半-PBPK 模型可以同时预测 S-维拉帕米、R-维拉帕米、S-去甲维拉帕米和 R-去甲维拉帕米的药代动力学特征。还研究了在维拉帕米缓释片（每天一次 240mg）第 38 次口服后自动抑制对维拉帕米和去甲维拉帕米积累的贡献。预测的蓄积比约为 1.3-1.5 倍，接近观察到的 1.4-2.1 倍的数据。最后，将开发的半-PBPK 模型进一步应用于预测维拉帕米与其他三种 CYP3A 底物（咪达唑仑、辛伐他汀和环孢素 A）之间的药物相互作用（DDI）。也获得了成功的预测，表明该模型在预测 CYP3A 底物的 DDI 方面也具有很大的优势。
