Prediction of pharmacokinetic drug-drug interactions using human hepatocyte suspension in plasma and cytochrome P450 phenotypic data. II. In vitro-in vivo correlation with ketoconazole
Prediction of pharmacokinetic drug-drug interactions using human hepatocyte suspension in plasma and cytochrome P450 phenotypic data. II. In vitro-in vivo correlation with ketoconazole
复制标题
DOI：
10.1124/dmd.107.018796
复制
发表时间：
2008-07-01
影响因子：
3.9
通讯作者：
Balani, Suresh K.
中科院分区：
文献类型：
--
作者：
Lu, Chuang;Hatsis, Panos;Balani, Suresh K.
传统的基于细胞色素P450（P450）的药物-药物相互作用（DDI）预测是基于抑制剂的生理浓度[I]与其抑制常数Ki的比率。在酶位点确定[I]，尽管对于预测临床DDI至关重要，但仍然是一个技术挑战。在我们先前的研究中，研究了使用悬浮在人血浆中的冷冻保存的人肝细胞来模拟酮康唑在酶位点的体内浓度的新方法（Lu等人，2007），有效地消除了对难以捉摸的[I]值的估计。该系统中的P450抑制似乎模拟了体内的情况。使用人肝细胞血浆悬浮液中的酮康唑抑制信息以及定量P450表型信息，我们成功预测了一小部分药物的药代动力学DDI，如茶碱、甲苯磺丁脲、奥美拉唑、地昔帕明、咪达唑仑、氯雷他定、环孢素和阿普唑仑，以及一种研究化合物。为了在更大范围内适用该模型，需要扩展体外-体内相关性数据集。然而，对于文献中的大多数药物，没有足够的关于单个P450参与的定量信息来回顾性预测DDI。为了促进这一点，在这项研究中，我们确定了七种上市药物的定量P450表型：布地奈德，丁丙诺啡，氯雷他定，西罗莫司，他克莫司，多西他赛和甲基强的松龙。用先前生成的数据集扩充新数据集，产生了更广泛的数据库，为使用酮康唑作为强效CYP 3A抑制剂的该方法的更广泛适用性提供了进一步支持。预计该应用与不是外排泵底物的其他P450抑制剂同样有效。
Traditional cytochrome P450 (P450) based drug-drug interaction (DDI) predictions are based on the ratio of an inhibitor's physiological concentration [I] and its inhibition constant K-i. Determining [I] at the enzymatic site, although critical for predicting clinical DDIs, remains a technical challenge. In our previous study, a novel approach using cryopreserved human hepatocytes suspended in human plasma was investigated to mimic the in vivo concentration of ketoconazole at the enzymatic site (Lu et al., 2007), effectively eliminating the estimation of the elusive [I] value. P450 inhibition in this system appears to model that in vivo. Using the ketoconazole inhibition information in a human hepatocyte-plasma suspension together with quantitative P450 phenotypic information, we successfully predicted the pharmacokinetic DDIs for a small set of drugs, such as theophylline, tolbutamide, omeprazole, desipramine, midazolam, loratadine, cyclosporine, and alprazolam, as well as an investigational compound. For the applicability of this model on a wider scale the in vitro-in vivo correlation data set needed to be expanded. However, for most drugs in the literature there is not enough quantitative information on the involvement of individual P450s to predict DDIs retrospectively. To facilitate that, in this study we determined quantitative P450 phenotyping for seven marketed drugs: budesonide, buprenorphine, loratadine, sirolimus, tacrolimus, docetaxel, and methylprednisolone. Augmentation of the new data set with the one generated previously produced broader a database that provided further support for the wider applicability of this approach using ketoconazole as a potent CYP3A inhibitor. This application is predicted to be equally effective with other P450 inhibitors that are not substrates of efflux pumps.