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首页> 外文期刊>Drug Metabolism and Disposition: The Biological Fate of Chemicals >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.
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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.

机译:使用血浆中人肝细胞悬液和细胞色素P450表型数据预测药代动力学药物相互作用。二。与酮康唑的体内外相关性。

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摘要

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.
机译: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]及其抑制常数K(i)的比率。尽管对预测临床DDI至关重要,但在酶部位确定[I]仍然是一项技术挑战。在我们以前的研究中,研究了一种使用冷冻保存在人血浆中的冷冻人肝细胞的新方法来模拟酶部位的体内酮康唑浓度(Lu等,2007),从而有效地消除了难以估计的[I]值。在该系统中,P450抑制作用似乎可以在体内建立模型。使用人类肝细胞浆悬液中的酮康唑抑制信息以及定量P450表型信息,我们成功预测了茶碱,甲苯磺丁酰胺,奥美拉唑,地昔帕明,咪达唑仑,氯雷他定,环孢菌素和阿普唑仑的一小类药物的药代动力学DDI为了更广泛地应用此模型,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而言,关于单个P450参与程度的定量信息尚不足以追溯性预测DDI。为促进这一点,在这项研究中,我们确定了7种市售药物的定量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将产生更广泛的数据库,该数据库为使用酮康唑作为有效的CYP3A抑制剂的这种方法的更广泛应用提供了进一步的支持。预计该应用与不是外排泵底物的其他P450抑制剂同样有效。

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