Database analyses for the prediction of in vivo drug-drug interactions from in vitro data
Database analyses for the prediction of in vivo drug-drug interactions from in vitro data
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DOI：
10.1111/j.1365-2125.2003.02041.x
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发表时间：
2004-04-01
影响因子：
3.4
通讯作者：
Houston, JB
中科院分区：
文献类型：
--
作者：
Ito, K;Brown, HS;Houston, JB
目的理论上，可以使用抑制剂浓度（[I]）与抑制常数（Ki）的比值预测由代谢清除抑制引起的体内药物-药物相互作用的大小。本研究的目的是构建一个数据库，用于从体外数据预测药物-药物相互作用，并评估术语[I]/K-i中抑制剂浓度的各种估计值的使用。从文献中整理CYP 2D 6或CYP 2C 9以及抑制剂的体外Ki值和药代动力学参数，允许计算给药间隔期间的平均/最大全身血药浓度和最大肝脏输入血药浓度（总浓度和未结合浓度）。结果假阴性预测的发生率（AUC比> 2，[I]/K-i < 1）使用平均未结合血浆浓度是最大的，并且使用每种酶的抑制剂的肝输入总血浆浓度是最小的。排除基于机制的抑制，使用总肝输入浓度基本上没有导致假阴性预测，尽管有几个假阳性预测（AUC比< 2，[I]/Ki> 1）。（AUC比> 2，[I]/K-i > 1）结论抑制剂的总肝输入浓度与总肝输入浓度联合使用，体外K-i值是对推定的β-内酰胺酶抑制剂进行分类和鉴定阴性药物-药物相互作用的最成功的方法。然而，这种方法应被视为一个初步的鉴别筛选，因为它是经验性的，需要随后的机制研究，以提供一个积极的结果的综合评价。
Aims In theory, the magnitude of an in vivo drug-drug interaction arising from the inhibition of metabolic clearance can be predicted using the ratio of inhibitor concentration ([I]) to inhibition constant (K-i). The aim of this study was to construct a database for the prediction of drug-drug interactions from in vitro data and to evaluate the use of the various estimates for the inhibitor concentrations in the term [I]/K-i.Methods One hundred and ninety-three in vivo drug-drug interaction studies involving inhibition of CYP3A4, CYP2D6 or CYP2C9 were collated from the literature together with in vitro K-i values and pharmacokinetic parameters for inhibitors, to allow calculation of average/maximum systemic plasma concentration during the dosing interval and maximum hepatic input plasma concentration (both total and unbound concentration). The observed increase in AUC (decreased clearance) was plotted against the estimated [I]/K-i ratio for qualitative zoning of the predictions.Results The incidence of false negative predictions (AUC ratio > 2, [I]/K-i < 1) was largest using the average unbound plasma concentration and smallest using the hepatic input total plasma concentration of inhibitor for each of the CYP enzymes. Excluding mechanism-based inhibition, the use of total hepatic input concentration resulted in essentially no false negative predictions, though several false positive predictions (AUC ratio < 2, [I]/K-i > 1) were found. The incidence of true positive predictions (AUC ratio > 2, [I]/K-i > 1) was also highest using the total hepatic input concentration.Conclusions The use of the total hepatic input concentration of inhibitor together with in vitro K-i values was the most successful method for the categorization of putative CYP inhibitors and for identifying negative drug-drug interactions. However this approach should be considered as an initial discriminating screen, as it is empirical and requires subsequent mechanistic studies to provide a comprehensive evaluation of a positive result.