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首页> 外文期刊>Biological & pharmaceutical bulletin >Usefulness of Two-Compartment Model-Assisted and Static Overall Inhibitory-Activity Method for Prediction of Drug-Drug Interaction
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Usefulness of Two-Compartment Model-Assisted and Static Overall Inhibitory-Activity Method for Prediction of Drug-Drug Interaction

机译:用于预测药物 - 药物相互作用的两室模型辅助和静态总抑制活性方法的有用性

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摘要

Our study of drug drug interaction (DDI) started with the clarification of unusually large DDI observed between ramelteon (RAM) and fluvoxamine (FLV). The main cause of this DDI was shown to be the extremely small hepatic availability of RAM (vF(h)). Traditional DDI prediction assuming the well-stirred hepatic extraction kinetic ignores the relative increase of vFh by DDI, while we could solve this problem by use of the tube model. Ultimately, we completed a simple and useful method for prediction of DDI. Currently, DDI prediction becomes more complex and difficult when examining issues such as dynamic changes in perpetrator level, inhibitory metabolites, etc. The regulatory agents recommend DDI prediction by use of some sophisticated methods. However, they seem problematic in requiring plural in vitro data that reduce the flexibility and accuracy of the simulation. In contrast, our method is based on the static and two-compartment models. The two-compartment model has advantages in that it uses common pharmacokinetics (PK) parameters determined from the actual clinical data, guaranteeing the simulation of the reference standard in DDI. Our studies confirmed that dynamic changes in perpetrator level do not make a difference between static and dynamic methods. DDIs perpetrated by FLV and itraconazole were successfully predicted by use of the present method where two DDI predictors [perpetrator-specific inhibitory activities toward CYP isoforms (pA(i,CYP)s) and victim-specific fractional CYP-isoform contributions to the clearance (vf(m,CYPs))] are determined successively as shown in the graphical abstract. Accordingly, this approach will accelerate DDI prediction over the traditional methods.
机译:我们对药物药物相互作用(DDI)的研究开始澄清ramelteon(RAM)和Fluvoxamine(FLV)之间观察到异常的大DDI。该DDI的主要原因显示为RAM的极小肝脏可用性(VF(H))。假设搅拌肝萃取动力学的传统DDI预测忽略了DDI的VFH的相对增加,而我们可以通过使用管模型来解决这个问题。最终,我们完成了一种简单而有用的方法来预测DDI。目前,DDI预测变得更加复杂,困难地检查诸如犯罪者级别,抑制代谢物等动态变化等问题时,监管代理推荐使用一些复杂方法推荐DDI预测。然而,它们似乎有问题在需要复数的体外数据时,这减少了模拟的灵活性和准确性。相比之下,我们的方法基于静态和两室模型。双隔室模型具有优势,因为它使用了从实际临床数据确定的常见药代动力学(PK)参数,保证DDI中的参考标准的模拟。我们的研究证实,突击者级别的动态变化不会在静态和动态方法之间产生差异。通过使用本方法成功地预测了由FLV和伊唑康唑犯下的DDI预测,其中两个DDI预测器[患者特异性抑制活动对CYP同种型(PA(I,CYP))和受害者特异性分数CYP-ISOOFORM贡献( VF(M,Cyps))]连续确定,如图形摘要所示。因此,该方法将加速对传统方法的DDI预测。

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