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首页> 外文期刊>Drug Metabolism and Disposition: The Biological Fate of Chemicals >Perspectives from the Innovation and Quality Consortium Induction Working Group on Factors Impacting Clinical Drug-Drug Interactions Resulting from Induction: Focus on Cytochrome 3A Substrates
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Perspectives from the Innovation and Quality Consortium Induction Working Group on Factors Impacting Clinical Drug-Drug Interactions Resulting from Induction: Focus on Cytochrome 3A Substrates

机译:来自创新和质量联盟的观点对诱导产生临床药物 - 药物相互作用的因素:焦点对细胞色素3A基材

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A recent publication from the Innovation and Quality Consortium Induction Working Group collated a large clinical data set with the goal of evaluating the accuracy of drug-drug interaction (DDI) prediction from in vitro data. Somewhat surprisingly, comparison across studies of the mean- or median-reported area under the curve ratio showed appreciable variability in the magnitude of outcome. This commentary explores the possible drivers of this range of outcomes observed in clinical induction studies. While recommendations on clinical study design are not being proposed, some key observations were informative during the aggregate analysis of clinical data. Although DDI data are often presented using median data, individual data would enable evaluation of how differences in study design, baseline expression, and the number of subjects contribute. Since variability in perpetrator pharmacokinetics (PK) could impact the overall DDI interpretation, should this be routinely captured? Maximal induction was typically observed after 5-7 days of dosing. Thus, when the half-life of the inducer is less than 30 hours, are there benefits to a more standardized study design? A large proportion of CYP3A4 inducers were also CYP3A4 inhibitors and/or inactivators based on in vitro data. In these cases, using CYP3A selective substrates has limitations. More intensive monitoring of changes in area under the curve over time is warranted. With selective CYP3A substrates, the net effect was often inhibition, whereas less selective substrates could discern induction through mechanisms not susceptible to inhibition. The latter included oral contraceptives, which raise concerns of reduced efficacy following induction. Alternative approaches for modeling induction, such as applying biomarkers and physiologically based pharmacokinetic modeling (PBPK), are also considered.
机译:最近从创新和质量联盟的融合工作组出版的出版物将一个大型临床数据集,目的是评估来自体外数据的药物 - 药物相互作用(DDI)预测的准确性。有些令人惊讶的是,在曲线比下的平均或中间报告区域的研究比较在结果的大小方面表现出明显的变化。该评论探讨了在临床感应研究中观察到这一种类结果的可能驱动因素。虽然没有提出关于临床研究设计的建议,但在临床资料的总分析期间,一些关键观测是信息。虽然通常使用中位数数据呈现DDI数据,但个别数据将能够评估研究设计,基线表达和受试者数量的差异。由于犯罪者药代动力学(PK)的可变性可能会影响整体DDI解释,这应该是常规捕获的吗?在给药5-7天后通常观察到最大诱导。于是,当诱导剂的半衰期小于30小时时,有利于更标准化的研究设计吗?大部分CYP3A4诱导剂也是CYP3A4抑制剂和/或基于体外数据的灭弧剂。在这些情况下,使用CYP3A选择性基板具有限制。有必要更加强化对曲线下的区域变化的更加密集监测。通过选择性CYP3A基材,净效应通常是抑制作用,而较少的选择性基材可以通过不易抑制的机制辨别诱导。后者包括口服避孕药,这提高了诱导后疗效降低的疑虑。还考虑了建模诱导的替代方法,例如施用生物标志物和生理学的药代动力学建模(PBPK)。

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