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Evidence-based selection of training compounds for use in the mechanism-based integrated prediction of drug-induced liver injury in man

机译:基于证据的训练化合物的选择用于基于机制的男性药物性肝损伤的综合预测

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摘要

The current test systems employed by pharmaceutical industry are poorly predictive for drug-induced liver injury (DILI). The ‘MIP-DILI’ project addresses this situation by the development of innovative preclinical test systems which are both mechanism-based and of physiological, pharmacological and pathological relevance to DILI in humans. An iterative, tiered approach with respect to test compounds, test systems, bioanalysis and systems analysis is adopted to evaluate existing models and develop new models that can provide validated test systems with respect to the prediction of specific forms of DILI and further elucidation of mechanisms. An essential component of this effort is the choice of compound training set that will be used to inform refinement and/or development of new model systems that allow prediction based on knowledge of mechanisms, in a tiered fashion. In this review, we focus on the selection of MIP-DILI training compounds for mechanism-based evaluation of non-clinical prediction of DILI. The selected compounds address both hepatocellular and cholestatic DILI patterns in man, covering a broad range of pharmacologies and chemistries, and taking into account available data on potential DILI mechanisms (e.g. mitochondrial injury, reactive metabolites, biliary transport inhibition, and immune responses). Known mechanisms by which these compounds are believed to cause liver injury have been described, where many if not all drugs in this review appear to exhibit multiple toxicological mechanisms. Thus, the training compounds selection offered a valuable tool to profile DILI mechanisms and to interrogate existing and novel in vitro systems for the prediction of human DILI.
机译:制药行业当前使用的测试系统对于药物诱发的肝损伤(DILI)的预测性较差。 “ MIP-DILI”项目通过开发创新的临床前测试系统来解决这种情况,该系统既基于机理,又与人体DILI具有生理,药理和病理学相关性。对于测试化合物,测试系统,生物分析和系统分析,采用了一种迭代,分层的方法来评估现有模型并开发新的模型,这些模型可以提供有关经过验证的DILI特定形式的预测以及进一步阐明机理的测试系统。这项工作的重要组成部分是选择复合训练集,该训练集将用于告知新模型系统的细化和/或开发,这些模型系统允许基于机制知识进行分层预测。在这篇综述中,我们着重于选择MIP-DILI训练化合物,用于基于机制的DILI非临床预测评估。选择的化合物可解决人的肝细胞和胆汁淤积性DILI模式,涵盖广泛的药理学和化学性质,并考虑到有关潜在DILI机制的可用数据(例如线粒体损伤,反应性代谢产物,胆汁运输抑制和免疫反应)。已经描述了据信这些化合物引起肝损伤的已知机理,其中本综述中的许多(如果不是全部)药物似乎表现出多种毒理学机理。因此,训练化合物的选择提供了一种有价值的工具,可用于描述DILI机制并询问现有和新颖的体外系统,以预测人类DILI。

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