Fukuchi Junichi, Kitazawa Airi, Hirabayashi Keiji, Honma Masamitsu
Division of Pharmacopoeia and Standards for Drugs, Pharmaceuticals and Medical Devices Agency, Shin-Kasumigaseki Building, Kasumigaseki, Chiyoda-ku, Tokyo, Japan.
Division of Genetics and Mutagenesis, National Institute of Health Sciences, Tonomachi, Kawasaki-ku, Kawasaki, Kanagawa, Japan.
Mutagenesis. 2019 Mar 6;34(1):49-54. doi: 10.1093/mutage/gey046.
The International Council for Harmonisation of Technical Requirement for Pharmaceuticals for Human Use (ICH) M7 guideline on 'Assessment and Control of DNA Reactive (Mutagenic) Impurities in Pharmaceuticals to Limit Potential Carcinogenic Risk' provides the application of two types of quantitative structure-activity relationship (QSAR) systems (rule- and statistics-based) as an alternative to the Ames test for evaluating the mutagenicity of impurities in pharmaceuticals. M7 guideline also states that the expert reviews can be applied when the outcomes of the two QSAR analyses show any conflicting or inconclusive prediction. However, the guideline does not provide any information of how to conduct expert reviews. Therefore, a conservative approach was chosen in this study, which is based on the intention to capture any mutagenic chemical substances. The 36 chemical substances, which are the model chemical substances in which positive mutagenicity was not observed according to the two types of QSAR analyses (i.e. the results are either conflicting or both negative), were selected from the list of chemical substances with strong mutagenicity known as the reported chemicals under the Industrial Safety and Health Act in Japan. The QSAR Toolbox was used in this study to rationally determine the positive mutagenicity of the 36 model chemical substances by applying a read-across method, a technique to evaluate the endpoint of the model chemical substances using the endpoint information of chemicals that are structurally similar to the model chemical substances. Resulting from the expert review by the read-across method, the 23 model chemical substances (63.8%) were rationally concluded as positive. In addition, 9 out of 11 model chemical substances that were assessed as negative for mutagenicity by both of the QSAR systems had positive analogues, supporting their mutagenicity. These results suggested that the read-across is a useful method, when conducting a conservative approach intended to capture any mutagenic chemical substances.
人用药品注册技术要求国际协调会(ICH)关于“评估和控制药品中DNA反应性(致突变性)杂质以限制潜在致癌风险”的M7指南规定,可应用两种类型的定量构效关系(QSAR)系统(基于规则和基于统计)作为替代艾姆斯试验的方法,用于评估药品中杂质的致突变性。M7指南还指出,当两种QSAR分析结果显示出相互矛盾或不确定的预测时,可应用专家评审。然而,该指南未提供有关如何进行专家评审的任何信息。因此,本研究选择了一种保守方法,其基于捕获任何致变化学物质的意图。从日本《工业安全与健康法》规定的已知具有强致突变性的化学物质清单中,挑选出36种化学物质作为模型化学物质,根据两种类型的QSAR分析,这些物质未观察到阳性致突变性(即结果相互矛盾或均为阴性)。本研究使用QSAR工具箱,通过应用“类推法”合理确定这36种模型化学物质的阳性致突变性,“类推法”是一种利用与模型化学物质结构相似的化学物质的终点信息来评估模型化学物质终点的技术。通过类推法进行专家评审得出,23种模型化学物质(63.8%)被合理判定为阳性。此外,在两种QSAR系统中均被评估为致突变性阴性的11种模型化学物质中,有9种具有阳性类似物,支持了它们的致突变性。这些结果表明,在采用旨在捕获任何致变化学物质的保守方法时,类推法是一种有用的方法。