[Researches on the in silico prediction of structure-activity relationship in the regulatory science sectors].

Q4 Medicine
Akihiko Hirose
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引用次数: 0

Abstract

Requirements of in silico toxicity prediction system are increasing in the chemical risk assessment fields, as well as in toxicity prediction at the early stage of the new drug development process. Recent amended chemical registration rules require internationally the risk assessment of huge amounts of existing chemicals. The (quantitative) structure-activity relationship ((Q)SAR) models are considered to be most effective tools for the acceleration of toxicity evaluation. In Europe or the United State, several research projects for the development of the (Q)SAR models are ongoing. Following this introduction, four researches on development of in silico prediction systems for (Q)SAR in the NIHS are reviewed. These activities must internationally contribute to the integrated chemical risk assessment approaches and/or could assist in the new drug development work.

[监管科学领域构效关系的计算机预测研究]。
在化学品风险评估领域,以及在新药开发过程的早期毒性预测中,对硅毒性预测系统的需求越来越大。最近修订的化学品登记规则要求在国际上对大量现有化学品进行风险评估。定量构效关系((Q)SAR)模型被认为是加速毒性评价的最有效工具。在欧洲或美国,正在进行几个开发(Q)SAR模式的研究项目。在此基础上,综述了中国科学院(NIHS)在(Q)SAR计算机预测系统开发方面的四项研究。这些活动必须在国际上有助于综合化学品风险评估方法和/或能够协助新药开发工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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0.20
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