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基于非动物模型预测毒理学终点的机制适用范围:一般原则及其在反应性毒性中的应用

Mechanistic applicability domains for nonanimal-based prediction of toxicological end points: general principles and application to reactive toxicity.

作者信息

Aptula Aynur O, Roberts David W

机构信息

SEAC, Unilever Colworth, Sharnbrook, Bedford, MK44 1LQ, England.

出版信息

Chem Res Toxicol. 2006 Aug;19(8):1097-105. doi: 10.1021/tx0601004.

Abstract

In light of new legislation (e.g., the REACH program in the European Union), several initiatives have recently emerged to increase acceptance of (quantitative) structure-activity relationships [(Q)SARs] to reduce reliance on animal (in vivo) testing. Among the principles for assessing the validity of (Q)SARs is the need for a defined domain of applicability, i.e., identification of the range of compounds for which the (Q)SAR can confidently be applied for purposes of toxicity prediction. Here, we attempt to develop a "natural" classification into applicability domains based on considering how a compound and the target organism between them "decide" on the nature and extent of the toxic effect. With particular emphasis on reactive toxicity, we present rules, based on organic reaction mechanistic principles, for classifying reactive toxicants into their appropriate mechanistic applicability domains.

摘要

鉴于新的法规(例如欧盟的化学品注册、评估、授权和限制法规),最近出现了多项举措,以提高(定量)构效关系[(Q)SARs]的接受度,从而减少对动物(体内)试验的依赖。评估(Q)SARs有效性的原则之一是需要定义适用范围,即确定可以可靠地将(Q)SAR用于毒性预测目的的化合物范围。在此,我们试图基于考虑化合物与目标生物体之间如何“决定”毒性作用的性质和程度,开发一种“自然”的适用范围分类方法。特别强调反应性毒性,我们基于有机反应机理原则提出规则,将反应性毒物分类到其适当的机理适用范围。

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