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试验指南制定与动物福利:体外研究的监管认可

Test guideline development and animal welfare: regulatory acceptance of in vitro studies.

作者信息

Koëter H B

机构信息

OECD Environmental Health and Safety Division, Paris, France.

出版信息

Reprod Toxicol. 1993;7 Suppl 1:117-23. doi: 10.1016/0890-6238(93)90077-k.

Abstract

Toxicity studies are necessary in order to be able to identify the potential hazards of chemical interference with human reproduction. Until today, most useful contributions to the assessment of possible human reproductive toxicity are considered to be made by animal studies. The OECD Test Guidelines provide the international standards for safety testing and, consequently, have traditionally focused on animal studies. However, the OECD Member countries consider the welfare of laboratory animals also of importance and are of the opinion that animal welfare considerations should significantly influence the work in the OECD Chemicals Programme. A constant effort is being made to discover alternative testing systems and to achieve their regulatory acceptance. However, activities predominately focus on finding alternatives to existing animal studies, rather than developing nonanimal tests that could contribute significantly to the hazard identification process. An approach based on the selection of endpoints essential for hazard identification that would focus on demonstrating similarities with the "real life" target events is considered likely to achieve regulatory acceptance much earlier than an approach based on high correlations between the alternative method and the existing animal study it is supposed to replace, simply because it is never better than the existing method, but at most "almost as reliable."

摘要

为了能够识别化学物质对人类生殖的潜在危害,进行毒性研究是必要的。直到如今,动物研究被认为是对评估可能的人类生殖毒性最有帮助的贡献。经合组织测试指南为安全测试提供了国际标准,因此传统上一直侧重于动物研究。然而,经合组织成员国也认为实验动物的福利很重要,并认为动物福利考量应显著影响经合组织化学品计划中的工作。人们一直在不断努力寻找替代测试系统并使其获得监管认可。然而,活动主要集中在寻找现有动物研究的替代方法,而不是开发能够对危害识别过程做出重大贡献的非动物测试。一种基于选择危害识别所需关键终点的方法,该方法侧重于证明与“现实生活”目标事件的相似性,被认为比基于替代方法与它应该替代的现有动物研究之间的高度相关性的方法更有可能更早地获得监管认可,仅仅是因为它永远不会比现有方法更好,最多只是“几乎同样可靠”。

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