4.4 Article

Building scientific confidence in the development and evaluation of read-across

期刊

REGULATORY TOXICOLOGY AND PHARMACOLOGY
卷 72, 期 1, 页码 117-133

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.yrtph.2015.03.015

关键词

Read-across; (Quantitative) Structure Activity Relationship (Q)SAR; Quantitative Mechanistic Models (QMM); Chemical categories; Analogue approach; Adverse Outcome Pathway (ADP); Scientific confidence

资金

  1. Cefic LRI

向作者/读者索取更多资源

Read-across is an alternative approach exploited to address information requirements for risk assessment and for regulatory programmes such as the European Union's REACH regulation. Whilst read-across approaches are accepted in principle, difficulties still remain in applying them consistently in practice. Recent work within Cefic LRI and ECETOC attempted to summarize the state-of-the-art and identify some of the barriers to broader acceptance of read-across approaches to overcome these. Acceptance is undoubtedly thwarted partly by the lack of a systematic framework to characterize the read-across justification and identify the uncertainties particularly for complex regulatory endpoints such as repeated-dose toxicity or prenatal developmental toxicity. Efforts are underway by the European Chemical's Agency (ECHA) to develop a Read-Across Assessment Framework (RAAF) and private sector experts have also considered the development of a similar framework. At the same time, mechanistic chemical categories are being proposed which are underpinned by Adverse Outcome Pathways (AOPs). Currently such frameworks are only focusing on discrete organic substances, though the AOP approach could conceivably be applied to evaluate more complex substances such as mixtures. Here we summarize the deliberations of the Cefic LRI read-across team in characterizing scientific confidence in the development and evaluation of read-across. (C) 2015 Elsevier Inc. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.4
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据