毒理基因组学
计算机科学
化妆品
生物信息学
风险评估
生化工程
计算生物学
毒理
风险分析(工程)
生物
化学
医学
工程类
计算机安全
生物化学
基因表达
有机化学
基因
作者
Camilla Alexander‐White,Dagmar Bury,Mark T.D. Cronin,Matthew Dent,Eric Hack,Nicola J. Hewitt,J. Gerry Kenna,Jorge M. Naciff,Gladys Ouédraogo,Andreas Schepky,Catherine Mahony,Cosmetics Europe
标识
DOI:10.1016/j.yrtph.2021.105094
摘要
This paper presents a 10-step read-across (RAX) framework for use in cases where a threshold of toxicological concern (TTC) approach to cosmetics safety assessment is not possible. RAX builds on established approaches that have existed for more than two decades using chemical properties and in silico toxicology predictions, by further substantiating hypotheses on toxicological similarity of substances, and integrating new approach methodologies (NAM) in the biological and kinetic domains. NAM include new types of data on biological observations from, for example, in vitro assays, toxicogenomics, metabolomics, receptor binding screens and uses physiologically-based kinetic (PBK) modelling to inform about systemic exposure. NAM data can help to substantiate a mode/mechanism of action (MoA), and if similar chemicals can be shown to work by a similar MoA, a next generation risk assessment (NGRA) may be performed with acceptable confidence for a data-poor target substance with no or inadequate safety data, based on RAX approaches using data-rich analogue(s), and taking account of potency or kinetic/dynamic differences.
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