社论:qAOPs会使毒理学现代化吗?

IF 3.1 Q2 TOXICOLOGY
Mark T.D. Cronin , Nicoleta Spînu , Andrew P. Worth
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引用次数: 0

摘要

在这篇社论中,我们反思了过去十年预测毒理学的发展,特别是不良结果途径(AOP)范式的演变。从一个概念开始,aop已经成为一个由科学家、监管者和决策者组成的社区的焦点。aop提供了支持测试和评估集成方法(IATA)开发的机械知识,包括现在称为定量aop (qAOPs)的计算模型。参考最近和相关的qAOPs工作,我们采取了一个简短的历史观点,并问什么是现代化的化学毒理学的下一个阶段,除了动物试验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Will qAOPs modernise toxicology?

In this editorial we reflect on the past decade of developments in predictive toxicology, and in particular on the evolution of the Adverse Outcome Pathway (AOP) paradigm. Starting out as a concept, AOPs have become the focal point of a community of scientists, regulators and decision-makers. AOPs provide the mechanistic knowledge underpinning the development of Integrated Approaches to Testing and Assessment (IATA), including computational models now referred to as quantitative AOPs (qAOPs). With reference to recent and related works on qAOPs, we take a brief historical perspective and ask what is the next stage in modernising chemical toxicology beyond animal testing.

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来源期刊
Computational Toxicology
Computational Toxicology Computer Science-Computer Science Applications
CiteScore
5.50
自引率
0.00%
发文量
53
审稿时长
56 days
期刊介绍: Computational Toxicology is an international journal publishing computational approaches that assist in the toxicological evaluation of new and existing chemical substances assisting in their safety assessment. -All effects relating to human health and environmental toxicity and fate -Prediction of toxicity, metabolism, fate and physico-chemical properties -The development of models from read-across, (Q)SARs, PBPK, QIVIVE, Multi-Scale Models -Big Data in toxicology: integration, management, analysis -Implementation of models through AOPs, IATA, TTC -Regulatory acceptance of models: evaluation, verification and validation -From metals, to small organic molecules to nanoparticles -Pharmaceuticals, pesticides, foods, cosmetics, fine chemicals -Bringing together the views of industry, regulators, academia, NGOs
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