从模型性能到决策支持--计算毒理学在化学品安全评估中的兴起

IF 3.1 Q2 TOXICOLOGY Computational Toxicology Pub Date : 2024-09-01 DOI:10.1016/j.comtox.2024.100303
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引用次数: 0

摘要

硅学系统可以减少对(动物)试验的需求,提高人体安全性,并为关键决策提供支持。它们越来越多地被引用到监管指导文件中,并成为新方法(NAMs)的关键要素。通过结合使用新方法、加深对机理毒理学的理解以及获取新检测方法的实验数据,这些方法的性能正在不断提高。对硅学方法的信任和接受要求这些方法准确、透明,同时对每项预测提供解释和置信度评估。本文总结了硅学模型的最新进展,并提出了进一步推动该领域发展的行动计划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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From model performance to decision support – The rise of computational toxicology in chemical safety assessments

In silico systems can reduce the need for (animal) testing, increase human safety and support critical decisions. They are increasingly being cited in regulatory guidance documents and are forming a key element of New Approach Methodologies (NAMs). Performance is being improved through a combination of new methodologies, increased understanding of mechanistic toxicology and access to experimental data from new assays. Trust and acceptance of in silico methodologies requires them to be accurate and transparent while also providing an explanation and confidence-assessment for each prediction. This paper summarises the state-of-art of in silico models and provides an action plan for further advances in this field.

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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
期刊最新文献
Evaluation of QSAR models for tissue-specific predictive toxicology and risk assessment of military-relevant chemical exposures: A systematic review From model performance to decision support – The rise of computational toxicology in chemical safety assessments Development of chemical categories for per- and polyfluoroalkyl substances (PFAS) and the proof-of-concept approach to the identification of potential candidates for tiered toxicological testing and human health assessment The OECD (Q)SAR Assessment Framework: A tool for increasing regulatory uptake of computational approaches A developmental and reproductive toxicity adverse outcome pathway network to support safety assessments
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