在可视化和交互式危害评估平台内实施计算机毒理学协议

IF 3.1 Q2 TOXICOLOGY
Glenn J. Myatt , Arianna Bassan , Dave Bower , Candice Johnson , Scott Miller , Manuela Pavan , Kevin P. Cross
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引用次数: 2

摘要

机械驱动的危害评估替代方法总是需要进行一系列测试,包括计算机模型和实验数据。决策过程,从选择方法到结合基于证据权重的信息,在已出版的指南或协议中有理想的描述。这确保了这些方法的应用对于监管机构和整个行业的审查员来说是可辩护的。例子包括ICH M7药物杂质指南和已出版的硅毒理学方案。为了支持这些协议的高效、透明、一致和完整的文档化实施,本文描述了一种新的交互式软件解决方案,用于基于公共和专有信息执行这种综合危害评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Implementation of in silico toxicology protocols within a visual and interactive hazard assessment platform

Implementation of in silico toxicology protocols within a visual and interactive hazard assessment platform

Mechanistically-driven alternative approaches to hazard assessment invariably require a battery of tests, including both in silico models and experimental data. The decision-making process, from selection of the methods to combining the information based on the weight-of-evidence, is ideally described in published guidelines or protocols. This ensures that the application of such approaches is defendable to reviewers within regulatory agencies and across the industry. Examples include the ICH M7 pharmaceutical impurities guideline and the published in silico toxicology protocols. To support an efficient, transparent, consistent and fully documented implementation of these protocols, a new and novel interactive software solution is described to perform such an integrated hazard assessment based on public and proprietary information.

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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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