Developing and validating read-across workflows that enable decision making for toxicity and potency: Case studies with N-nitrosamines

IF 3.1 Q2 TOXICOLOGY
Steven Kane, Dan Newman, David J. Ponting, Edward Rosser, Robert Thomas, Jonathan D. Vessey, Samuel J. Webb, William H.J. Wood
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引用次数: 0

Abstract

To reach conclusions during chemical safety assessments, risk assessors need to ensure sufficient information is present to satisfy the decision criteria. This often requires data to be generated and, in some cases, insufficient knowledge is present, or it is not feasible to generate new data through experiments. Read-across is a powerful technique to fill such data gaps, however the expert-driven process can be time intensive and subjective in nature resulting in variation of approach. To overcome these barriers a prototype software application has been developed by Lhasa Limited to support decision making about the toxicity and potency of chemicals using a read-across approach. The application supports a workflow which allows the user to gather data and knowledge about a chemical of interest and possible read-across candidates. Relevant information is then presented that enables the user to decide if read-across can be performed and, if so, which analogue or category can be considered the most appropriate. Data and knowledge about the toxicity of a compound and potential analogues include assay and metabolism data, toxicophore identification and its local similarity, physico-chemical and pharmacokinetic properties and observed and predicted metabolic profile. The utility of the approach is demonstrated with case studies using N-nitrosamine compounds, where the conclusions from using the workflow supported by the software are concordant with the evidence base. The components of the workflow have been further validated by demonstrating that conclusions are significantly better than would be expect from the distribution of data in test sets. The approach taken demonstrates how software implementing intuitive workflows that guide experts during read-across can support decisions and how validation of the methods can increase confidence in the overall approach.

开发和验证可对毒性和效力做出决策的跨读工作流程:亚硝胺案例研究
为了在化学品安全评估过程中得出结论,风险评估人员需要确保有足够的信息来满足决策标准。这通常需要生成数据,而在某些情况下,知识不足或通过实验生成新数据并不可行。读取数据是填补此类数据空白的一项强大技术,但专家驱动的过程可能需要大量时间,而且主观性强,导致方法各异。为了克服这些障碍,拉萨有限公司开发了一个原型软件应用程序,以支持使用 "交叉阅读 "方法对化学品的毒性和效力进行决策。该应用软件支持一个工作流程,允许用户收集有关所关注化学品的数据和知识,以及可能的候选对照品。相关信息随后会显示出来,使用户能够决定是否可以进行交叉分析,如果可以,哪种类似物或类别最合适。有关化合物和潜在类似物毒性的数据和知识包括化验和代谢数据、毒源鉴定及其局部相似性、物理化学和药代动力学特性以及观察到的和预测的代谢概况。利用 N-亚硝胺化合物进行的案例研究证明了该方法的实用性,使用该软件支持的工作流程得出的结论与证据基础一致。工作流程的各个组成部分得到了进一步验证,证明结论明显优于测试集数据分布的预期。所采用的方法表明,实施直观工作流程的软件如何能够指导专家进行交叉阅读,从而为决策提供支持,以及对方法的验证如何能够增强对整体方法的信心。
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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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