Knowledge infrastructure for integrated data management and analysis supporting new approach methods in predictive toxicology and risk assessment

IF 2.6 3区 医学 Q3 TOXICOLOGY
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引用次数: 0

Abstract

The EU-ToxRisk project (2016–2021) was a large European project working towards shifting toxicological testing away from animal tests, towards a toxicological assessment based on comprehensive mechanistic understanding of cause-consequence relationships of chemical adverse effects. More than 40 partners from scientific institutions, industry and regulators coordinated their work towards this goal in a six-year long programme. The breadth and variety of data and knowledge generated, presented a challenging data management landscape.

Here, we describe our approach to data management as developed under EU-ToxRisk. The main building blocks of the data infrastructure are: 1) An easy-to-use, extensible data and metadata format; 2) A flexible system with protocols for data capture and sharing from the entire consortium; 3) A methods database for describing and reviewing data generation and processing protocols; 4) Data archiving using a sustainable resource; 5) Data transformation from the archive to the system that provides granular access; 6) Application Programming Interface (API) for access to individual data points; 7) Data exploration and analysis modules, based on a «web notebook» approach to executable data processing documentation; and 8) Knowledge portal that ties together all of the above and provides a collaboration space for information exchange across the consortium. This knowledge infrastructure is being extended and refined for the support of follow-up projects (RISK-HUNT3R, ASPIS cluster, European Open Science Cloud (2021–2026)).

Abstract Image

支持预测毒理学和风险评估新方法的综合数据管理和分析知识基础设施。
欧盟-毒物风险项目(2016-2021 年)是欧洲的一个大型项目,致力于将毒理学测试从动物试验转向基于对化学品不良影响因果关系的全面机理理解的毒理学评估。来自科研机构、行业和监管机构的 40 多个合作伙伴在长达六年的计划中为实现这一目标而协调工作。所产生的数据和知识范围广、种类多,给数据管理工作带来了挑战。在此,我们将介绍在欧盟-毒物风险计划下开发的数据管理方法。数据基础设施的主要组成部分包括1) 易于使用、可扩展的数据和元数据格式;2) 灵活的系统,具有从整个联盟获取和共享数据的协议;3) 用于描述和审查数据生成和处理协议的方法数据库;4) 使用可持续资源进行数据存档;5) 从存档到系统的数据转换,提供细粒度访问;6) 用于访问单个数据点的应用编程接口(API); 7) 基于可执行数据处理文档的 "网络笔记本 "方法的数据探索和分析模块;以及 8) 知识门户网站,将上述所有内容联系在一起,为整个联盟的信息交流提供合作空间。目前正在扩展和完善这一知识基础设施,以支持后续项目(RISK-HUNT3R、ASPIS 集群、欧洲开放科学云(2021-2026 年))。
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来源期刊
Toxicology in Vitro
Toxicology in Vitro 医学-毒理学
CiteScore
6.50
自引率
3.10%
发文量
181
审稿时长
65 days
期刊介绍: Toxicology in Vitro publishes original research papers and reviews on the application and use of in vitro systems for assessing or predicting the toxic effects of chemicals and elucidating their mechanisms of action. These in vitro techniques include utilizing cell or tissue cultures, isolated cells, tissue slices, subcellular fractions, transgenic cell cultures, and cells from transgenic organisms, as well as in silico modelling. The Journal will focus on investigations that involve the development and validation of new in vitro methods, e.g. for prediction of toxic effects based on traditional and in silico modelling; on the use of methods in high-throughput toxicology and pharmacology; elucidation of mechanisms of toxic action; the application of genomics, transcriptomics and proteomics in toxicology, as well as on comparative studies that characterise the relationship between in vitro and in vivo findings. The Journal strongly encourages the submission of manuscripts that focus on the development of in vitro methods, their practical applications and regulatory use (e.g. in the areas of food components cosmetics, pharmaceuticals, pesticides, and industrial chemicals). Toxicology in Vitro discourages papers that record reporting on toxicological effects from materials, such as plant extracts or herbal medicines, that have not been chemically characterized.
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