Bossa Cecilia, Andreoli Cristina, Bakker Martine, Barone Flavia, De Angelis Isabella, Jeliazkova Nina, Nymark Penny, Battistelli Chiara Laura
Environment and Health Department, Istituto Superiore di Sanità, Rome, Italy.
Centre for Safety of Substances and Products, National Institute of Public Health and the Environment (RIVM), Bilthoven, the Netherlands.
Comput Toxicol. 2021 Nov;20:100190. doi: 10.1016/j.comtox.2021.100190.
(Quantitative) structure-activity relationship ([Q]SAR) methodologies are widely applied to predict the (eco)toxicological effects of chemicals, and their use is envisaged in different regulatory frameworks for filling data gaps of untested substances. However, their application to the risk assessment of nanomaterials is still limited, also due to the scarcity of large and curated experimental datasets. Despite a great amount of nanosafety data having been produced over the last decade in international collaborative initiatives, their interpretation, integration and reuse has been hampered by several obstacles, such as poorly described (meta)data, non-standard terminology, lack of harmonized reporting formats and criteria. Recently, the FAIR (Findable, Accessible, Interoperable, and Reusable) principles have been established to guide the scientific community in good data management and stewardship. The EU H2020 Gov4Nano project, together with other international projects and initiatives, is addressing the challenge of improving nanosafety data FAIRness, for maximizing their availability, understanding, exchange and ultimately their reuse. These efforts are largely supported by the creation of a common Nanosafety Data Interface, which connects a row of project-specific databases applying the eNanoMapper data model. A wide variety of experimental data relating to characterization and effects of nanomaterials are stored in the database; however, the methods, protocols and parameters driving their generation are not fully mature. This article reports the progress of an ongoing case study in the Gov4nano project on the reuse of Comet genotoxicity data, focusing on the issues and challenges encountered in their FAIRification through the eNanoMapper data model. The case study is part of an iterative process in which the FAIRification of data supports the understanding of the phenomena underlying their generation and, ultimately, improves their reusability.
(定量)构效关系([Q]SAR)方法被广泛应用于预测化学品的(生态)毒理效应,并且在不同的监管框架中设想使用这些方法来填补未测试物质的数据空白。然而,由于缺乏大量经过整理的实验数据集,它们在纳米材料风险评估中的应用仍然有限。尽管在过去十年中,国际合作项目已经产生了大量的纳米安全数据,但由于(元)数据描述不佳、术语不标准、缺乏统一的报告格式和标准等诸多障碍,这些数据的解释、整合和再利用受到了阻碍。最近,已确立了可查找、可访问、可互操作和可再利用(FAIR)原则,以指导科学界进行良好的数据管理和 stewardship(此处可能有误,推测为“管理”)。欧盟“2020 地平线”Gov4Nano 项目与其他国际项目和倡议一道,正在应对提高纳米安全数据 FAIR 性的挑战,以最大限度地提高其可用性、可理解性、交换性,并最终实现其再利用。这些努力在很大程度上得益于创建了一个通用的纳米安全数据接口,该接口连接了一系列应用 eNanoMapper 数据模型的特定项目数据库。数据库中存储了与纳米材料表征和效应相关的各种实验数据;然而,驱动这些数据生成的方法、协议和参数尚未完全成熟。本文报告了 Gov4nano 项目中一个正在进行的关于彗星实验遗传毒性数据再利用的案例研究进展,重点关注通过 eNanoMapper 数据模型使其符合 FAIR 原则过程中遇到的问题和挑战。该案例研究是一个迭代过程的一部分,在此过程中,数据的 FAIR 化有助于理解其生成背后的现象,并最终提高其可再利用性。