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Int. J. Mol. Sci. 2017, 18(7), 1504; doi:10.3390/ijms18071504

Current Knowledge on the Use of Computational Toxicology in Hazard Assessment of Metallic Engineered Nanomaterials

1
Institute of Environmental Sciences, Leiden University, 2300 RA Leiden, The Netherlands
2
Centre for Safety of Substances and Products, National Institute of Public Health and the Environment (RIVM), Bilthoven, 3720 BA Bilthoven, The Netherlands
*
Author to whom correspondence should be addressed.
Received: 12 June 2017 / Revised: 7 July 2017 / Accepted: 10 July 2017 / Published: 12 July 2017
(This article belongs to the Special Issue Nanotoxicology and Nanosafety)
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Abstract

As listed by the European Chemicals Agency, the three elements in evaluating the hazards of engineered nanomaterials (ENMs) include the integration and evaluation of toxicity data, categorization and labeling of ENMs, and derivation of hazard threshold levels for human health and the environment. Assessing the hazards of ENMs solely based on laboratory tests is time-consuming, resource intensive, and constrained by ethical considerations. The adoption of computational toxicology into this task has recently become a priority. Alternative approaches such as (quantitative) structure–activity relationships ((Q)SAR) and read-across are of significant help in predicting nanotoxicity and filling data gaps, and in classifying the hazards of ENMs to individual species. Thereupon, the species sensitivity distribution (SSD) approach is able to serve the establishment of ENM hazard thresholds sufficiently protecting the ecosystem. This article critically reviews the current knowledge on the development of in silico models in predicting and classifying the hazard of metallic ENMs, and the development of SSDs for metallic ENMs. Further discussion includes the significance of well-curated experimental datasets and the interpretation of toxicity mechanisms of metallic ENMs based on reported models. An outlook is also given on future directions of research in this frontier. View Full-Text
Keywords: computational toxicology; hazard assessment; metallic engineered nanomaterials; (quantitative) structure–activity relationships; species sensitivity distributions computational toxicology; hazard assessment; metallic engineered nanomaterials; (quantitative) structure–activity relationships; species sensitivity distributions
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MDPI and ACS Style

Chen, G.; Peijnenburg, W.; Xiao, Y.; Vijver, M.G. Current Knowledge on the Use of Computational Toxicology in Hazard Assessment of Metallic Engineered Nanomaterials. Int. J. Mol. Sci. 2017, 18, 1504.

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