The use of computational toxicology in hazard assessment of engineered nanomaterials

Chen, G. (2017)

Doctoral Thesis

Assessing the risks of engineered nanomaterials (ENMs) solely on the basis of experimental assays is time-consuming, resource intensive, and constrained by ethical considerations (such as the principles of the 3Rs of animal testing). The adoption of computational toxicology in this field is a high priority. Computational toxicology is able to contribute to the prediction of the extent of toxic effects of untested ENMs, to the hazard categorization and labeling of ENMs, and to the establishment of hazard threshold values that are sufficiently protecting the ecosystem with respect to the ENMs of concern. These three steps are listed by the European Chemicals Agency (ECHA) as the three elements in evaluating the hazards of ENMs. This study has expanded the use of computational toxicology in the hazard assessment with regard to the safe handling of ENMs. The results obtained contribute to the integration and evaluation of toxicity data, the identification of research gaps on ENM-related modeling, and the development of nano-SARs and SSDs for metallic ENMs. Despite the uncertainties that are associated with our results, as mainly due to limited data quality and availability, we managed to take this field one step forwards and contribute to better-informed regulatory decisions of ENMs.

• Ecotoxicity
• Hazards assessment
• Metallic
• Nanomaterials
• (Q)SARs
• Species sensitivity distributions

• All authors: Chen, G.
• Editor(s): Chen G.
• Supervisor: Peijnenburg, W.J.G.M.
• Co-supervisor: Vijver, M.G.
• Committee: Meent, D. van de; Jagiello, K.; Tetko, I.; Tukker, Arnold; Bodegom, P.M. van
• Qualification: Doctor (dr.)
• Awarding Institution: Institute of Environmental Sciences (CML), Science, Leiden University
• Date: 2017-09-19
• ISBN (print): 9789461828231