Development of a systematic method to assess similarity between nanomaterials for human hazard evaluation purposes - lessons learnt.
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Authors
Vdz Park, MargrietCatalán, Julia
Ferraz, Natalia
Cabellos, Joan
Vanhauten, Ralph
Vázquez-Campos, Socorro
Janer, Gemma
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ArticleLanguage
en
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Development of a systematic method to assess similarity between nanomaterials for human hazard evaluation purposes - lessons learnt.Published in
Nanotoxicology 2018; 12(7):652-76Publiekssamenvatting
Within the EU FP-7 GUIDEnano project, a methodology was developed to systematically quantify the similarity between a nanomaterial (NM) that has been tested in toxicity studies and the NM for which risk needs to be evaluated, for the purpose of extrapolating toxicity data between the two materials. The methodology is a first attempt to use current knowledge on NM property-hazard relationships to develop a series of pragmatic and systematic rules for assessing NM similarity. Moreover, the methodology takes into account the practical feasibility, in that it is based on generally available NM characterization information. In addition to presenting this methodology, the lessons learnt and the challenges faced during its development are reported here. We conclude that there is a large gap between the information that is ideally needed and its application to real cases. The current database on property-hazard relationships is still very limited, which hinders the agreement on the key NM properties constituting the basis of the similarity assessment and the development of associated science-based and unequivocal rules. Currently, one of the most challenging NM properties to systematically assess in terms of similarity between two NMs is surface coating and functionalization, which lacks standardized parameters for description and characterization methodology. Standardization of characterization methods that lead to quantitative, unambiguous, and measurable parameters describing NM properties are necessary in order to build a sufficiently robust property-hazard database that allows for evidence-based refinement of our methodology, or any other attempt to systematically assess the similarity of NMs.PMID
29732939ae974a485f413a2113503eed53cd6c53
10.1080/17435390.2018.1465142
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