Hazard assessment of nanomaterials: how to meet the requirements for (next generation) risk assessment

[Background] Hazard and risk assessment of nanomaterials (NMs) face challenges due to, among others, the numerous existing nanoforms, discordant data and conflicting results found in the literature, and specific challenges in the application of strategies such as grouping and read-across, emphasizin...

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Detalles Bibliográficos
Autores: Longhin, Eleonora Marta, Ríos-Mondragón, Iván, Mariussen, Espen, Zheng, Congying, Busquets-Fité, Martí, Gajewska, Agnieszka, Hofshagen, Ole-Bendik, Bastús, Neus G., Puntes, Víctor F., Cimpan, Mihaela Roxana, Shaposhnikov, Sergey, Dusinska, María, Rundén-Pran, Elise
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/380736
Acceso en línea:http://hdl.handle.net/10261/380736
https://api.elsevier.com/content/abstract/scopus_id/85213337178
Access Level:acceso abierto
Palabra clave:Hazard assessment
Nanomaterials
New approach methodologies
Next generation risk assessment
Safe and sustainable by design
Descripción
Sumario:[Background] Hazard and risk assessment of nanomaterials (NMs) face challenges due to, among others, the numerous existing nanoforms, discordant data and conflicting results found in the literature, and specific challenges in the application of strategies such as grouping and read-across, emphasizing the need for New Approach Methodologies (NAMs) to support Next Generation Risk Assessment (NGRA). Here these challenges are addressed in a study that couples physico-chemical characterization with in vitro investigations and in silico similarity analyses for nine nanoforms, having different chemical composition, sizes, aggregation states and shapes. For cytotoxicity assessment, three methods (Alamar Blue, Colony Forming Efficiency, and Electric Cell-Substrate Impedance Sensing) are applied in a cross-validation approach to support NAMs implementation into NGRA.