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The use of new approach methodologies for the environmental risk assessment of food and feed chemicals.
Nicola, Matteo Riccardo Di; Cattaneo, Irene; Nathanail, Alexis V; Carnesecchi, Edoardo; Astuto, Maria Chiara; Steinbach, Melina; Williams, Antony John; Charles, Sandrine; Gestin, Ophélia; Lopes, Christelle; Lamonica, Dominique; Tarazona, Jose Vicente; Dorne, Jean Lou C M.
Afiliação
  • Nicola MRD; IRCCS San Raffaele Hospital, Unit of Dermatology, Milan, Italy.
  • Cattaneo I; Asociación Herpetológica Española, Madrid, Spain.
  • Nathanail AV; European Food Safety Authority, Parma, Italy.
  • Carnesecchi E; European Food Safety Authority, Parma, Italy.
  • Astuto MC; European Food Safety Authority, Parma, Italy.
  • Steinbach M; European Food Safety Authority, Parma, Italy.
  • Williams AJ; European Food Safety Authority, Parma, Italy.
  • Charles S; Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency (U.S. EPA), Research Triangle Park, NC, USA.
  • Gestin O; University of Lyon, University Lyon 1, UMR CNRS 5558, Villeurbanne, France.
  • Lopes C; University of Lyon, University Lyon 1, UMR CNRS 5558, Villeurbanne, France.
  • Lamonica D; INRAE, Riverly, Ecotoxicology, Lyon, France.
  • Tarazona JV; University of La Rochelle, UMRi 7266, La Rochelle, France.
  • Dorne JLCM; University of Lyon, University Lyon 1, UMR CNRS 5558, Villeurbanne, France.
Curr Opin Environ Sci Health ; 31: 1-8, 2023 Feb.
Article em En | MEDLINE | ID: mdl-36741274
ABSTRACT
New Approach Methodologies (NAMs) provide tools for supporting both human and environmental risk assessment (HRA and ERA). This short review provides recent insights regarding the use of NAMs in ERA of food and feed chemicals. We highlight the usefulness of tiered methods supporting weight-of-evidence approaches in relation to problem formulation (i.e., data availability, time, and resource availability). In silico models, including quantitative structure activity relationship models, support filling data gaps when no chemical property or ecotoxicological data are available, and biologically-based models (e.g., toxicokinetic-toxicodynamic models, dynamic energy models, physiologically-based models and species sensitivity distributions) are applicable in more data rich situations, including landscape-based modelling approaches. Particular attention is given to provide practical examples to apply the approaches described in real-world settings. We conclude with future perspectives, with regards to the need for addressing complex challenges such as chemical mixtures and multiple stressors in a wide range of organisms and ecosystems.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article