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Protocol for Acute and Chronic Ecotoxicity Testing of the Turquoise Killifish Nothobranchius furzeri
Published on: April 24, 2018
To what extent do fish toxicity studies drive harmonized classification for acute and chronic aquatic hazards?
Marta Sobanska1, Salvador Moncho1, Anna-Maija Nyman1
1European Chemicals Agency, Helsinki, Finland.
None:
The current regulatory risk management of chemicals relies on ecotoxicological data from three trophic levels (algae/plants, invertebrates, and fish) as the surrogate for all aquatic organisms, a long-standing foundation of environmental hazard and risk assessment. To explore opportunities for reducing vertebrate testing while maintaining environmental protection levels, it is essential to better understand the specific contribution of each trophic level to regulatory decision-making. This article analyzed ecotoxicity data for aquatic hazard classification under the Classification, Labelling, and Packaging Regulation, focusing on the role of in vivo fish toxicity data within the European Union's harmonized classification and labelling system. Results indicate that all three trophic levels are important for classification. Without fish data, 12% of substances for acute hazards and 11% for chronic hazards would have less stringent classifications. Thus, omitting fish testing would considerably affect the protection of the aquatic environment. The study also examined a subset of substances confirmed as potent neurotoxicants, comparing acute toxicity data on Daphnia magna to in vivo acute fish toxicity data. The analysis confirms that daphnids were similarly or more sensitive than fish for most investigated neurotoxicants. Therefore, even without acute fish data, these substances would have similar or more stringent classification. However, substance types other than those potent neurotoxicants were not investigated. Moreover, there remains uncertainty for some pyrethroids regarding Daphnia data's sufficiency in assessing hazards, indicating a need for further research. Finally, the study evaluated the use of computational profilers based on quantitative structure-activity relationship models to predict aquatic toxicity. The aim was to investigate whether currently available computational methods can identify chemicals more toxic to fish compared with other trophic levels, focusing the conduct of vertebrate tests only on those substance classes. The analysis revealed a need for better understanding of how different chemical classes affect acute aquatic toxicity across various trophic levels.
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