QTOX · Quantitative extrapolation in ecotoxicology

Quantitative extrapolation in ecotoxicology

Reliable assessment of the ecological risks posed by chemicals is a fundamental component of European policies concerned with safe use of chemicals e.g. REACh, The Green Deal, and the Water Framework Directive. The assumption that adverse effects of chemicals can be extrapolated from laboratory test conditions (in-vitro and in-vivo) to the ecosystem level is inherently embedded in these policies. Also, the availability of extrapolation methods underpins efforts to reduce, replace, and refine the use of animals in toxicity testing. However, current methods for extrapolation of adverse effects across levels of biological organisation have limitations, due to the ecological processes that are disregarded by the models and the paucity of data for parameterisation and validation, with consequent limitations in their predictive capabilities. This lack of mechanistic underpinning raises questions about the robustness of environmental quality standards and confounds efforts to identify the cause of adverse effects and to design remediation strategies. QTOX addresses this situation via development of data efficient modelling tools based on mechanistic knowledge of the underlying processes in the chain from exposure to effects, across all levels of biological organisation, with close connection to regulatory endpoints, and under environmentally realistic conditions. The QTOX approach will bridge the gap between standard toxicity data (typically acute effects of single chemicals) and ecologically relevant end points arising from chronic, time variable exposures to mixtures. QTOX aims to develop predictive models for describing the adverse effects of chemicals under realistic long-term exposure scenarios based on systematic knowledge acquired under laboratory and semi-field (mesocosm) conditions. The research objectives are: 1. To develop and validate quantitative mechanistic models for predicting the relationships between dynamic chemical exposure conditions and adverse effects on a range of aquatic organisms at the level of the individual under both laboratory and mesocosm conditions. 2. To elucidate the predictive capabilities of effect models from cellular to the individual and population levels, and validate the models with mesocosm data. 3. To link adverse effects on populations to those on communities (biodiversity, bioproductivity) and validate these with mesocosm data. 4. To identify the best predictors of adverse effects at the ecosystem level, and the potential ecotoxicological consequences of climate change stressors. 5. To develop an integrated data efficient open-access toolbox for quantitative extrapolations in ecotoxicology.

Data: CORDIS, © European Union