Qtox Doctoral Network

chemical risk assessment typically involves extrapolation of effects observed in-vitro and in-vivo under laboratory conditions to predictions of effects at the ecosystem level. this is a very challenging task and current extrapolation models have limitations, notably due to a number of ecological processes that are disregarded by the models and the paucity of data for parameterisation and validation. qtox will develop mechanistic knowledge and data-efficient modelling tools to bridge the gap between standard toxicity data and ecologically relevant endpoints arising from chronic, time variable exposures to chemical mixtures. the results will be achieved through an interdisciplinary and intersectoral research and training program in which 10 doctoral candidates will characterise the mechanistic processes describing the successive events from exposure to ecosystem-level effects and develop models for extrapolation of adverse effects across levels of biological organization under environ