DeEP (DEB-TKTD EPx Predictor) is a user-friendly software to predict the effects of time-varying pesticide exposure profiles on non-target species. Using the toxicokinetic-toxicodynamic modelling based on Dynamic Energy Budget theory (DEB-TKTD) - specifically DEBtox2019 (Jager, 2020) - DeEP considers the toxicant’s impacts on the rates of reproduction and growth. Model parameters (i.e. calibrated to the results of toxicity tests) need to be provided by the user. These are used to predict the X% Effect Profile multiplier or ‘EPx multiplier’ (Ashauer et al., 2013), which can be considered in ecological risk assessment (ERA) of chemicals such as pesticides. This is the factor by which a user-provided exposure profile would need to be multiplied in order to elicit an X% reduction to any one endpoint. Thereby, the EPx can be interpreted as a safety margin for the specific exposure profile.
The main features of the software are:
DeEP was co-developed by RIFCON GmbH and Syngenta, with support from Dr. Tjalling Jager/DEBtox Research.