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.
Features
The main features of the software are:
- Open and free: the software is open source and freely downloadable.
- User-friendly: DeEP is easy to use and makes predictions using fixed model parameters. The tool gives background information on all relevant model parameters and provides an output report summarising results and all input data.
- Flexible: The software simultaneously considers two endpoints (reproduction and growth) and any user specified exposure profile can be tested. Users can save and load parameter sets and projects to return to later.
- Reportable and reproducible: DeEP automatically produces a formal report of all results and tool settings.
- Focussed: By focussing on predictions only, DeEP makes DEB modelling accessible to non-specialists. However, the software does not perform model calibration, which must be carried out beforehand.
- Verified: The DEB-TKTD model implementation within the DeEP software has been thoroughly tested and verified. A wide range of settings, pMoAs and extreme cases produced identical or near identical results using DeEP or the BYOM platform in Matlab.
Development
DeEP was co-developed by RIFCON GmbH and Syngenta, with support from Dr. Tjalling Jager/DEBtox Research.