Databases for pesticide ecotoxicity

Comparison ofin silicomodels for prediction ofDaphnia magnaacute toxicity

“…Furthermore, assessing the exact sign of the error given by these three models, errors with DEMETRA were much smaller than with the others and the underpredictions were fewer than the overpredictions. In fact the DEMETRA model was developed by designing a hybrid model to avoid false negatives [5,12]. If QSAR models are used for regulatory purposes, the errors generating underestimation are of much more concern than overestimates.…”

“…The US Environmental Protection Agency (USEPA) Office of Pesticide Programs (OPP) was the primary source database for this project. Ass explained elsewhere [12], different processes have been run on this dataset to ensure adequate quality.…”

Developing innovative in silico models with EFSA's OpenFoodTox database

“…2. For the bee toxicity model, acute contact toxicity data (LC 50 ) in bees were collected from the DEMETRA database (Benfenati et al, 2011), the terrestrial US-EPA ECOTOX database present in the OECD QSAR Toolbox, vers. 3.3.…”

“…Compounds in the datasets were classified as low toxicity for LD 50 greater than 100 µg/bee, moderately toxic for LD 50 between 1 and 100 µg/bee, and highly toxic for LD50 lower than 1 µg/bee according to the Pesticide Properties Database (PPDB) (http://sitem.herts.ac.uk/aeru/iupac/docs/Background_and_Support.pdf). For compounds with more than one experimental value, the associated variability was evaluated using the strategy employed by Benfenati and collaborators (Benfenati et al, 2011) as the ratio between duplicated experimental data (x/y) as follows:…”

Towards the Development of Innovative Quantitative Structure-Activity Relationship Models for Human and Ecological Risk Assessment of Chemicals and their Mixtures

“…These QSAR models for species of ecological importance are often developed using the well-characterised relationships between the physico-chemical properties of chemicals, their persistence and toxicity as well as their global environmental fate (Domine et al, 1992;Devillers and Flatin, 2000). QSAR models have already been applied to the prediction of ecotoxicological endpoints in species of ecological importance including trout, daphnia, quail and bees within the project DEMETRA (Benfenati et al, 2011) and more recently for qualitative and quantitative toxici ty prediction in bees using a global quantitative structure-toxicity relationship model (QSTR) (Singh et al, 2014). To address the needs for QSAR models predicting toxicity of PPPs in honey bees, we developed an in-house software using databases on acute contact data in honey bees from different sources and a k-Nearest Neighbor algorithm (k-NN).…”