| Popis: |
Checking the persistence of a chemical in the environment is extremely important. Regulations like REACH, the European one on chemicals, require the measurements or estimates of the half-life of the chemical in water, sediment, and soil. The use of non-testing methods, like quantitative structure-activity relationship (QSAR) models, is encouraged because it reduces costs and time. To our knowledge, there are very few freely available models for these properties and some are for specific chemical classes. Here, we present three new semi-quantitative models, one for each of the required environmental compartments (water, sediment, and soil). Using literature and REACH registration data, we developed three new counter-propagation artificial neural network models using the CPANNatNIC tool. We calculated the VEGA descriptors, and selected the relevant ones using an internal method in R based on the forward selection technique. The best model for each compartment was implemented in two open-source stand-alone tools, the VEGA platform, and the JANUS tool (https://www.vegahub.eu/). These models were also used by ECHA to build their PBT profiler available in the OECD QSAR toolbox (https://qsartoolbox.org/). Screening and prioritization are also our main target. The models perform well, with R |
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