Predicting characterization factors of chemical substances from a set of molecular descriptors based on machine learning algorithms

Abstract

Today, thousands of chemical substances are released into the environment because of human activities. It is thus crucial to identify all relevant chemicals that contribute to toxic effects on living organisms, also potentially disturbing the community functioning and the ecosystem services that flow from them. Once identified, chemical substances need to be associated with ecotoxicity factors. Nevertheless, getting such factors usually requires time-, resourcesand animal-costly experiments that it should be possible to avoid. In this perspective, modelling approaches may be particularly helpful if they rely on easy-to-obtain information to be used as predictive variables.