Introduction:

Predictions of environmental adverse effects and pharmacokinetic properties of compounds are areas of great interest. Objectives: The aim of this work is to develop computational models to predict ecotoxicological risk and to predict pharmacokinetic properties.

Methods:

In order to develop the computational models, several databases of toxicity, mode of toxic action, permeability across human barriers and chiral properties were collected. According to the specific study, statistical techniques as well as artificial intelligence and/or machine learning techniques were employed. We used several international software as well as software developed by our groups.

Results:

The main results are the development of new QSAR models to predict environmental toxicity of chemicals, new models to predict the permeability of compounds as well as the computational definition of new chiral descriptors. The results have been published in internationally recognized journals, presented in conferences and have obtained several national and international awards. Conclusions: The work permits increasing the collaboration with several universities from Cuba and other countries. The new developed models are available for the international scientific community.

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