We were in the JRC Summer School

Participation of ProtoQSAR in the “JRC Summer School 2019”

Our collaborators Sergi Gómez and Elizabeth Goya have presented their work at the summer school “Non-animal approaches in Science: challenges & future directions”, held at the “Joint Research Center” (JRC) in Ispra (Italy) the 21st – 24th May. Different sessions took place during these four days, dedicated both to the legal obligations for the replacement of animals slaughtered for scientific purposes in the EU and to the latest advances in the existing alternative methods. Different debates were also held on these topics and about the future in this area.

The European Commission’s Joint Research Centre (JRC) is the entity that runs the EU Reference Laboratory for alternatives to animal testing (EURL ECVAM). The aim of the JRC Summer School is to share knowledge and experience on the latest non-animal approaches used in research and testing, including in vitro methods and computational modelling. In addition, the intention is to explore the role of the “three Rs” (Replacement, Reduction and Refinement of animal experiments) in science today through focused seminars and debates.

ProtoQSAR presented its computational strategy to complete the 3Rs and alternative methods to animal testing through two posters:

  • Sergi Gómez presented a recently developed QSAR model for the prediction of algae growth inhibition caused by biocides. This model was created previous establishment, for the first time, of a specific chemical space characterizing known biocidal compounds. Next, a mixed model integrating a qualitative QSAR (LDA) and a quantitative one (ANN) were combined, resulting in a very good evaluation of biocides considered toxic and non-toxic (around 80% predictive efficacy in the set of validation compounds).
  • Elizabeth Goya presented the in silico evaluation of the potential endocrine disruption of chemical compounds via antagonism to the AhR receptor (aryl hydrocarbon). To generate the models, we have developed the largest AhR antagonism database known to date, and from that information two complementary computational models were generated, a QSAR model and a toxicophore mapping. This study has been developed in collaboration with specialists of Liège University (Belgium) and the Department of Pharmacology of the University of Valencia.