Davide Sabbadin brings several years of industrial agrochemical and drug discovery expertise in the domain of pre-clinical lead-discovery and optimization projects in targeting ion-channels, GPCRs and cytosolic proteins. Prior joining Qubit, he worked for large agrochemical organizations (Syngenta Crop Protection), biotechs (Heptares Therapeutics, Autifony) where his responsibilities ranged from the implementation of novel computational protein structure prediction methods to compound collection enhancement, HTS activities coordination and project feasibility analysis. He delivered more than 100+ high quality protein-ligand bound models to support medicinal chemistry activities and he is passionate about ligand-protein contact analysis, canonical and non-canonical bio-isosteric substitutions and transformative molecular scaffolds design. He teaches computational methods applied to drug discovery at the Master of Medical Informatics at the Fachhochschule Nordwestschweiz FHNW, Switzerland