I bring 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.

After my Master degree in Chemistry and pharmaceutical technology in 2010, I wanted to specialize in drug discovery to make an impact in the world, helping to advance scientific knowledge in important areas of the medical field.

Moreover, the meeting with Martin Karplus (Nobel laureate in chemistry) during a seminar on molecular dynamics at the University of Padua had certainly a huge impact on the selection of my future scientific research.

That’s why I decided to deepen my studies at the Department of Pharmaceutical sciences of the University of Padova with a PhD focused on G Protein-Coupled Receptors as a Drug Targets.

After my academic studies, prior joining Qubit, I have worked for large agrochemical organizations (Syngenta Crop Protection), biotechs (Heptares Therapeutics, Autifony) where my responsibilities ranged from the implementation of novel computational protein structure prediction methods to compound collection enhancement, HTS activities coordination and project feasibility analysis. I delivered more than 100+ high quality protein-ligand bound models to support medicinal chemistry activities and I am passionate about ligand-protein contact analysis, canonical and non-canonical bio-isosteric substitutions and transformative molecular scaffolds design.

I also teach computational methods applied to drug discovery at the Master of Medical Informatics at the Fachhochschule Nordwestschweiz FHNW, Switzerland

If I am at Qubit Pharmaceuticals today, it is because I realized that there are still limitations in the computational methods applied to drug discovery.

Computational chemistry was often thought in support of chemistry; while at Qubit Pharmaceuticals, thanks to Atlas, which allows accurate calculation of free-energy of binding, it is computational chemistry that can guide the drug discovery process.