Aurelie Bornot completed her PhD in 2009 at the University Denis Diderot Paris 7 and the (French) National Institute for Blood Transfusion (INTS), focusing on protein local structure and flexibility prediction using machine learning. She received an award from L'Oréal France – UNESCO – French Science Academy for the quality of her PhD research. In parallel, she worked as a consultant for L’Oréal Paris and delivered a predictive model for compound in vivo toxicity using in vitro data within the framework of the REACh European regulation and of the 7th Amendment for cosmetic products. Aurelie joined AstraZeneca in 2009, as a postdoctoral scientist to developed a workflow for a systematic identification of multi-targeted ligand opportunities by combining computational biology and computational chemistry perspectives. Since then she progressed in the company to a director position, now leading a group focusing on bioinformatics for target and hit identification/validation using mainly proteomics analysis, multiOmics integration, DNA-encoded library screening and protein recombinant expression prediction.