Due to the high cost of drug development and low response among cancer patients for approved drugs, it is clear that patient stratification, biomarker discovery and strong understanding of disease mechanism are key challenges of oncology. Better pharmacogenomics involves better drug response prediction but also better understanding of the causal mechanisms that link induced changes in molecular level events to emergent changes in phenotype at the organism level. Machine learning on drug treated cancer cell lines, polypharmacology, drug combination, the huge amount of biomedical data of open science, as well as a holistic approach are important points to consider, with the aim to accelerate drug development, improve diagnostic test and better use of already approved drugs (alone or in combination). Those are my current research interests.
|2015-date||PhD Candidate, JRC-COMBINE, Saez-Rodriguez Group|
|2015||Internship in the Hunt lab at UCSF (California, USA)|
|2014-2015||Master in Systems and Synthetic biology, Genopole (France)|
|2007-2014||Doctorate of Pharmacy, University of Paris-Saclay (France)|