Gencovery is the realisation of an idea that has been maturing since 2013 following a simple observation: developing a drug takes more than 15 years. Out of more than 10,000 molecules tested, only 1 gives a drug. Most of data generated for the other 9,999 molecules remained untapped. If we take the analogy of the iceberg: we use less than 10% of knowledge on the surface of the water and the remaining 90% is a new world of knowledge to explore.
Gencovery purpose is to advance biotech science through data upcycling to sustainably turn knowledge into new insights.
Gencovery is the contraction of the words: GENE and DISCOVERY.
Adama holds a PhD in automatic control and applied mathematics from Ecole Centrale de Nantes and University of Nantes (France). Passionate about the modelling of living systems, he worked as research fellow at the Université Libre de Bruxelles (Belgium) and INERIS/CNRS (France) on the modelling of biological systems (systems oncology, toxicology, bioartificial organs, systems metabolomics). He then moved to industry as software project manager in systems oncology (Sobios, Paris) before joining BIOASTER as bioinformatics scientist and leader of the bioinformatics group. He namely initiated and led the development of a computational platform for the in silico modelling of living cells. Based on these developments, and together with its previous experiences on this technology, he decided to create Gencovery with Wassim and bring this technology to biotechnology industry.
Graduated from the Ecole polytechnique (Palaiseau, France) and the Imperial College of London, Wassim holds a PhD in Systems Biology from the Université Libre de Bruxelles (Belgium), as well as the “agrégation” in mathematics (competitive examination for the French teaching qualification). He worked as a researcher at the INRIA Sophia Antipolis and the Institut de Biologie de l’Ecole Normale Supérieure de Paris (IBENS), and as a research engineer in the private sector (Sobios, Paris) on the design of mathematical and algorithmic solutions for the modeling and simulation of biological systems. His expertise ranges in the field of applied mathematics to biological systems, his research work being essentially devoted to the dynamical modeling and analysis of cellular regulatory networks, such as networks involved in cancer in mammals, in the immune system in mice and humans, or in metabolism in yeast.