A comprehensive, interconnected understanding of diverse scientific data is paramount in the ever-evolving landscape of pharmaceutical and biotechnological advancements. This is primarily due to the variety of sources from which scientific data is collected- structural, cellular, chemical or phenotypic sciences- and also because they correspond to heterogeneous pharmaco-biological concepts.
Our webinar will shed light on the innovative Pegasus knowledge graph, which has the power to reshape the way you approach drug development. Learn how this approach helps capitalise on currently available data and explore the complex environment of therapeutic targets to identify relevant screening modalities and to design new experiments.
Thierry Dorval received a Ph.D. in image analysis and Artificial Intelligence from University Pierre & Marie Curie and then joined the institut Pasteur Korea in 2005 as a group leader specialized in High Content Screening applied to cellular differentiation and toxicity prediction.
In 2012 he joined AstraZeneca, where his activities were about developing and advising on quantitative image and data analysis solutions in support of high content phenotypic screening.
In 2015 he joined Servier, France, to lead the Data Sciences & Data Management pole of activities where he is in charge of optimizing the early stages of the drug discovery by taking advantage of cutting-edge computational approaches. This includes usage of Artificial Intelligence, knowledge graph database, system modeling and sequences design applied to multiple modalities including small molecules, antibodies, and oligonucleotides.
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