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.
Register now to reserve your seat.
Jeremy Grignard is a Data Scientist at the Servier Research Institute. He obtained his engineering degree from the École Centrale d’Électronique of Paris in Computer Science & Big Data in 2017, followed with a Specialised Master in Applied Mathematics from École Polytechnique - Université Paris-Saclay in 2018. He recently finalised his PhD in Computer Science, Data and Artificial Intelligence at École Polytechnique - Polytechnic Institute of Paris under the supervision of François Fages and Thierry Dorval. As part of his thesis, he developed computational methods derived from knowledge graphs, data science and mathematical modelling to improve the primary phases of drug discovery.
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