Pegasus: a knowledge graph to support drug discovery

11 Nov, 2021



Jeremy Grignard - Servier
The design and deployment of Pegasus will be presented as well as three associated applications. The first one allows the rational selection of chemical sub-libraries for target-based screening with proprietary chemicals. The second presents the derisking of the experimental modality coupling upstream open reading frame and antisense oligonucleotides for target identification and validation. The third one shows the rich perspectives of using phenotypic signatures induced by exogenous and endogenous perturbators in high content screening campaigns on different cellular models. Overall, the Pegasus knowledge graph and its applications rationally support the early drug discovery.

Our third Neo4j Health Care & Life Sciences Workshop has been set up to showcase practical solutions to common problems as well as helping to incubate collaboration, innovation and good practice. Graph databases are powerful tools that are inherently capable of managing vast quantities of data points and the web of relationships between them. As people start turning to tools like Neo4j for answers there are inevitably more questions: data modeling, performance, resilience, interoperability. These are the kinds of questions we want to help you answer.

Learn more: https://neo4j.com/use-cases/life-sciences/

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