The knowledge graph developed by Semalytix comprises of millions of pharma-relevant entities modeling key knowledge about pharma companies, trials, diseases, medications, side effects as well as relations between all these entities. The knowledge graph is a key technology that is used in all products of Semalytix. The pharma knowledge contained in the knowledge graph is key to contextualize and improve machine learning results by extracting important facts and entities from unstructured documents. Further, it is the basis for precise identification and disambiguation of entities in texts.
On May 08 2019 Dr. Anne Bichteler and Dr. Sebastian Walter attended the event “Neo4J GraphTalk: Health & Life Sciences“ on invitation. The goal of the event was to bring together users of Neo4J technology for use cases and applications in health and the life sciences.
Anne Bichteler and Sebastian Walter gave a talk with the title „VoCE: an AI-enhanced Graph DB Illuminates the Real-world Patient Experience“ in front of a graph-enthusiastic audience from the Pharma and Life Science domain. As part of their talk, they introduced Semalytix’ Knowledge Graph, which is powered by a Neo4J database.
Other speakers also presented extremely interesting use cases for Neo4J Technology in the life science domain. Dr. Alexander Jarasch from the Deutsche Zentrum für Diabetesforschung (DZD)
discussed how the DZD uses Neo4J to map different naming schemas for genes etc in order to reduce time for researchers to analyze specific results and find common patterns among different species.
We are proud of having been part of a great meet up with many lessons learned for us and many new opportunities to be followed up upon.