Connecting the Dots in Early Drug Discovery at Novartis

The Novartis Institutes for BioMedical Research, a pharmaceutical company, has been working on combining heterogeneous data and integrating it into a big knowledge graph to help discover cures for diseases. The underlying problem is how to construct a system of scalable biological knowledge, which involves connecting vast amounts of data and enabling researchers to construct queries for specific triangular relationships between chemical compounds, biological entities, and diseases. Graph database technology plays a significant role in this effort by enabling the capture of the strength of relationships between terms in medical research text, as well as providing a foundation for later queries that link literature to observed chemical or biological data. The company has built a graph database using Neo4j and is now using it to analyze cellular assays and identify connections between compounds, genes, and diseases. The database contains about 30 million nodes, including articles, proteins, gene annotations, and more. By integrating heterogeneous data sources and analyzing relationships, the researchers aim to capture biological knowledge that can be used to understand how compounds interact with cells and develop new medicines.

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