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Neo4j > Case Studies > Novartis Utilizes Neo4j Knowledge Graph for Accelerated Drug Discovery
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Novartis Utilizes Neo4j Knowledge Graph for Accelerated Drug Discovery

 Novartis Utilizes Neo4j Knowledge Graph for Accelerated Drug Discovery - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Computer Vision Software
  • Application Infrastructure & Middleware - Data Visualization
Applicable Industries
  • Healthcare & Hospitals
  • Mining
Applicable Functions
  • Product Research & Development
Use Cases
  • Clinical Image Analysis
  • Traffic Monitoring
The Challenge
Novartis faced the challenge of combining its historical data stores with the burgeoning phenotypic data and placing it within the larger context of ongoing medical research from around the world.
The Customer


About The Customer
Novartis is a global healthcare company based in Basel, Switzerland. The Novartis Institutes for BioMedical Research comprise the innovation arm of Novartis, with 6,000 researchers at six locations around the globe.
The Solution
Novartis created a knowledge graph stored in Neo4j and devised a processing pipeline for ingesting the latest medical research. They used text mining to extract relevant data from PubMed and populated the graph with their own historical and image data. They also used Neo4j graph algorithms to traverse the graph and identify desired triangular node patterns linking genes, diseases, and compounds.
Quantitative Benefit
  • Using Neo4j, researchers can identify the compounds and genes most closely associated with diseases and examine the evidence for the association in medical literature. The flexibility to navigate multiple data sources is powerful for Novartis.

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