Clinical Trials as Graphs and Vectors

Gemini Data’s resident data scientist and bioinformatician Sixing Huang creates a search engine of clinical trials data with Neo4j, Gemini Explore, and Qdrant.

“As a demonstration, 24 Japanese clinical studies were downloaded from the site. In addition, the English SNOMED CT provides me with the taxonomies for medical conditions and body structures. On the one hand, I used Apache Hop to import the data into the graph database Neo4j. On the other hand, the trial descriptions were embedded and then inserted into the vector database Qdrant. Users can not only search trials semantically on Qdrant, but also learn their details, relationships, and statistics on Neo4j and Gemini Explore. This two-database setup allows users to quickly answer the three example questions above.”

By improving the searchability of clinical trials data providers can ask complex questions of their data sets like, “What trials are targeting leukemia?” and “What trials compare the drugs iberdomide and lenalidomid?”

Read the full walkthrough on Medium.

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