Built a knowledge graph and recommendation engine on Databricks to help scientists mine millions of data points across thousands of sources and generate novel drug-target hypotheses; separately used Agent Bricks to parse 400,000+ clinical trial documents into structured data in under 60 minutes with no code

AstraZeneca built a knowledge graph and recommendation engine on Databricks to help scientists mine millions of data points across thousands of sources and generate novel drug-target hypotheses; separately used Agent Bricks to parse 400,000+ clinical trial documents into structured data in under 60 minutes with no code. Named alongside Databricks in Databricks’s own account of this story: Agent Bricks.

Databricks is a unified data-and-AI lakehouse platform, used across pharma R&D for everything from early prototyping to production model governance via Unity Catalog.

This sits in the Design & Stress-Test stage of the AI use-case lifecycle: Named examples from the tools pharma teams use to scope, prototype and benchmark an AI use case before committing to build it — data-catalog, sandbox and evaluation platforms.