Design & Stress-Test · Databricks
healthcare organization using Lakebase for patient, provider and member applications
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.
Source
Published by Databricks on its own site — read the original case study on databricks.com ↗
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- 01pharmaceutical company using Agent Bricks for clinical and pharmacovigilance workflows
- 02runs its platform on Databricks/AWS to accelerate drug discovery; the Regeneron Genetics Center built one of the largest genetics databases pairing sequenced exomes with EHRs for 400,000+ people
- 03built 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
- 04transformed its data ecosystem (data silos/redundancy) using Databricks and Unity Catalog; Consumer Health division built reusable core data assets/data products for dashboarding, ad hoc analytics, ML and AI
- 05replaced an aging data warehouse with Databricks; cut data-processing time 69%, data-availability lag 52%, and operating costs 45%
- 06healthcare performance-improvement company using Genie for AI-driven analytics/BI