Case Study: AstraZeneca achieves faster AI-driven drug discovery with Databricks

How AI is Changing Drug Discovery

AstraZeneca, a global biopharmaceutical company, faced a major data challenge: scientists were unable to rapidly use the growing volume of disjointed internal and public scientific information to make timely drug-discovery decisions. With data spread across hundreds of sources and millions of data points, their teams needed scalable, low‑maintenance infrastructure and better support for data science and machine learning workflows.

Using the Databricks Lakehouse Platform, AstraZeneca built scalable, performant data pipelines and a knowledge graph that powers a recommendation engine and NLP-driven analysis of scientific literature. The fully managed platform enabled faster model development and deployment, processing millions of data points from thousands of sources, improving operational efficiency and team productivity, and accelerating time‑to‑insight for novel drug hypotheses.

AstraZeneca

Eliseo Papa

Computational Biologist