Powering clinical research innovation: How TriNetX uses Databricks to accelerate drug development

Summary

TriNetX operates a federated real-world health data network spanning more than 230 healthcare organizations and needed infrastructure to make growing volumes of RWD easier to use for clinical research. Databricks now provides the centralized lakehouse architecture, consolidating electronic health record data while supporting custom datasets, consulting, ML models, proprietary algorithms, APIs and self-service access. TriNetX is extending this foundation with a beta Query Assistant for natural-language analysis and a Support Assistant prototype built with Databricks’ Agent Bricks, requiring no programming expertise for the former. In 2025, pharmaceutical clients reduced protocol amendments by up to 50%, while an AI-enhanced site-identification effort achieved a 63% site acceptance rate and nine-day average response time. Other models suggest enrollment conversion could rise from 33% to 85%, with expanded APIs and Genie exploration planned for 2026.

Takeaways

1. 1

   Databricks consolidates TriNetX real-world data and supports custom datasets, consulting, ML models and proprietary algorithms across the network.

2. 2

   The beta Query Assistant lets researchers ask complex questions in natural language and receive analyses without programming expertise; a Support Assistant prototype uses Agent Bricks.

3. 3

   In 2025, TriNetX helped pharmaceutical clients reduce protocol amendments by up to 50%, while an AI-enhanced site-identification effort achieved 63% site acceptance and a nine-day average response time.

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