Traditional SDTM programming comes with challenges:
- EDC-specific data structures
- Variable inconsistencies
- The complexities of standardizing workflows
How can we streamline these processes while ensuring reproducibility and efficiency?
What You’ll Learn About Using sdtm.oak
This presentation introduces sdtm.oak, an open-source R package designed to automate SDTM programming. Developed as part of the pharmaverse project, sdtm.oak provides a universal, EDC-agnostic solution through reusable algorithms and modular programming. You’ll discover its core features, learn about real-world use cases, and see how it’s driving SDTM automation forward.
Shiyu Chen, data solutions engineer at Atorus™ Research, shares practical examples and programming workflows that demonstrate the package’s capabilities. This presentation also explores the future of SDTM automation — from metadata-driven workflows to AI-assisted code generation.
Atorus is a leader in open-source data analytics and your guide to the most advanced technologies and protocols in the life sciences industry.