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.