Daphné Grasselly – Enabling Multi-Language Programming in Data Engineering Workflows
www.pydata.org
Streamlining clinical trial output workflows is a key challenge in clinical studies. To deliver reports to health authorities, clinical trial statisticians need to create several scripts to produce deliverables such as output datasets, tables, figures, and listings. Statisticians must also handle specific execution orders to respect dependencies between the generated datasets.
Our project leverages Python programming to automatically generate orchestration workflows from clinical trial project metadata using the Snakemake framework. Snakemake supports the execution of multiple jobs using Docker containers, facilitating multilingual orchestration. This enables our users to run end-to-end (E2E) data engineering workflows using their preferred programming languages, primarily SAS and R. Moreover, Snakemake allows parallel runs for efficient workflow management.
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