Less Writing, More Science: Automated Reports by Integrating JMP and Python (2026-US-30MP-2916)

To support regulatory filings, the Process Characterization and Cell Banking group at Regeneron executes small-scale laboratory studies to generate characterization models. Historically, analyzing results and assembling reports has been a tedious, months-long effort, with final reports spanning hundreds of pages. By combining JMP’s scripting capabilities with Python, we have developed an automation tool to significantly enhance efficiency while maintaining scientific rigor.

The report automation tool comprises two parts: standardized statistic analyses using JMP scripts and document generation using Python. The first component consists of flexible analytical workflows written in JSL that adapt and run based on the input data set and selected analyses. While we have previously utilized standalone JMP scripts for specific analyses, this tool connects these scripts into larger analytical workflows.

The second component employs Python scripts that extract analysis results and automatically format them into structured Word documents. By focusing on automating routine analyses while flagging areas requiring further investigation, this tool eliminates repetitive tasks, ensures consistency across reports, and achieves substantial time savings while preserving scientific judgment and interpretation.

This solution demonstrates how JMP's scripting capabilities, when strategically integrated with complementary tools, can be used to develop flexible analytical systems that automate documentation workflows in the biopharmaceutical space.