Data to Design Space: Leveraging JMP for Late-Stage Biosimilar Process Characterization (2026-EU-30MP-2866)

Late-stage bioprocess development presents a critical challenge in establishing process robustness and defining an acceptable design space prior to Process Performance Qualification (PPQ). In biosimilar development, where comparability to the reference molecule and regulatory alignment are essential, managing high-dimensional process characterization data becomes complex and resource-intensive.

This session presents a real-world case study demonstrating how JMP software was used to streamline data analysis, visualization, and modeling for a biosimilar upstream process. Using integrated statistical tools such as definitive screening design (DSD), central composite design (CCD), and the Design Space Profiler, multi-factorial process data were analyzed to identify critical process parameters (CPPs) and quantify their interactions and effects on critical quality attributes (CQAs).

The results illustrate how JMP enabled a data-driven definition of the proven acceptable range (PAR) and design space, significantly improving process understanding and PPQ readiness. Beyond compliance, this approach reduced experimentation time, enhanced predictive capability, and strengthened decision making across development and manufacturing teams. Discover how to apply JMP to implement advanced analytics that bridge scientific understanding and regulatory expectations in late-stage biosimilar development.