Deriving Design Space for Upstream Process Optimization of Biosimilars: A JMP DOE Case Study (2026-EU-30MP-2824)

This case study applies a Quality by Design (QbD) approach to optimize the upstream process of a biosimilar using design of experiments (DOE) in JMP software. The goal was to derive a robust design space that enhances process understanding and control.

Since its goal was to improve efficiency, a streamlined design with fewer than 30 runs was needed to identify optimal parameters while minimizing cost and time.

A central composite design (CCD) in JMP DOE was applied to study five factors (pH, initial temperature, final temperature, DO, and seed viable cell density) to capture main effects, interactions, and quadratic terms with minimal confounding. The design required 28 runs and achieved over 80% power for detecting main effects. DOE data analysis using JMP Fit Model and stepwise regression identified significant factors. Visualization tools like prediction profiles and contour plots aided in interpreting response behavior and identifying significant factor settings. Design space was proposed based on historical ranges and predicted responses, supporting process robustness by defining optimal factor settings that ensure consistent product quality and reduce variability.

This presentation is relevant for process development professionals, offering practical DOE strategies to define design space, optimize parameters, and reduce experimental cost, time, and rework.