Development of a scale down cell culture model using multivariate analysis as a qualification tool.

Area of Science:

• Biotechnology
• Bioprocess Engineering
• Mammalian Cell Culture

Background:

• Developing representative scale down models is critical for regulatory activities like process validation and Quality by Design.
• Manufacturing bioreactor performance often differs from bench scale due to geometric variations, impacting cell growth, protein productivity, and dissolved carbon dioxide.
• A robust scale down model is essential for defining the design space and ensuring process consistency.

Purpose of the Study:

• To develop and improve a bench scale cell culture model that accurately mimics historical manufacturing scale performance for a late-stage Chinese Hamster Ovary (CHO)-based monoclonal antibody program.
• To identify and address performance gaps between manufacturing and bench scales.
• To propose a comprehensive approach for small-scale model qualification.

Main Methods:

• Utilized multivariate analysis (MVA) alongside traditional univariate analysis to identify scale-related performance differences.
• Implemented process adjustments at the bench scale based on identified gaps.
• Employed a case study approach for a late-stage monoclonal antibody program.

Main Results:

• Achieved an improved scale down cell culture process model that better represents manufacturing scale performance.
• Successfully identified key parameters and differences between scales using MVA.
• Demonstrated the feasibility of using MVA for scale down model development and optimization.

Conclusions:

• The developed bench scale model effectively mimics manufacturing performance, supporting regulatory activities.
• Multivariate analysis is a powerful tool for identifying scale-up challenges and optimizing bioprocess models.
• Proposed a qualification approach involving MVA, physiological rate comparison, and product quality attribute assessment for robust scale down models.