(75d) Application of Multivariate Analysis Tools and Design of Experiments (DoE) to Model the Design Space for Characterization of a Mammalian Cell Culture Process

This work will cover the design space characterization of a mammalian cell culture process used for the production of a humanized monoclonal antibody. In any late stage process characterization, the first step is to develop a valid scale-down model, which will ensure the results from small scale testing are representative of manufacturing scale. The first part of this presentation will focus on developing and qualifying a scale-down model using statistical multivariate analysis tools. The selection of an appropriate scale-down parameter, such as k_La or power per unit volume, is important and scenarios will be presented. Furthermore, experimental strategies to model the interrelationship between culture pH, lactate and dissolved CO₂ will be discussed. In the second half, the application of design of experiments (DoE) strategy to fully characterize the cell culture design space will be presented. A fractional factorial central composite design was used to minimize the number of experiments within an aggressive timeline. A response surface model describing the impact of pH, dissolved oxygen, temperature and seed density on growth, titer and critical quality attributes (CQAs) was developed. The process optimum was identified and verified, and the model had good predictability over the entire design space. Based on the outcome of these studies, critical controlled parameters, and critical in-process tests and controls were identified, as well as appropriate action limits set. Collectively, this formed our process control strategy to ensure consistent production of a product that would meet its pre-determined specifications and quality attributes. The modeling and experimental strategies discussed here will have potential application for any stage of process development.