Enhancing early-stage cell culture process development efficiency using an integrated approach of high-throughput miniaturized bioreactors and definitive screening design

Abstract

Rapidly expanding pipelines in biopharmaceutical industry and increasingly stringent requirements from regulatory agencies call for a more efficient and rational study design at early-stage cell culture process development. Recent developments in high-throughput bioreactor system and design of experiments (DoE) enable cell culture process development sector to meet such demand by integrating both technological advances. In this study, we compared varied forms of fractional factorial designs (FFDs) and definitive screening design (DSD) covering key process parameters such as temperature shift target, temperature shift timing, feed strategy, pH, dissolved oxygen, harvest time and additives in Ambr® 15 bioreactors to better understand the initial cell culture process and thus optimize it. Results showed that DSD was more effective and efficient in detecting both main and quadratic effects comparing to FFDs. Comparison of varied available model development strategies revealed that two-stage forward regression combined with corrected Akaike's information criterion (AICc) and least absolute shrinkage and selection operator (LASSO) regression combined with self-validated ensembled models (SVEM) offered superior predictive capability. Moreover, key DoE regularities was evaluated for their validity. In conclusion, DSD is a suitable experimental design for the early-stage cell culture process development if quadratic effects might exist. Statistical models derived based on DSD-based dataset could be applied for predictive optimization of antibody producing bioprocess while regularities such as effect heredity and effect hierarchy might be relaxed considering higher-order interaction effects are more likely to existed for a cell-based biological system.