Optimization and robustness analysis of hybridoma cell fed-batch cultures using the overflow metabolism model

• Published in: Bioprocess and biosystems engineering Vol. 37; no. 8; pp. 1637 - 1652
• Main Authors: Amribt, Z., Dewasme, L., Vande Wouwer, A., Bogaerts, Ph
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01-08-2014; Springer Nature B.V
• Subjects: Ammonia - metabolism; Animals; Biomass; Biotechnology; Cell Culture Techniques - methods; Chemistry; Chemistry and Materials Science; Environmental Engineering/Biotechnology; Feeding rates; Food Science; Glucose; Glucose - metabolism; Glutamine - metabolism; Hybridomas - cytology; Hybridomas - metabolism; Industrial and Production Engineering; Industrial Chemistry/Chemical Engineering; Lactic Acid - metabolism; Mice; Models, Biological; Monoclonal antibodies; Optimization; Original Paper; Overflow; Oxygen Consumption; Productivity; Hybridoma cultures; Biomass productivity; Overflow metabolism; Optimal feeding profiles; Bioprocess optimization; Robustness analysis
• ISSN: 1615-7591; 1615-7605
• DOI: 10.1007/s00449-014-1136-2

The maximization of biomass productivity in fed-batch cultures of hybridoma cells is analyzed based on the overflow metabolism model. Due to overflow metabolism, often attributed to limited oxygen capacity, lactate and ammonia are formed when the substrate concentrations (glucose and glutamine) are above a critical value, which results in a decrease in biomass productivity. Optimal feeding rate, on the one hand, for a single feed stream containing both glucose and glutamine and, on the other hand, for two separate feed streams of glucose and glutamine are determined using a Nelder–Mead simplex optimization algorithm. The optimal multi exponential feed rate trajectory improves the biomass productivity by 10 % as compared to the optimal single exponential feed rate. Moreover, this result is validated by the one obtained with the analytical approach in which glucose and glutamine are fed to the culture so as to control the hybridoma cells at the critical metabolic state, which allows maximizing the biomass productivity. The robustness analysis of optimal feeding profiles obtained with different optimization strategies is considered, first, with respect to parameter uncertainties and, finally, to model structure errors.