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Dynamic Metabolic Modeling for a MAB Bioprocess
Author(s) -
Gao Jianying,
Gorenflo Volker M.,
Scharer Jeno M.,
Budman Hector M.
Publication year - 2007
Publication title -
biotechnology progress
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.572
H-Index - 129
eISSN - 1520-6033
pISSN - 8756-7938
DOI - 10.1021/bp060089y
Subject(s) - bioprocess , biochemical engineering , monoclonal antibody , metabolic flux analysis , bioprocess engineering , computer science , biological system , flux balance analysis , key (lock) , computational biology , metabolic network , systems biology , chemistry , biology , metabolism , biochemistry , engineering , antibody , immunology , paleontology , computer security
Production of monoclonal antibodies (MAb) for diagnostic or therapeutic applications has become an important task in the pharmaceutical industry. The efficiency of high‐density reactor systems can be potentially increased by model‐based design and control strategies. Therefore, a reliable kinetic model for cell metabolism is required. A systematic procedure based on metabolic modeling is used to model nutrient uptake and key product formation in a MAb bioprocess during both the growth and post‐growth phases. The approach combines the key advantages of stoichiometric and kinetic models into a complete metabolic network while integrating the regulation and control of cellular activity. This modeling procedure can be easily applied to any cell line during both the cell growth and post‐growth phases. Quadratic programming (QP) has been identified as a suitable method to solve the underdetermined constrained problem related to model parameter identification. The approach is illustrated for the case of murine hybridoma cells cultivated in stirred spinners.