title: Segmented linear modeling of CHO fed-batch culture and its application to large scale production.
abstract: We describe a systematic approach to model CHO metabolism during biopharmaceutical production across a wide range of cell culture conditions. To this end, we applied the metabolic steady state concept. We analyzed and modeled the production rates of metabolites as a function of the specific growth rate. First, the total number of metabolic steady state phases and the location of the breakpoints were determined by recursive partitioning. For this, the smoothed derivative of the metabolic rates with respect to the growth rate were used followed by hierarchical clustering of the obtained partition. We then applied a piecewise regression to the metabolic rates with the previously determined number of phases. This allowed identifying the growth rates at which the cells underwent a metabolic shift. The resulting model with piecewise linear relationships between metabolic rates and the growth rate did well describe cellular metabolism in the fed-batch cultures. Using the model structure and parameter values from a small-scale cell culture (2 L) training dataset, it was possible to predict metabolic rates of new fed-batch cultures just using the experimental specific growth rates. Such prediction was successful both at the laboratory scale with 2 L bioreactors but also at the production scale of 2000 L. This type of modeling provides a flexible framework to set a solid foundation for metabolic flux analysis and mechanistic type of modeling. Biotechnol. Bioeng. 2017;114: 785-797. © 2016 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.
authors.affiliation: Biochemical Engineering Institute, Saarland University, Campus A1.5, D-66123 Saarbrücken, Germany.|Upstream Process Sciences Biotech Sciences, UCB Pharma S.A., Avenue de l'Industrie, Braine l'Alleud B-1420, Belgium.
authors.forename: Bassem
authors.initials: B
authors.lastname: Ben Yahia
authors.affiliation: Institut de NeuroScience Paris-Saclay (NeuroPSI), UMR CNRS 9197.|Université Paris-Sud, Orsay Cedex 91405, France.
authors.forename: Boris
authors.initials: B
authors.lastname: Gourevitch
authors.affiliation: Upstream Process Sciences Biotech Sciences, UCB Pharma S.A., Avenue de l'Industrie, Braine l'Alleud B-1420, Belgium.
authors.forename: Laetitia
authors.initials: L
authors.lastname: Malphettes
authors.affiliation: Biochemical Engineering Institute, Saarland University, Campus A1.5, D-66123 Saarbrücken, Germany.
authors.forename: Elmar
authors.initials: E
authors.lastname: Heinzle
mesh_terms: D000818:Animals; D000911:Antibodies, Monoclonal / Q000032:analysis* / Q000378:metabolism*; D061249:Batch Cell Culture Techniques / Q000379:methods* / Q000592:standards*; D019149:Bioreactors; D016466:CHO Cells; D002138:Calibration; D006224:Cricetinae; D003412:Cricetulus; D016014:Linear Models; D015203:Reproducibility of Results
chemical_list: D000911:Antibodies, Monoclonal
keywords: Chinese hamster ovary cells; mammalian cell culture; modeling; monoclonal antibody; scale up; segmented regression