Segmented linear modeling of CHO fed-batch culture and its application to large scale production

被引:21
作者
Ben Yahia, Bassem [1 ,2 ]
Gourevitch, Boris [3 ,4 ]
Malphettes, Laetitia [2 ]
Heinzle, Elmar [1 ]
机构
[1] Univ Saarland, Biochem Engn Inst, Campus A1-5, D-66123 Saarbrucken, Germany
[2] UCB Pharma SA, Upstream Proc Sci Biotech Sci, Ave Ind, B-1420 Braine Lalleud, Belgium
[3] UMR CNRS 9197, Inst NeuroSci Paris Saclay NeuroPSI, Gif Sur Yvette, France
[4] Univ Paris 11, F-91405 Orsay, France
关键词
monoclonal antibody; Chinese hamster ovary cells; segmented regression; modeling; mammalian cell culture; scale up; HAMSTER OVARY CELLS; MULTIVARIATE-ANALYSIS; PIECEWISE REGRESSION; MAINTENANCE ENERGY; MAMMALIAN-CELLS; SYSTEMS BIOLOGY; GROWTH; METABOLISM; FERMENTATION; DYNAMICS;
D O I
10.1002/bit.26214
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
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 (2L) 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 2L bioreactors but also at the production scale of 2000L. 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. (c) 2016 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.
引用
收藏
页码:785 / 797
页数:13
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