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• W2035530007 abstract "Markov chain Monte Carlo (MCMC) method was applied to model kinetics of a fed-batch Chinese hamster ovary cell culture process in 5,000-L bioreactors. The kinetic model consists of six differential equations, which describe dynamics of viable cell density and concentrations of glucose, glutamine, ammonia, lactate, and the antibody fusion protein B1 (B1). The kinetic model has 18 parameters, six of which were calculated from the cell culture data, whereas the other 12 were estimated from a training data set that comprised of seven cell culture runs using a MCMC method. The model was confirmed in two validation data sets that represented a perturbation of the cell culture condition. The agreement between the predicted and measured values of both validation data sets may indicate high reliability of the model estimates. The kinetic model uniquely incorporated the ammonia removal and the exponential function of B1 protein concentration. The model indicated that ammonia and lactate play critical roles in cell growth and that low concentrations of glucose (0.17 mM) and glutamine (0.09 mM) in the cell culture medium may help reduce ammonia and lactate production. The model demonstrated that 83% of the glucose consumed was used for cell maintenance during the late phase of the cell cultures, whereas the maintenance coefficient for glutamine was negligible. Finally, the kinetic model suggests that it is critical for B1 production to sustain a high number of viable cells. The MCMC methodology may be a useful tool for modeling kinetics of a fed-batch mammalian cell culture process. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2010" @default.
• W2035530007 created "2016-06-24" @default.
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• W2035530007 date "2010-01-01" @default.
• W2035530007 modified "2023-10-17" @default.
• W2035530007 title "Modeling kinetics of a large-scale fed-batch CHO cell culture by Markov chain Monte Carlo method" @default.
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• W2035530007 doi "https://doi.org/10.1002/btpr.284" @default.
• W2035530007 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/19834967" @default.
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