Off-Gas-Based Soft Sensor for Real-Time Monitoring of Biomass and Metabolism in Chinese Hamster Ovary Cell Continuous Processes in Single-Use Bioreactors

被引:6
作者
Wallocha, Tobias [1 ]
Popp, Oliver [1 ]
机构
[1] Roche Diagnost GmbH, Pharma Res & Early Dev, D-82377 Penzberg, Germany
关键词
process analytical technologies (PAT); off-gas analytic; real-time monitoring; viable cell biomass; perfusion process; continuous process; single-use bioreactor (SUB); oxygen uptake rate (OUR); soft sensor; DIOXIDE EVOLUTION RATES; OXYGEN-UPTAKE RATES; ONLINE ESTIMATION; CULTURES; VOLUME; RECONSTRUCTION; DENSITY; NUMBER; SCALE; BATCH;
D O I
10.3390/pr9112073
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
In mammalian cell culture, especially in pharmaceutical manufacturing and research, biomass and metabolic monitoring are mandatory for various cell culture process steps to develop and, finally, control bioprocesses. As a common measure for biomass, the viable cell density (VCD) or the viable cell volume (VCV) is widely used. This study highlights, for the first time, the advantages of using VCV instead of VCD as a biomass depiction in combination with an oxygen-uptake- rate (OUR)-based soft sensor for real-time biomass estimation and process control in single-use bioreactor (SUBs) continuous processes with Chinese hamster ovary (CHO) cell lines. We investigated a series of 14 technically similar continuous SUB processes, where the same process conditions but different expressing CHO cell lines were used, with respect to biomass growth and oxygen demand to calibrate our model. In addition, we analyzed the key metabolism of the CHO cells in SUB perfusion processes by exometabolomic approaches, highlighting the importance of cell-specific substrate and metabolite consumption and production rate qS analysis to identify distinct metabolic phases. Cell-specific rates for classical mammalian cell culture key substrates and metabolites in CHO perfusion processes showed a good correlation to qOUR, yet, unexpectedly, not for qGluc. Here, we present the soft-sensoring methodology we developed for qPyr to allow for the real-time approximation of cellular metabolism and usage for subsequent, in-depth process monitoring, characterization and optimization.
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页数:23
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