, Volume 62, Issue 5, pp 413–422 | Cite as

Comparison of viable cell concentration estimation methods for a mammalian cell cultivation process

  • M. Aehle
  • R. Simutis
  • A. Lübbert
Original Research


Various mechanistic and black-box models were applied for on-line estimations of viable cell concentrations in fed-batch cultivation processes for CHO cells. Data from six fed-batch cultivation experiments were used to identify the underlying models and further six independent data sets were used to determine the performance of the estimators. The performances were quantified by means of the root mean square error (RMSE) between the estimates and the corresponding off-line measured validation data sets. It is shown that even simple techniques based on empirical and linear model approaches provide a fairly good on-line estimation performance. Best results with respect to the validation data sets were obtained with hybrid models, multivariate linear regression technique and support vector regression. Hybrid models provide additional important information about the specific cellular growth rates during the cultivation.


Mammalian cell culture Biomass estimation Multivariate regression Artificial neural networks Support vector regression 



Specific growth rate (h−1)


Specific product formation rate (g e9cells−1 h−1)


Cell concentration (e9cells L−1)


Viable cell concentration (e9cells L−1)


Cells count (e9cells)


Mass of product (g)


Culture weight (kg)


Culture density (kg L−1)


Process time (h)


Oxygen uptake rate (mmol kg−1 h−1)


Carbon dioxide production rate (mmol kg−1 h−1)


Total oxygen uptake rate (mmol h−1)


Total carbon dioxide production rate (mmol h−1)


Total cumulative O2 uptake rate (mmol)


Total cumulative CO2 production rate (mmol)


Consumed Base (g, kg)


Yield O2/Cells, Y OX = 10.34 (mmol e9cells−1)


Yield CO2/Cells, Y CX = 11.37 (mmol e9cells−1)


Maintenance for O2, m O = 0.001 (mmol e9cells−1 h−1)


Maintenance for CO2, m C = 0.001 (mmol e9cells−1 h−1)


Yield Base consumption/Cells Ybx = 9.0e-3 (kg e9cells−1)


Root mean square error (e9cells kg−1)


Weighted average of Base, tOUR, tCPR related models



The financial support from Ministry of Science and Education by means of the Excellence-Initiative Sachsen-Anhalt is gratefully acknowledged.


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Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Institute of Biochemistry and BiotechnologyMartin-Luther-University Halle-WittenbergHalle (Saale)Germany
  2. 2.Institute of Automation and Control SystemsKaunas University of TechnologyKaunasLithuania

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