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Poster

Mathematical Modeling of MDCK Cell Growth by the Use of On-line Data

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons86410

Möhler,  L.
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons86258

Bock,  A.
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons86461

Sann,  H.
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons86448

Reichl,  U.
Otto-von-Guericke-Universität Magdeburg;
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Zitation

Möhler, L., Bock, A., Sann, H., & Reichl, U. (2003). Mathematical Modeling of MDCK Cell Growth by the Use of On-line Data. Poster presented at DECHEMA Jahrestagung der Biotechnologen, Munich, Germany.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-9F4F-D
Zusammenfassung
Many existing as well as potential new drugs such as monoclonal antibodies, recombinant proteins or vaccines are produced in animal cells which shows poor productivity compared to classical fermentation processes. To achieve the full potential of these production methods, not only highly developed cell culture technology and sophisticated downstream processing but also a qualitative and quantitative description of the complex mechanism underlying cell growth and product formationis required. With a process of equine influenza virus production as an example we focus on cell growth, scale-up and virus production in microcarrier cultures; mathematical modeling of cell growth and virus replication; process monitoring and control; downstream processing with respect to improvements of yields, purity and safety. Besides detailed analysis of growth and morphology of animal cells on microcarries, specific oxygen uptake rates and consumption of the most important substrates, mathematical modeling plays a cruical role in understanding metabolic processes. Here we introduce a mathematical for the growth of adherent cell lines taking into account glucose and glutamine consumption as well as ammonia and lactate production. Additionally we show the correlation between base consumption and lactate production and discuss the profiles of oxygen uptake ratess (OUR) during the cell growth. We are planning to use this model to develop feeding strategies especially for high cell-density and perfusion cultures, thereby providing optimal substrate concentrations in every process stage and reducing production of inhibitory metabolites.