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Analytical platform for bioprocesses with adherent mammalian cells

MPG-Autoren
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Genzel,  Y.
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Vester,  D.
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Schulze-Horsel,  J.
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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

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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

Genzel, Y., Vester, D., Schulze-Horsel, J., Bock, A., & Reichl, U. (2007). Analytical platform for bioprocesses with adherent mammalian cells. Poster presented at MPG-CNRS Joint Workshop on Systems Biology, Berlin, Germany.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0013-972D-C
Zusammenfassung
Detailed data sets from validated analytical methods for animal cell culture-based production processes are needed for quantitative studies in systems biology approaches. Typically, cell culture media contain more than 50 compounds, in addition to undefined components such as hydrolysates or sera. Monitoring metabolites in the medium can indicate nutrient limitations or accumulation of inhibitors as well as switches in metabolism during cell growth and product formation. Adherent cells often used in viral vaccine manufacturing need time to attach to a growth surface (lag time) before they start to grow exponentially. Once growth surface becomes limited, growth slows down, cells go into G0-phase and switch to maintenance metabolism. During virus production phase further changes in metabolism take place before going into apoptosis. Several analytical methods were set-up on an influenza virus production process with adherent mammalian cells to generate detailed data sets for process characterization. Some of these methods will be presented to show their potential in monitoring, process design and optimization. Thereby, extracellular metabolites (glucose, lactate, ammonia, amino acids), cell numbers (cells on microcarriers and in supernatant) and cell physiology (cell cycle and apoptosis using flow cytometry), protein levels (2D-DIGE), virus titers and online-data will be discussed.