Literature DB >> 18171074

Segregated mathematical model for growth of anchorage-dependent MDCK cells in microcarrier culture.

Lars Möhler1, Andreas Bock, Udo Reichl.   

Abstract

To describe the growth behavior of anchorage-dependent mammalian cells in microcarrier systems, various approaches comprising deterministic and stochastic single cell models as well as automaton-based models have been presented in the past. The growth restriction of these often contact-inhibited cells by spatial effects is described at levels with different complexity but for the most part not taking into account their metabolic background. Compared to suspension cell lines these cells have a comparatively long lag phase required for attachment and start of proliferation on the microcarrier. After an initial phase of exponential growth only a moderate specific growth rate is achieved due to restrictions in space available for cell growth, limiting medium components, and accumulation of growth inhibitors. Here, a basic deterministic unstructured segregated cell model for growth of Madin Darby Canine Kidney (MDCK) cells used in influenza vaccine production is described. Four classes of cells are considered: cells on microcarriers, cells in suspension, dead cells, and lysed cells. Based on experimental data, cell attachment and detachment is taken explicitly into account. The model allows simulation of the overall growth behavior in microcarrier culture, including the lag phase. In addition, it describes the time course of uptake and release of key metabolites and the identification of parameters relevant for the design and optimization of vaccine manufacturing processes.

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Year:  2008        PMID: 18171074     DOI: 10.1021/bp0701923

Source DB:  PubMed          Journal:  Biotechnol Prog        ISSN: 1520-6033


  5 in total

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5.  Tracking changes in adaptation to suspension growth for MDCK cells: cell growth correlates with levels of metabolites, enzymes and proteins.

Authors:  Sabine Pech; Markus Rehberg; Robert Janke; Dirk Benndorf; Yvonne Genzel; Thilo Muth; Albert Sickmann; Erdmann Rapp; Udo Reichl
Journal:  Appl Microbiol Biotechnol       Date:  2021-02-13       Impact factor: 4.813

  5 in total

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