The use of multidimensional image-based analysis to accurately monitor cell growth in 3D bioreactor culture

The transition from traditional culture methods towards bioreactor based bioprocessing to produce cells in commercially viable quantities for cell therapy applications requires the development of robust methods to ensure the quality of the cells produced. Standard methods for measuring cell quality...

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Bibliographic Details
Published in:PloS one 2011-10, Vol.6 (10), p.e26104-e26104
Main Authors: Baradez, Marc-Olivier, Marshall, Damian
Format: Article
Language:English
Subjects:
Biology
Bioprocessing
Bioreactors
Cell Adhesion
Cell Count
Cell culture
Cell Culture Techniques - methods
Cell growth
Cell morphology
Cell Proliferation
Computational Biology
Cytology
Engineering
Experiments
Fibroblasts
Fibroblasts - cytology
Humans
Image processing
Imaging, Three-Dimensional - methods
Information processing
Measurement methods
Measurement techniques
Metabolism
Microscopy
Microspheres
Morphology
Principal components analysis
Quality control
Skin - cytology
Stem cells
Surface Properties
Time Factors
Tissue engineering
Trends
Viability
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Summary:The transition from traditional culture methods towards bioreactor based bioprocessing to produce cells in commercially viable quantities for cell therapy applications requires the development of robust methods to ensure the quality of the cells produced. Standard methods for measuring cell quality parameters such as viability provide only limited information making process monitoring and optimisation difficult. Here we describe a 3D image-based approach to develop cell distribution maps which can be used to simultaneously measure the number, confluency and morphology of cells attached to microcarriers in a stirred tank bioreactor. The accuracy of the cell distribution measurements is validated using in silico modelling of synthetic image datasets and is shown to have an accuracy >90%. Using the cell distribution mapping process and principal component analysis we show how cell growth can be quantitatively monitored over a 13 day bioreactor culture period and how changes to manufacture processes such as initial cell seeding density can significantly influence cell morphology and the rate at which cells are produced. Taken together, these results demonstrate how image-based analysis can be incorporated in cell quality control processes facilitating the transition towards bioreactor based manufacture for clinical grade cells.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0026104