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A Novel Approach for Using Dielectric Spectroscopy to Predict Viable Cell Volume (VCV) in Early Process Development

Online monitoring of viable cell volume (VCV) is essential to the development, monitoring, and control of bioprocesses. The commercial availability of steam-sterilizable dielectric-spectroscopy probes has enabled successful adoption of this technology as a key noninvasive method to measure VCV for c...

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Autores principales: Downey, Brandon J, Graham, Lisa J, Breit, Jeffrey F, Glutting, Nathaniel K
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Blackwell Publishing Ltd 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4162991/
https://www.ncbi.nlm.nih.gov/pubmed/24851255
http://dx.doi.org/10.1002/btpr.1845
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author Downey, Brandon J
Graham, Lisa J
Breit, Jeffrey F
Glutting, Nathaniel K
author_facet Downey, Brandon J
Graham, Lisa J
Breit, Jeffrey F
Glutting, Nathaniel K
author_sort Downey, Brandon J
collection PubMed
description Online monitoring of viable cell volume (VCV) is essential to the development, monitoring, and control of bioprocesses. The commercial availability of steam-sterilizable dielectric-spectroscopy probes has enabled successful adoption of this technology as a key noninvasive method to measure VCV for cell-culture processes. Technological challenges still exist, however. For some cell lines, the technique's accuracy in predicting the VCV from probe-permittivity measurements declines as the viability of the cell culture decreases. To investigate the cause of this decrease in accuracy, divergences in predicted vs. actual VCV measurements were directly related to the shape of dielectric frequency scans collected during a cell culture. The changes in the shape of the beta dispersion, which are associated with changes in cell state, are quantified by applying a novel “area ratio” (AR) metric to frequency-scanning data from the dielectric-spectroscopy probes. The AR metric is then used to relate the shape of the beta dispersion to single-frequency permittivity measurements to accurately predict the offline VCV throughout an entire fed-batch run, regardless of cell state. This work demonstrates the possible feasibility of quantifying the shape of the beta dispersion, determined from frequency-scanning data, for enhanced measurement of VCV in mammalian cell cultures by applying a novel shape-characterization technique. In addition, this work demonstrates the utility of using changes in the shape of the beta dispersion to quantify cell health. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 30:479–487, 2014
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spelling pubmed-41629912014-09-22 A Novel Approach for Using Dielectric Spectroscopy to Predict Viable Cell Volume (VCV) in Early Process Development Downey, Brandon J Graham, Lisa J Breit, Jeffrey F Glutting, Nathaniel K Biotechnol Prog Process Sensing and Control Online monitoring of viable cell volume (VCV) is essential to the development, monitoring, and control of bioprocesses. The commercial availability of steam-sterilizable dielectric-spectroscopy probes has enabled successful adoption of this technology as a key noninvasive method to measure VCV for cell-culture processes. Technological challenges still exist, however. For some cell lines, the technique's accuracy in predicting the VCV from probe-permittivity measurements declines as the viability of the cell culture decreases. To investigate the cause of this decrease in accuracy, divergences in predicted vs. actual VCV measurements were directly related to the shape of dielectric frequency scans collected during a cell culture. The changes in the shape of the beta dispersion, which are associated with changes in cell state, are quantified by applying a novel “area ratio” (AR) metric to frequency-scanning data from the dielectric-spectroscopy probes. The AR metric is then used to relate the shape of the beta dispersion to single-frequency permittivity measurements to accurately predict the offline VCV throughout an entire fed-batch run, regardless of cell state. This work demonstrates the possible feasibility of quantifying the shape of the beta dispersion, determined from frequency-scanning data, for enhanced measurement of VCV in mammalian cell cultures by applying a novel shape-characterization technique. In addition, this work demonstrates the utility of using changes in the shape of the beta dispersion to quantify cell health. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 30:479–487, 2014 Blackwell Publishing Ltd 2014-03 2013-12-19 /pmc/articles/PMC4162991/ /pubmed/24851255 http://dx.doi.org/10.1002/btpr.1845 Text en © 2013 The Authors. Published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Process Sensing and Control
Downey, Brandon J
Graham, Lisa J
Breit, Jeffrey F
Glutting, Nathaniel K
A Novel Approach for Using Dielectric Spectroscopy to Predict Viable Cell Volume (VCV) in Early Process Development
title A Novel Approach for Using Dielectric Spectroscopy to Predict Viable Cell Volume (VCV) in Early Process Development
title_full A Novel Approach for Using Dielectric Spectroscopy to Predict Viable Cell Volume (VCV) in Early Process Development
title_fullStr A Novel Approach for Using Dielectric Spectroscopy to Predict Viable Cell Volume (VCV) in Early Process Development
title_full_unstemmed A Novel Approach for Using Dielectric Spectroscopy to Predict Viable Cell Volume (VCV) in Early Process Development
title_short A Novel Approach for Using Dielectric Spectroscopy to Predict Viable Cell Volume (VCV) in Early Process Development
title_sort novel approach for using dielectric spectroscopy to predict viable cell volume (vcv) in early process development
topic Process Sensing and Control
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4162991/
https://www.ncbi.nlm.nih.gov/pubmed/24851255
http://dx.doi.org/10.1002/btpr.1845
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