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Modeling carbon dioxide transport in PDMS-based microfluidic cell culture devices

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Modeling carbon dioxide transport in PDMS-based microfluidic cell culture devices. / Mäki, A. J.; Peltokangas, M.; Kreutzer, J.; Auvinen, S.; Kallio, P.

julkaisussa: Chemical Engineering Science, Vuosikerta 137, 01.12.2015, s. 515-524.

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@article{ff127c4fe0dc4492bd5e00affc8ebc21,
title = "Modeling carbon dioxide transport in PDMS-based microfluidic cell culture devices",
abstract = "Maintaining a proper pH level is crucial for successful cell culturing. Mammalian cells are commonly cultured in incubators, where the cell culture medium is saturated with a mixture of air and 5{\%} carbon dioxide (CO2). Therefore, to keep cell culture medium pH in an acceptable level outside these incubators, a suitable CO2 concentration must be dissolved in the medium. However, it can be very difficult to control and measure precisely local concentration levels. Furthermore, possible undesired concentration gradients generated during long-term cell culturing are almost impossible to detect. Therefore, we have developed a computational model to estimate CO2 transport in silicone-based microfluidic devices. An extensive set of experiments was used to validate the finite element model. The model parameters were obtained using suitable measurement set-ups and the model was validated using a fully functional cell cultivation device. The predictions obtained by the simulations show very good responses to experiments. It is shown in this paper how the model helps to understand the dynamics of CO2 transport in silicone-based cell culturing devices possessing different geometries, thus providing cost-effective means for studying different device designs under a variety of experimental conditions without the need of actual testing. Finally, based on the results from the computational model, an alternative strategy for feeding CO2 is proposed to accelerate the system performance such that a faster and more uniform CO2 concentration response is achieved in the area of interest.",
keywords = "Carbon dioxide, Finite element method, Mass transport, Microfluidics cell culturing, Numerical simulation, pH",
author = "M{\"a}ki, {A. J.} and M. Peltokangas and J. Kreutzer and S. Auvinen and P. Kallio",
note = "ORG=ase,0.9 ORG=mol,0.1",
year = "2015",
month = "12",
day = "1",
doi = "10.1016/j.ces.2015.06.065",
language = "English",
volume = "137",
pages = "515--524",
journal = "Chemical Engineering Science",
issn = "0009-2509",
publisher = "Elsevier",

}

RIS (suitable for import to EndNote) - Lataa

TY - JOUR

T1 - Modeling carbon dioxide transport in PDMS-based microfluidic cell culture devices

AU - Mäki, A. J.

AU - Peltokangas, M.

AU - Kreutzer, J.

AU - Auvinen, S.

AU - Kallio, P.

N1 - ORG=ase,0.9 ORG=mol,0.1

PY - 2015/12/1

Y1 - 2015/12/1

N2 - Maintaining a proper pH level is crucial for successful cell culturing. Mammalian cells are commonly cultured in incubators, where the cell culture medium is saturated with a mixture of air and 5% carbon dioxide (CO2). Therefore, to keep cell culture medium pH in an acceptable level outside these incubators, a suitable CO2 concentration must be dissolved in the medium. However, it can be very difficult to control and measure precisely local concentration levels. Furthermore, possible undesired concentration gradients generated during long-term cell culturing are almost impossible to detect. Therefore, we have developed a computational model to estimate CO2 transport in silicone-based microfluidic devices. An extensive set of experiments was used to validate the finite element model. The model parameters were obtained using suitable measurement set-ups and the model was validated using a fully functional cell cultivation device. The predictions obtained by the simulations show very good responses to experiments. It is shown in this paper how the model helps to understand the dynamics of CO2 transport in silicone-based cell culturing devices possessing different geometries, thus providing cost-effective means for studying different device designs under a variety of experimental conditions without the need of actual testing. Finally, based on the results from the computational model, an alternative strategy for feeding CO2 is proposed to accelerate the system performance such that a faster and more uniform CO2 concentration response is achieved in the area of interest.

AB - Maintaining a proper pH level is crucial for successful cell culturing. Mammalian cells are commonly cultured in incubators, where the cell culture medium is saturated with a mixture of air and 5% carbon dioxide (CO2). Therefore, to keep cell culture medium pH in an acceptable level outside these incubators, a suitable CO2 concentration must be dissolved in the medium. However, it can be very difficult to control and measure precisely local concentration levels. Furthermore, possible undesired concentration gradients generated during long-term cell culturing are almost impossible to detect. Therefore, we have developed a computational model to estimate CO2 transport in silicone-based microfluidic devices. An extensive set of experiments was used to validate the finite element model. The model parameters were obtained using suitable measurement set-ups and the model was validated using a fully functional cell cultivation device. The predictions obtained by the simulations show very good responses to experiments. It is shown in this paper how the model helps to understand the dynamics of CO2 transport in silicone-based cell culturing devices possessing different geometries, thus providing cost-effective means for studying different device designs under a variety of experimental conditions without the need of actual testing. Finally, based on the results from the computational model, an alternative strategy for feeding CO2 is proposed to accelerate the system performance such that a faster and more uniform CO2 concentration response is achieved in the area of interest.

KW - Carbon dioxide

KW - Finite element method

KW - Mass transport

KW - Microfluidics cell culturing

KW - Numerical simulation

KW - pH

U2 - 10.1016/j.ces.2015.06.065

DO - 10.1016/j.ces.2015.06.065

M3 - Article

VL - 137

SP - 515

EP - 524

JO - Chemical Engineering Science

JF - Chemical Engineering Science

SN - 0009-2509

ER -