In-silico characterisation of the Kirkstall QV900 in-vitro system for advanced cell culture

Sean McGinty, Lauren Hyndman, Nigel Mottram, Sean McKee, Steven Webb

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Abstract

We have developed an in-silico model of the Kirkstall Quasi-Vivo QV900 cell culture system. The QV900 consists of a series of connected sealed chambers, within which cells can be cultured in a low shear stress flow environment. By modelling fluid flow and oxygen transport within the chambers, we have been able to simulate flow patterns and shear stress/oxygen levels experienced by the cells, and we have demonstrated that physiologically relevant oxygen concentration gradients can be achieved by configuring connected chambers in a particular way.
LanguageEnglish
Title of host publicationCMBE17
Subtitle of host publication5th International Conference on Computational & Mathematical Biomedical Engineering
EditorsPerumal Nithiarasu, Anne M. Robertson
Place of PublicationSwansea
Pages1174-1177
Number of pages4
Publication statusPublished - 10 Apr 2017
Event5th International Conference on Computational and Mathematical Biomedical Engineering - Pittsburgh, United States
Duration: 10 Apr 201712 Apr 2017

Conference

Conference5th International Conference on Computational and Mathematical Biomedical Engineering
Abbreviated titleCMBE 2017
CountryUnited States
CityPittsburgh
Period10/04/1712/04/17

Fingerprint

Cell Culture
Cell culture
Oxygen
Shear Stress
Shear stress
Cell
Flow Pattern
Flow patterns
Fluid Flow
Flow of fluids
Gradient
Series
Modeling
Model

Keywords

  • cell culture systems
  • bioreactors
  • fluid dynamics
  • drug toxicity testing

Cite this

McGinty, S., Hyndman, L., Mottram, N., McKee, S., & Webb, S. (2017). In-silico characterisation of the Kirkstall QV900 in-vitro system for advanced cell culture. In P. Nithiarasu, & A. M. Robertson (Eds.), CMBE17: 5th International Conference on Computational & Mathematical Biomedical Engineering (pp. 1174-1177). Swansea.
McGinty, Sean ; Hyndman, Lauren ; Mottram, Nigel ; McKee, Sean ; Webb, Steven. / In-silico characterisation of the Kirkstall QV900 in-vitro system for advanced cell culture. CMBE17: 5th International Conference on Computational & Mathematical Biomedical Engineering. editor / Perumal Nithiarasu ; Anne M. Robertson. Swansea, 2017. pp. 1174-1177
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McGinty, S, Hyndman, L, Mottram, N, McKee, S & Webb, S 2017, In-silico characterisation of the Kirkstall QV900 in-vitro system for advanced cell culture. in P Nithiarasu & AM Robertson (eds), CMBE17: 5th International Conference on Computational & Mathematical Biomedical Engineering. Swansea, pp. 1174-1177, 5th International Conference on Computational and Mathematical Biomedical Engineering, Pittsburgh, United States, 10/04/17.

In-silico characterisation of the Kirkstall QV900 in-vitro system for advanced cell culture. / McGinty, Sean; Hyndman, Lauren; Mottram, Nigel; McKee, Sean; Webb, Steven.

CMBE17: 5th International Conference on Computational & Mathematical Biomedical Engineering. ed. / Perumal Nithiarasu; Anne M. Robertson. Swansea, 2017. p. 1174-1177.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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AU - Webb, Steven

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AB - We have developed an in-silico model of the Kirkstall Quasi-Vivo QV900 cell culture system. The QV900 consists of a series of connected sealed chambers, within which cells can be cultured in a low shear stress flow environment. By modelling fluid flow and oxygen transport within the chambers, we have been able to simulate flow patterns and shear stress/oxygen levels experienced by the cells, and we have demonstrated that physiologically relevant oxygen concentration gradients can be achieved by configuring connected chambers in a particular way.

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KW - bioreactors

KW - fluid dynamics

KW - drug toxicity testing

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McGinty S, Hyndman L, Mottram N, McKee S, Webb S. In-silico characterisation of the Kirkstall QV900 in-vitro system for advanced cell culture. In Nithiarasu P, Robertson AM, editors, CMBE17: 5th International Conference on Computational & Mathematical Biomedical Engineering. Swansea. 2017. p. 1174-1177