2019_HFB.pdf (11.64 MB)
Mathematical modelling of a liver hollow fibre bioreactor
journal contribution
posted on 2019-05-21, 08:32 authored by Ian Sorrell, Rebecca Shipley, Sophie Regan, Iain Gardner, Michael P. Storm, Marianne J. Ellis, John WardJohn Ward, Dominic P. Williams, Pratibha Mistry, Jose D. Salazar, Andrew Scott, Steven WebbA mathematical model has been developed to assist with the development ofa hollow fibre bioreactor (HFB) forhepatotoxicity testing of xenobiotics; specifically, to informthe HFBoperating set-up, interpret data from HFB outputsand aid in optimizingHFBdesign to mimic certain hepatic physiological conditions. Additionally,the mathematical model has been used to identify the key HFB and compound parameters that will affect xenobiotic clearance. The analysis of this model has produced novel results that allow the operating set-up to be calculated,and predictions of compound clearanceto begenerated.The mathematical modelpredictsthe inlet oxygen concentration and volumetric flow ratethat gives a physiological oxygen gradient in the HFB to mimic a liver sinusoid. It has also been used to predict the concentration gradients and clearanceof a test drug and paradigm hepatotoxin, paracetamol (APAP).The effect of altering theHFBdimensions and fibre propertieson APAP clearance under the condition of a physiological oxygen gradientis analysed.These theoretical predictions can be usedto design the most appropriateexperimental set upand data analysis toquantitatively compare the functionality of cell types that are cultured within the HFB to those in other systems
Funding
The work was supported by the National Centrefor the Replacement, Refinement and Reduction of Animals in Research (NC3Rs) CRACK-IT fund, Challenge 5: IVIVE.
History
School
- Science
Department
- Mathematical Sciences
Published in
Journal of Theoretical BiologyVolume
475Pages
25 - 33Citation
SORRELL, I. ... et al., 2019. Mathematical modelling of a liver hollow fibre bioreactor. Journal of Theoretical Biology, 475, pp.25-33.Publisher
© Elsevier BVVersion
- AM (Accepted Manuscript)
Publisher statement
This paper was accepted for publication in the journal Journal of Theoretical Biology and the definitive published version is available at https://doi.org/10.1016/j.jtbi.2019.05.008.Acceptance date
2019-05-13Publication date
2019-05-14ISSN
0022-5193Publisher version
Language
- en