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Sorrell, I, Shipley, RJ, Regan, S, Gardner, I, Storm, MP, Ellis, M, Ward, J, Williams, D, Mistry, P, Salazar, JD, Scott, A and Webb, SD (2019) Mathematical modelling of a liver hollow fibre bioreactor. Journal of Theoretical Biology, 475. pp. 25-33. ISSN 0022-5193
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SorrellMML2018_clean.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (1MB) | Preview |
Abstract
A mathematical model has been developed to assist with the development of a hollow fibre bioreactor (HFB) for hepatotoxicity testing of xenobiotics; specifically, to inform the HFB operating set-up, interpret data from HFB outputs and aid in optimizing HFB design 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 clearance to be generated. The mathematical model predicts the inlet oxygen concentration and volumetric flow rate that gives a physiological oxygen gradient in the HFB to mimic a liver sinusoid. It has also been used to predict the concentration gradients and clearance of a test drug and paradigm hepatotoxin, paracetamol (APAP). The effect of altering the HFB dimensions and fibre properties on APAP clearance under the condition of a physiological oxygen gradient is analysed. These theoretical predictions can be used to design the most appropriate experimental set up and data analysis to quantitatively compare the functionality of cell types that are cultured within the HFB to those in other systems.
| Item Type: | Article |
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| Uncontrolled Keywords: | 01 Mathematical Sciences, 06 Biological Sciences, 08 Information and Computing Sciences |
| Subjects: | Q Science > QA Mathematics Q Science > QP Physiology R Medicine > RM Therapeutics. Pharmacology |
| Divisions: | Applied Mathematics (merged with Comp Sci 10 Aug 20) |
| Publisher: | Elsevier |
| Related URLs: | |
| Date Deposited: | 26 Sep 2019 10:02 |
| Last Modified: | 04 Sep 2021 09:04 |
| DOI or ID number: | 10.1016/j.jtbi.2019.05.008 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/11132 |
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