Hubbard, ME, Jove, M, Loadman, PM et al. (3 more authors) (2017) Drug delivery in a tumour cord model: a computational simulation. Royal Society Open Science, 4 (5). 170014. ISSN 2054-5703
Abstract
The tumour vasculature and microenvironment is complex and heterogeneous, contributing to reduced delivery of cancer drugs to the tumour. We have developed an in silico model of drug transport in a tumour cord to explore the effect of different drug regimes over a 72 h period and how changes in pharmacokinetic parameters affect tumour exposure to the cytotoxic drug doxorubicin. We used the model to describe the radial and axial distribution of drug in the tumour cord as a function of changes in the transport rate across the cell membrane, blood vessel and intercellular permeability, flow rate, and the binding and unbinding ratio of drug within the cancer cells. We explored how changes in these parameters may affect cellular exposure to drug. The model demonstrates the extent to which distance from the supplying vessel influences drug levels and the effect of dosing schedule in relation to saturation of drug-binding sites. It also shows the likely impact on drug distribution of the aberrant vasculature seen within tumours. The model can be adapted for other drugs and extended to include other parameters. The analysis confirms that computational models can play a role in understanding novel cancer therapies to optimize drug administration and delivery.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. |
Keywords: | computational modelling, mathematical modelling, drug delivery, drug transport and binding, pharmacokinetic resistance |
Dates: |
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Institution: | The University of Leeds |
Depositing User: | Symplectic Publications |
Date Deposited: | 19 Jul 2017 08:48 |
Last Modified: | 19 Jul 2017 08:48 |
Status: | Published |
Publisher: | Royal Society |
Identification Number: | 10.1098/rsos.170014 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:119233 |