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Modelling rheumatoid arthritis : a hybrid modelling framework to describe pannus formation in a small joint

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Macfarlane_2022_Immunoinformatics_Modelling_RA_CC.pdf (6.030Mb)
Date
06/2022
Author
Macfarlane, Fiona R.
Chaplain, Mark A.J.
Eftimie, Raluca
Keywords
Rheumatoid arthritis
Hybrid model
Stochasticity
Immune response
QA75 Electronic computers. Computer science
QR180 Immunology
DAS
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Abstract
Rheumatoid arthritis (RA) is a chronic inflammatory disorder that causes pain, swelling and stiffness in the joints, and negatively impacts the life of affected patients. The disease does not have a cure yet, as there are still many aspects of this complex disorder that are not fully understood. While mathematical models can shed light on some of these aspects, to date there are few such models that can be used to better understand the disease. As a first step in the mechanistic understanding of RA, in this study we introduce a new hybrid mathematical modelling framework that describes pannus formation in a small proximal interphalangeal (PIP) joint. We perform numerical simulations with this new model, to investigate the impact of different levels of immune cells (macrophages and fibroblasts) on the degradation of bone and cartilage. Since many model parameters are unknown and cannot be estimated due to a lack of experiments, we also perform a sensitivity analysis of model outputs to various model parameters (single parameters or combinations of parameters). Finally, we discuss how our model could be applied to investigate current treatments for RA, for example, methotrexate, TNF-inhibitors or tocilizumab, which can impact different model parameters.
Citation
Macfarlane , F R , Chaplain , M A J & Eftimie , R 2022 , ' Modelling rheumatoid arthritis : a hybrid modelling framework to describe pannus formation in a small joint ' , ImmunoInformatics , vol. 6 , 100014 . https://doi.org/10.1016/j.immuno.2022.100014
Publication
ImmunoInformatics
Status
Peer reviewed
DOI
https://doi.org/10.1016/j.immuno.2022.100014
ISSN
2667-1190
Type
Journal article
Rights
Copyright © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Collections
  • University of St Andrews Research
URI
http://hdl.handle.net/10023/25378

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