Imperial College London
Alternate

Dr Chris Cantwell

Faculty of Engineering, Department of Aeronautics

Senior Lecturer in Aeronautics
 
 
 
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Contact

 

+44 (0)20 7594 5050c.cantwell Website

 
 
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Location

 

Department of Aeronautics, Room 219City and Guilds BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Houston:2020:10.1098/rsta.2019.0339,
author = {Houston, C and Marchand, B and Engelbert, L and Cantwell, CD},
doi = {10.1098/rsta.2019.0339},
journal = {Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences},
pages = {1--17},
title = {Reducing complexity and unidentifiability when modelling human atrial cells},
url = {http://dx.doi.org/10.1098/rsta.2019.0339},
volume = {378},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Mathematical models of a cellular action potential in cardiac modelling have become increasingly complex, particularly in gating kinetics which control the opening and closing of individual ion channel currents. As cardiac models advance towards use in personalised medicine to inform clinical decision-making, it is critical to understand the uncertainty hidden in parameter estimates from their calibration to experimental data. This study applies approximate Bayesian computation to re-calibrate the gating kinetics of four ion channels in two existing human atrial cell models to their original datasets, providing a measure of uncertainty and indication of potential issues with selecting a single unique value given the available experimental data. Two approaches are investigated to reduce the uncertainty present: re-calibrating the models to a more complete dataset and using a less complex formulation with fewer parameters to constrain. The re-calibrated models are inserted back into the full cell model to study the overall effect on the action potential. The use of more complete datasets does not eliminate uncertainty present in parameter estimates. The less complex model, particularly for the fast sodium current, gave a better fit to experimental data alongside lower parameter uncertainty and improved computational speed.
AU  - Houston,C
AU  - Marchand,B
AU  - Engelbert,L
AU  - Cantwell,CD
DO  - 10.1098/rsta.2019.0339
EP  - 17
PY  - 2020///
SN  - 1364-503X
SP  - 1
TI  - Reducing complexity and unidentifiability when modelling human atrial cells
T2  - Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
UR  - http://dx.doi.org/10.1098/rsta.2019.0339
UR  - http://arxiv.org/abs/2001.10954v1
UR  - https://royalsocietypublishing.org/doi/10.1098/rsta.2019.0339
UR  - http://hdl.handle.net/10044/1/77239
VL  - 378
ER  -
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