Development, calibration, and validation of a novel human ventricular myocyte model in health, disease, and drug block
Abstract
Human-based modelling and simulations are becoming ubiquitous in biomedical science due to their ability to augment experimental and clinical investigations. Cardiac electrophysiology is one of the most advanced areas, with cardiac modelling and simulation being considered for virtual testing of pharmacological therapies and medical devices. Current models present inconsistencies with experimental data, which limit further progress. In this study, we present the design, development, calibration and independent validation of a human-based ventricular model (ToR-ORd) for simulations of electrophysiology and excitation-contraction coupling, from ionic to whole-organ dynamics, including the electrocardiogram. Validation based on substantial multiscale simulations supports the credibility of the ToR-ORd model under healthy and key disease conditions, as well as drug blockade. In addition, the process uncovers new theoretical insights into the biophysical properties of the L-type calcium current, which are critical for sodium and calcium dynamics. These insights enable the reformulation of L-type calcium current, as well as replacement of the hERG current model.
Data availability
No new experimental data were created. However, codes for simulations are available at https://github.com/jtmff/torord.
Article and author information
Author details
Funding
Wellcome (100246/Z/12/Z)
- Blanca Rodriguez
Amazon Web Services (Machine learning research award)
- Blanca Rodriguez
Wellcome (214290/Z/18/Z)
- Blanca Rodriguez
British Heart Foundation (FS/17/22/32644)
- Alfonso Bueno-Orovio
European Commission (675451)
- Blanca Rodriguez
National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC/P001076/1)
- Blanca Rodriguez
TransQST (116030)
- Blanca Rodriguez
BHF Centre of Research Excellence, Oxford (RE/13/1/30181)
- Blanca Rodriguez
UK National Supercomputing (Archer RAP award (322 00180))
- Blanca Rodriguez
UK National Supercomputing (PRACE (2017174226))
- Blanca Rodriguez
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2019, Tomek et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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