1. Cell Biology
  2. Computational and Systems Biology
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Development, calibration, and validation of a novel human ventricular myocyte model in health, disease, and drug block

  1. Jakub Tomek  Is a corresponding author
  2. Alfonso Bueno-Orovio
  3. Elisa Passini
  4. Xin Zhou
  5. Ana Minchole
  6. Oliver Britton
  7. Chiara Bartolucci
  8. Stefano Severi
  9. Alvin Shrier
  10. Laszlo Virag
  11. Andras Varro
  12. Blanca Rodriguez  Is a corresponding author
  1. University of Oxford, United Kingdom
  2. University of Bologna, Italy
  3. McGill University, Canada
  4. University of Szeged, Hungary
Research Article
  • Cited 33
  • Views 3,289
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Cite this article as: eLife 2019;8:e48890 doi: 10.7554/eLife.48890

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

  1. Jakub Tomek

    Department of Computer Science, University of Oxford, Oxford, United Kingdom
    For correspondence
    jakub.tomek@dpag.ox.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0157-4386
  2. Alfonso Bueno-Orovio

    Department of Computer Science, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Elisa Passini

    Department of Computer Science, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Xin Zhou

    Department of Computer Science, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  5. Ana Minchole

    Department of Computer Science, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  6. Oliver Britton

    Department of Computer Science, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  7. Chiara Bartolucci

    Department of Electrical, Electronic, and Information Engineering 'Guglielmo Marconi', University of Bologna, Bologna, Italy
    Competing interests
    The authors declare that no competing interests exist.
  8. Stefano Severi

    Department of Electrical, Electronic, and Information Engineering 'Guglielmo Marconi', University of Bologna, Bologna, Italy
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4306-8294
  9. Alvin Shrier

    Department of Physiology, McGill University, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
  10. Laszlo Virag

    Department of Pharmacology and Pharmacotherapy, University of Szeged, Szeged, Hungary
    Competing interests
    The authors declare that no competing interests exist.
  11. Andras Varro

    Department of Pharmacology and Pharmacotherapy, University of Szeged, Szeged, Hungary
    Competing interests
    The authors declare that no competing interests exist.
  12. Blanca Rodriguez

    Department of Computer Science, University of Oxford, Oxford, United Kingdom
    For correspondence
    Blanca.Rodriguez@cs.ox.ac.uk
    Competing interests
    The authors declare that no competing interests exist.

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.

Reviewing Editor

  1. José D Faraldo-Gómez, National Heart, Lung and Blood Institute, National Institutes of Health, United States

Publication history

  1. Received: May 29, 2019
  2. Accepted: December 18, 2019
  3. Accepted Manuscript published: December 23, 2019 (version 1)
  4. Accepted Manuscript updated: December 24, 2019 (version 2)
  5. Version of Record published: January 20, 2020 (version 3)
  6. Version of Record updated: May 13, 2020 (version 4)

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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