Journal article
Variability in cardiac electrophysiology: Using experimentally-calibrated populations of models to move beyond the single virtual physiological human paradigm.
- Muszkiewicz A Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom.
- Britton OJ Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom.
- Gemmell P Clyde Biosciences Ltd, West Medical Building, University of Glasgow, Glasgow G12 8QQ, United Kingdom.
- Passini E Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom.
- Sánchez C Center for Computational Medicine in Cardiology (CCMC), Institute of Computational Science, Università della Svizzera italiana, Lugano, Switzerland.
- Zhou X Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom.
- Carusi A Medical Humanities, University of Sheffield, United Kingdom.
- Quinn TA Department of Physiology and Biophysics, Dalhousie University, Halifax, Nova Scotia, Canada.
- Burrage K Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom; Mathematical Sciences, Queensland University of Technology, Queensland 4072, Australia; ACEMS, ARC Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology, Queensland 4072, Australia.
- Bueno-Orovio A Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom.
- Rodriguez B Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom. Electronic address: blanca.rodriguez@cs.ox.ac.uk.
- 2015-12-25
Published in:
- Progress in biophysics and molecular biology. - 2016
Action potential
Arrhythmias
Cardiac electrophysiology
In silico high-throughput screening
Physiological variability
Populations of models
Calibration
Electrophysiological Phenomena
Heart
Humans
Models, Cardiovascular
User-Computer Interface
English
Physiological variability manifests itself via differences in physiological function between individuals of the same species, and has crucial implications in disease progression and treatment. Despite its importance, physiological variability has traditionally been ignored in experimental and computational investigations due to averaging over samples from multiple individuals. Recently, modelling frameworks have been devised for studying mechanisms underlying physiological variability in cardiac electrophysiology and pro-arrhythmic risk under a variety of conditions and for several animal species as well as human. One such methodology exploits populations of cardiac cell models constrained with experimental data, or experimentally-calibrated populations of models. In this review, we outline the considerations behind constructing an experimentally-calibrated population of models and review the studies that have employed this approach to investigate variability in cardiac electrophysiology in physiological and pathological conditions, as well as under drug action. We also describe the methodology and compare it with alternative approaches for studying variability in cardiac electrophysiology, including cell-specific modelling approaches, sensitivity-analysis based methods, and populations-of-models frameworks that do not consider the experimental calibration step. We conclude with an outlook for the future, predicting the potential of new methodologies for patient-specific modelling extending beyond the single virtual physiological human paradigm.
- Language
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- English
- Open access status
- hybrid
- Identifiers
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- DOI 10.1016/j.pbiomolbio.2015.12.002
- PMID 26701222
- Persistent URL
- https://sonar.ch/global/documents/61655
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