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Variability in cardiac electrophysiology: Using experimentally-calibrated populations of models to move beyond the single virtual physiological human paradigm

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Variability in cardiac electrophysiology: Using experimentally-calibrated populations of models to move beyond the single virtual physiological human paradigm

Content Provider	PubMed Central
Author	Anna, Muszkiewicz Britton, Oliver J. Gemmell, Philip Passini, Elisa Carlos, SÃ¡nchez Zhou, Xin Carusi, Annamaria Quinn, T. Alexander Burrage, Kevin Alfonso, Bueno-orovio Rodriguez, Blanca
Copyright Year	2015
Abstract	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.
Related Links	http://dx.doi.org/10.1016/j.pbiomolbio.2015.12.002
Ending Page	127
Page Count	13
Starting Page	115
File Format	PDF
ISSN	00796107
e-ISSN	18731732
Journal	Progress in Biophysics and Molecular Biology
Issue Number	1-3
Volume Number	120
Language	English
Publisher	Pergamon Press
Publisher Date	2016-01-01
Access Restriction	Open
Rights Holder	Pergamon Press
Subject Keyword	Biophysics Molecular Biology Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Molecular Biology Biophysics

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