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

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.

Myokit: A simple interface to cardiac cellular electrophysiology

“…Please see also related communications in this issue by Muszkiewicz et al (2016) and Lee et al (2016).…”

Validation and models in computational biomedical sciences: Philosophy, science, engineering

“…Validation of computational models of biological processes does not occur through direct comparison with that which they attempt to model; rather the whole process of modelling is an iterative process of establishing what would count as criteria for comparison, or the grounds of comparability, that make validating experiments interpretable . The variability of biological systems presents a profound challenge to computational modelling in biomedical contexts, and our research team has proposed the methodology of an experimentally calibrated population of models approach to addressing it, with Carusi (2014) presenting a social and philosophical view of the epistemological aspects of this methodology, and Muskiewicz et al (2016) setting out the methodology in the context of cardiac electrophysiology.…”

Using Populations of Models to Navigate Big Data in Electrophysiology: Evaluation of Parameter Sensitivity of Action Potential Models

“…Recently, 'experimentally-calibrated populations of models' (ePoM) have been used as a means to study the role of variability in EP models [2]. These populations are constructed by varying the maximal conductances and currents which are normally parameters of the EP models; this allows to investigate variability, which is not possible if assuming that these peak conductances and currents have a fixed value.…”

“…Using these models researchers can study cellular action potentials, in-silico, without having to isolate individual myocytes for an invitro study; furthermore, these models can be used to simulate both physiology and pathology in action potential genesis and propagation. Although numerous advances have been made in the field, and computational EP models have become incredibly detailed, there remain open questions that need to be addressed, particularly on how to choose a model that best suits the study at hand, about the choice of parameters and evaluation of parameter sensitivities, validation against reliable experimental data and in taking into account the role of inter-subject variability when studying both physiology and pathology [1].Recently, 'experimentally-calibrated populations of models' (ePoM) have been used as a means to study the role of variability in EP models [2]. These populations are constructed by varying the maximal conductances and currents which are normally parameters of the EP models; this allows to investigate variability, which is not possible if assuming that these peak conductances and currents have a fixed value.…”