Abstract
Distinct electrophysiological phenotypes are exhibited by biological cells that have differentiated into particular cell types. The usual approach when simulating the cardiac electrophysiology of tissue that includes different cell types is to model the different cell types as occupying spatially distinct yet coupled regions. Instead, we model the electrophysiology of well-mixed cells by using homogenisation to derive an extension to the commonly used monodomain or bidomain equations. These new equations permit spatial variations in the distribution of the different subtypes of cells and will reduce the computational demands of solving the governing equations. We validate the homogenisation computationally, and then use the new model to explain some experimental observations from stem cell-derived cardiomyocyte monolayers.
Highlights
Since its inception in the 1960s, the field of computational cardiac electrophysiology has contributed to many advances in understanding the links between the flow of ions, transmembrane potential and electromechanical activity of the heart under control, pathological and drug-influenced conditions
We develop methods for simulating a system that is of particular interest for safety pharmacology—monolayers of human stem cell-derived cardiomyocytes
We use the layout of phenotypes shown in the top panel of Fig. 3 with four different combinations of the cellular electrophysiology models described in Sect. 3.2, given by:
Summary
Since its inception in the 1960s, the field of computational cardiac electrophysiology has contributed to many advances in understanding the links between the flow of ions, transmembrane potential and electromechanical activity of the heart under control, pathological and drug-influenced conditions. We develop methods for simulating a system that is of particular interest for safety pharmacology—monolayers of human stem cell-derived cardiomyocytes (hSC-CMs). The Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative has proposed a series of complementary cardiac safety assays to improve upon the current methods of assessing the arrhythmic risk associated with novel pharmaceutical compounds (Sager et al 2014; Gintant et al 2016). We propose simulation as a method by which the impact of variation in cell type on the cardiac safety assessment process may be investigated. We compare two methods of simulating a system that contains variable cellular populations, with our primary focus on a future application to simulation of multi-cellular hSC-CM cultures
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