A computational model of induced pluripotent stem‐cell derived cardiomyocytes incorporating experimental variability from multiple data sources

Abstract

Induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) capture patient-specific genotype-phenotype relationships, as well as cell-to-cell variability of cardiac electrical activity r Computational modelling and simulation provide a high throughput approach to reconcile multiple datasets describing physiological variability, and also identify vulnerable parameter regimes r We have developed a whole-cell model of iPSC-CMs, composed of single exponential voltage-dependent gating variable rate constants, parameterized to fit experimental iPSC-CM outputs r We have utilized experimental data across multiple laboratories to model experimental variability and investigate subcellular phenotypic mechanisms in iPSC-CMs r This framework links molecular mechanisms to cellular-level outputs by revealing unique subsets of model parameters linked to known iPSC-CM phenotypes Abstract There is a profound need to develop a strategy for predicting patient-to-patient vulnerability in the emergence of cardiac arrhythmia. A promising in vitro method to address patient-specific proclivity to cardiac disease utilizes induced pluripotent stem cell-derived Divya Kernik is currently a PhD candidate in Biomedical Engineering at the University of California, Davis. She obtained a BS in Biomedical Engineering from Johns Hopkins University. The focus of her PhD work has been the development of computational methods that help to understand human-derived cardiac cells, as reported in the present study. In the future, she aims to continue to use computational modelling to address questions in cardiac physiology and pharmacology, with the underlying goal of incorporating human diversity throughout these efforts.

To their own beat: modelling variability in induced pluripotent stem cell‐derived cardiomyocytes

“…When the physiological behaviours of these six populations were analysed, correlations between variability in a single current and particular whole‐cell behaviours became clear (Kernik et al . , Fig. 13).…”

“…Simulating the reaction to specific ion channel targeting drugs and comparing the output to experimental data validated the responses seen in the model populations, and further illustrated the large variability of iPSC‐CM drug responses (Kernik et al . , Fig. 14).…”

“…Following this refinement, the baseline model produces characteristic iPSC‐CM action potentials and calcium handling within the range of experimental observations (Kernik et al . , Figs 10–11). This simple and effective method to derive a model from multiple datasets is easily generalizable and can be extended when more data become available.…”

“…The most recent advance has come in an article in The Journal of Physiology by Kernik et al . () who built a thoroughly informed model using an array of data sources. In a groundbreaking step forward, this model comprehensively captures the variability inherent in iPSC‐CMs.…”

“…For each current, two to five different datasets were considered (Kernik et al . , Table 1) and the final parameter value was established as the average of the corresponding parameters determined from each dataset‐specific optimization.…”