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Tailoring mathematical models to stem-cell derived cardiomyocyte lines can improve predictions of drug-induced changes to their electrophysiology

Lei, Chon-Lok; Wang, Ken; Clerx, Michael; Johnstone, Ross H.; Hortigon-Vinagre, Maria P.; Zamora, Victor; Allan, Andrew; Smith, Godfrey L.; Gavaghan, David J.; Mirams, Gary R.; Polonchuk, Liudmila

Tailoring mathematical models to stem-cell derived cardiomyocyte lines can improve predictions of drug-induced changes to their electrophysiology Thumbnail


Authors

Chon-Lok Lei

Ken Wang

Michael Clerx

Ross H. Johnstone

Maria P. Hortigon-Vinagre

Victor Zamora

Andrew Allan

Godfrey L. Smith

David J. Gavaghan

Liudmila Polonchuk



Abstract

Human induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs) have applications in disease modeling, cell therapy, drug screening and personalized medicine. Computational models can be used to interpret experimental findings in iPSC-CMs, provide mechanistic insights, and translate these findings to adult cardiomyocyte (CM) electrophysiology. However, different cell lines display different expression of ion channels, pumps and receptors, and show differences in electrophysiology. In this exploratory study, we use a mathematical model based on iPSC-CMs from Cellular Dynamic International (CDI, iCell), and compare its predictions to novel experimental recordings made with the Axiogenesis Cor.4U line. We show that tailoring this model to the specific cell line, even using limited data and a relatively simple approach, leads to improved predictions of baseline behavior and response to drugs. This demonstrates the need and the feasibility to tailor models to individual cell lines, although a more refined approach will be needed to characterize individual currents, address differences in ion current kinetics, and further improve these results.

Citation

Lei, C.-L., Wang, K., Clerx, M., Johnstone, R. H., Hortigon-Vinagre, M. P., Zamora, V., …Polonchuk, L. (2017). Tailoring mathematical models to stem-cell derived cardiomyocyte lines can improve predictions of drug-induced changes to their electrophysiology. Frontiers in Physiology, 8, Article 986. https://doi.org/10.3389/fphys.2017.00986

Journal Article Type Article
Acceptance Date Nov 17, 2017
Publication Date Dec 12, 2017
Deposit Date Dec 12, 2017
Publicly Available Date Dec 12, 2017
Journal Frontiers in Physiology
Electronic ISSN 1664-042X
Publisher Frontiers Media
Peer Reviewed Peer Reviewed
Volume 8
Article Number 986
DOI https://doi.org/10.3389/fphys.2017.00986
Keywords cardiomyocytes, stem cell derived, electrophysiology, mathematical model, pharmacology, variability, computational model
Public URL https://nottingham-repository.worktribe.com/output/899515
Publisher URL https://www.frontiersin.org/articles/10.3389/fphys.2017.00986/full
Contract Date Dec 12, 2017

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