Tailoring mathematical models to stem-cell derived cardiomyocyte lines can improve predictions of drug-induced changes to their electrophysiology
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 find...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
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Frontiers Research Foundation
2017
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| Online Access: | https://eprints.nottingham.ac.uk/48668/ |
| _version_ | 1848797819502067712 |
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| author | 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 |
| author_facet | 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 |
| author_sort | Lei, Chon-Lok |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T20:09:56Z |
| format | Article |
| id | nottingham-48668 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:09:56Z |
| publishDate | 2017 |
| publisher | Frontiers Research Foundation |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-486682020-05-04T19:22:10Z https://eprints.nottingham.ac.uk/48668/ 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 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. Frontiers Research Foundation 2017-12-12 Article PeerReviewed 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. and Polonchuk, Liudmila (2017) Tailoring mathematical models to stem-cell derived cardiomyocyte lines can improve predictions of drug-induced changes to their electrophysiology. Frontiers in Physiology, 8 . 986/1-986/13. ISSN 1664-042X cardiomyocytes stem cell derived electrophysiology mathematical model pharmacology variability computational model https://www.frontiersin.org/articles/10.3389/fphys.2017.00986/full doi:10.3389/fphys.2017.00986 doi:10.3389/fphys.2017.00986 |
| spellingShingle | cardiomyocytes stem cell derived electrophysiology mathematical model pharmacology variability computational model 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 |
| title | Tailoring mathematical models to stem-cell derived cardiomyocyte lines can improve predictions of drug-induced changes to their electrophysiology |
| title_full | Tailoring mathematical models to stem-cell derived cardiomyocyte lines can improve predictions of drug-induced changes to their electrophysiology |
| title_fullStr | Tailoring mathematical models to stem-cell derived cardiomyocyte lines can improve predictions of drug-induced changes to their electrophysiology |
| title_full_unstemmed | Tailoring mathematical models to stem-cell derived cardiomyocyte lines can improve predictions of drug-induced changes to their electrophysiology |
| title_short | Tailoring mathematical models to stem-cell derived cardiomyocyte lines can improve predictions of drug-induced changes to their electrophysiology |
| title_sort | tailoring mathematical models to stem-cell derived cardiomyocyte lines can improve predictions of drug-induced changes to their electrophysiology |
| topic | cardiomyocytes stem cell derived electrophysiology mathematical model pharmacology variability computational model |
| url | https://eprints.nottingham.ac.uk/48668/ https://eprints.nottingham.ac.uk/48668/ https://eprints.nottingham.ac.uk/48668/ |