%0 Journal Article %1 Lei2017 %A Lei, Chon Lok %A Wang, Ken %A Clerx, Michael %A Johnstone, Ross H. %A Hortigon-Vinagre, Maria P. %A Zamora, Victor %A Allan, Andrew %A Smith, Godfrey L. %A Gavaghan, David J. %A Mirams, Gary R. %A Polonchuk, Liudmila %D 2017 %J Frontiers in Physiology %K Cardiomyocytes Computational_model Electrophysiology Mathematical_model Pharmacology Stem_cell_derived Variability %R 10.3389/fphys.2017.00986 %T Tailoring mathematical models to stem-cell derived cardiomyocyte lines can improve predictions of drug-induced changes to their electrophysiology %X 3 Human induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs) have applications 4 in disease modelling, cell therapy, drug screening and personalised medicine. Computational 5 models can be used to interpret experimental findings in iPSC-CMs, provide mechanistic insights, 6 and translate these findings to adult cardiomyocyte (CM) electrophysiology. However, different 7 cell lines display different expression of ion channels, pumps and receptors, and show differences 8 in electrophysiology. In this exploratory study, we use a mathematical model based on iPSC 9 CMs from Cellular Dynamic International (CDI, iCell), and compare its predictions to novel 10 experimental recordings made with the Axiogenesis Cor.4U line. We show that tailoring this 11 model to the specific cell line, even using limited data and a relatively simple approach, leads to 12 improved predictions of baseline behaviour and response to drugs. This demonstrates the need 13 and the feasibility to tailor models to individual cell lines, although a more refined approach will 14 be needed to characterise individual currents, address differences in ion current kinetics, and 15 further improve these results.

@article{Lei2017, abstract = {3 Human induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs) have applications 4 in disease modelling, cell therapy, drug screening and personalised medicine. Computational 5 models can be used to interpret experimental findings in iPSC-CMs, provide mechanistic insights, 6 and translate these findings to adult cardiomyocyte (CM) electrophysiology. However, different 7 cell lines display different expression of ion channels, pumps and receptors, and show differences 8 in electrophysiology. In this exploratory study, we use a mathematical model based on iPSC 9 CMs from Cellular Dynamic International (CDI, iCell), and compare its predictions to novel 10 experimental recordings made with the Axiogenesis Cor.4U line. We show that tailoring this 11 model to the specific cell line, even using limited data and a relatively simple approach, leads to 12 improved predictions of baseline behaviour and response to drugs. This demonstrates the need 13 and the feasibility to tailor models to individual cell lines, although a more refined approach will 14 be needed to characterise individual currents, address differences in ion current kinetics, and 15 further improve these results.}, added-at = {2019-06-17T23:34:05.000+0200}, author = {Lei, Chon Lok and Wang, Ken and Clerx, Michael and Johnstone, Ross H. and Hortigon-Vinagre, Maria P. and Zamora, Victor and Allan, Andrew and Smith, Godfrey L. and Gavaghan, David J. and Mirams, Gary R. and Polonchuk, Liudmila}, biburl = {https://www.bibsonomy.org/bibtex/27cea8affe5f70ed2146b9a626fbd617b/fcdi}, doi = {10.3389/fphys.2017.00986}, interhash = {52607142c60011758cb22b170465774b}, intrahash = {7cea8affe5f70ed2146b9a626fbd617b}, issn = {1664042X}, journal = {Frontiers in Physiology}, keywords = {Cardiomyocytes Computational_model Electrophysiology Mathematical_model Pharmacology Stem_cell_derived Variability}, timestamp = {2019-06-18T22:58:44.000+0200}, title = {{Tailoring mathematical models to stem-cell derived cardiomyocyte lines can improve predictions of drug-induced changes to their electrophysiology}}, year = 2017 }