Towards Patient-Specific Computational Modeling of hiPS-Derived Cardiomyocyte Function and Drug Action

  • Ralf Frotscher
  • Manfred Staat


Human-induced pluripotent stem cell-derived cardiomyocytes (hiPS-CM) today are widely used for the investigation of normal electromechanical cardiac function, of cardiac medication and of mutations. Computational models are thus established that simulate the behavior of this kind of cells. This section first motivates the modeling of hiPS-CM and then presents and discusses several modeling approaches of microscopic and macroscopic constituents of human-induced pluripotent stem cell-derived and mature human cardiac tissue. The focus is led on the mapping of the computational results one can achieve with these models onto mature human cardiomyocyte models, the latter being the real matter of interest. Model adaptivity is the key feature that is discussed because it opens the way for modeling various biological effects like biological variability, medication, mutation and phenotypical expression. We compare the computational with experimental results with respect to normal cardiac function and with respect to inotropic and chronotropic drug effects. The section closes with a discussion on the status quo of the specificity of computational models and on what challenges have to be solved to reach patient-specificity.


  1. 1.
    Augustin, C. M., Neic, A., Liebmann, M., Prassl, A. J., Niederer, S. A., Haase, G., et al. (2016). Anatomically accurate high resolution modeling of human whole heart electromechanics: A strongly scalable algebraic multigrid solver method for nonlinear deformation. Journal of Computational Physics, 305, 622–646. Scholar
  2. 2.
    Bondarenko, V. E., Szigeti, G. P., Bett, G. C. L., Kim, S.-J., & Rasmusson, R. L. (2004). Computer model of action potential of mouse ventricular myocytes. American Journal of Physiology Heart and Circulatory Physiology, 287(3), H1378–H1403. Scholar
  3. 3.
    Clancy, C. E., & Rudy, Y. (1999). Linking a genetic defect to its cellular phenotype in a cardiac arrhythmia. Nature, 400(6744), 566–569. Scholar
  4. 4.
    Clancy, C. E., & Rudy, Y. (2002). Na+ channel mutation that causes both Brugada and long-QT syndrome phenotypes: A simulation study of mechanism. Circulation, 105(10), 1208–1213. Scholar
  5. 5.
    Clayton, R. H., Bernus, O., Cherry, E. M., Dierckx, H., Fenton, F. H., Mirabella, L., … Zhang, H. (2011). Models of cardiac tissue electrophysiology: Progress, challenges and open questions. Progress in Biophysics and Molecular Biology, 104(1–3), 22–48. Scholar
  6. 6.
    Davies, M. R., Wang, K., Mirams, G. R., Caruso, A., Noble, D., Walz, A., …, Polonchuk, L. (2016). Recent developments in using mechanistic cardiac modelling for drug safety evaluation. Drug Discovery Today, 21(6), 924–938. Scholar
  7. 7.
    Denning, C., Borgdorff, V., Crutchley, J., Firth, K. S. A., George, V., Kalra, S., … Young, L. E. (2016). Cardiomyocytes from human pluripotent stem cells: From laboratory curiosity to industrial biomedical platform. Biochimica et Biophysica Acta (BBA)—Molecular Cell Research, 1863(7), 1728–1748. Scholar
  8. 8.
    Fenton, F., & Cherry, E. (2008). Models of cardiac cell. Scholar
  9. 9.
    Frotscher, R., Koch, J.-P., Raatschen, H.-J., & Staat, M. (2014). Evaluation of a computational model for drug action on cardiac tissue. In E. Oñate J. Oliver & A. Huerta (Eds.), Proceedings 11th World Congress on Computational Mechanics (WCCM XI), 5th European Conference on Computational Mechanics (ECCM V), 6th European Conference on Computational Fluid Dynamics (ECFD VI) (pp. 1425–1436) Barcelona, Spain.
  10. 10.
    Frotscher, R., Koch, J.-P., & Staat, M. (2015). Computational investigation of drug action on human-induced stem cell-derived cardiomyocytes. Journal of Biomechanical Engineering, 137(7), 71002. Scholar
  11. 11.
    Frotscher, R., Muanghong, D., Dursun, G., Goßmann, M., Temiz-Artmann, A., & Staat, M. (2016). Sample-specific adaption of an improved electro-mechanical model of in vitro cardiac tissue. Journal of Biomechanics, 49(12), 2428–2435. Scholar
  12. 12.
    Frotscher, R., & Staat, M. (2015). Homogenization of a cardiac tissue construct. In P. Nithiarasu & E. Budyn (Eds.), Proceedings of the 4th International Conference on Computational and Mathematical Biomedical Engineering—CMBE2015, 29 June–1 July 2015, Cachan (Paris), France. Zeta Computational Resources Ltd., Swansea, UK (pp. 645–648).
  13. 13.
    Göktepe, S., & Kuhl, E. (2010). Electromechanics of the heart: A unified approach to the strongly coupled excitation-contraction problem. Computational Mechanics, 45(2–3), 227–243. Scholar
  14. 14.
    Goßmann, M., Frotscher, R., Linder, P., Neumann, S., Bayer, R., Epple, M., … Artmann, G. M. (2016). Mechano-pharmacological characterization of cardiomyocytes derived from human induced pluripotent stem cells. Cellular Physiology and Biochemistry, 38(3), 1182–1198. Scholar
  15. 15.
    Guo, L., Abrams, R. M. C., Babiarz, J. E., Cohen, J. D., Kameoka, S., Sanders, M. J., … Kolaja, K. L. (2011). Estimating the risk of drug-induced proarrhythmia using human induced pluripotent stem cell-derived cardiomyocytes. Toxicological Sciences : An Official Journal of the Society of Toxicology, 123(1), 281–289. Scholar
  16. 16.
    Harris, K., Aylott, M., Cui, Y., Louttit, J. B., McMahon, N. C., & Sridhar, A. (2013). Comparison of electrophysiological data from human-induced pluripotent stem cell-derived cardiomyocytes to functional preclinical safety assays. Toxicological Sciences, 134(2), 412–426. Scholar
  17. 17.
    Hartman, M. E., Dai, D.-F., & Laflamme, M. A. (2016). Human pluripotent stem cells: Prospects and challenges as a source of cardiomyocytes for in vitro modeling and cell-based cardiac repair. Advanced Drug Delivery Reviews, 96, 3–17. Scholar
  18. 18.
    Hodgkin, A. L., & Huxley, A. F. (1952). A quantitative description of membrane current and its application to conduction and excitation in nerve. The Journal of Physiology, 117(4), 500–544. Scholar
  19. 19.
    Keip, M.-A., Steinmann, P., & Schröder, J. (2014). Two-scale computational homogenization of electro-elasticity at finite strains. Computer Methods in Applied Mechanics and Engineering, 278, 62–79. Scholar
  20. 20.
    Land, S., Park-Holohan, S.-J., Smith, N. P., dos Remedios, C. G., Kentish, J. C., & Niederer, S. A. (2017). A model of cardiac contraction based on novel measurements of tension development in human cardiomyocytes. Journal of Molecular and Cellular Cardiology, 106, 68–83. Scholar
  21. 21.
    Linder, P., Trzewik, J., Rüffer, M., Artmann, G. M., Digel, I., Kurz, R., … Temiz Artmann, A. (2010). Contractile tension and beating rates of self-exciting monolayers and 3D-tissue constructs of neonatal rat cardiomyocytes. Medical & Biological Engineering & Computing, 48(1), 59–65. Scholar
  22. 22.
    Luo, C. H., & Rudy, Y. (1994). A dynamic model of the cardiac ventricular action potential. I. Simulations of ionic currents and concentration changes. Circulation Research, 74(6), 1071–1096. Scholar
  23. 23.
    McAllister, R. E., Noble, D., & Tsien, R. W. (1975). Reconstruction of the electrical activity of cardiac Purkinje fibres. The Journal of Physiology, 251(1), 1–59. Scholar
  24. 24.
    Mehta, A., Chung, Y. Y., Ng, A., Iskandar, F., Atan, S., Wei, H., … Shim, W. (2011). Pharmacological response of human cardiomyocytes derived from virus-free induced pluripotent stem cells. Cardiovascular Research, 91(4), 577–586. Scholar
  25. 25.
    Niederer, S. A., Hunter, P. J., & Smith, N. P. (2006). A quantitative analysis of cardiac myocyte relaxation: A simulation study. Biophysical Journal, 90(5), 1697–1722. Scholar
  26. 26.
    Niederer, S. A., & Smith, N. P. (2008). An improved numerical method for strong coupling of excitation and contraction models in the heart. Progress in Biophysics and Molecular Biology, 96(1–3), 90–111. Scholar
  27. 27.
    Sirenko, O., Crittenden, C., Callamaras, N., Hesley, J., Chen, Y.-W., Funes, C., … Cromwell, E. F. (2013). Multiparameter in vitro assessment of compound effects on cardiomyocyte physiology using iPSC cells. Journal of Biomolecular Screening, 18(1), 39–53. Scholar
  28. 28.
    Stewart, P., Aslanidi, O. V., Noble, D., Noble, P. J., Boyett, M. R., & Zhang, H. (2009). Mathematical models of the electrical action potential of Purkinje fibre cells. Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences, 367(1896), 2225–2255. Scholar
  29. 29.
    ten Tusscher, K. H. W. J., & Panfilov, A. V. (2006). Alternans and spiral breakup in a human ventricular tissue model. American Journal of Physiology Heart and Circulatory Physiology, 291(3), H1088–H1100. Scholar
  30. 30.
    Tveito, A., & Lines, G. T. (2016). Computing characterizations of drugs for ion channels and receptors using Markov models (Lecture Notes in Computational Science and Engineering Vol. 111). Cham: Springer International Publishing.
  31. 31.
    Yokoo, N., Baba, S., Kaichi, S., Niwa, A., Mima, T., Doi, H., … Heike, T. (2009). The effects of cardioactive drugs on cardiomyocytes derived from human induced pluripotent stem cells. Biochemical and Biophysical Research Communications, 387(3), 482–488. Scholar

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© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Biomechanics LaboratoryInstitute of Bioengineering, University of Applied Sciences AachenJülichGermany

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