Phenotypic Screening of iPSC-Derived Cardiomyocytes for Cardiotoxicity Testing and Therapeutic Target Discovery

  • Arne A. N. Bruyneel
  • Tyler Muser
  • Vaidya Parthasarathy
  • Dries Feyen
  • Mark MercolaEmail author


The remarkable ability to generate unlimited numbers of cardiomyocytes and other differentiated cell types, from any person, and to edit the genome to introduce or correct disease-causing mutations, creates unprecedented opportunities for drug discovery. The new technologies have the potential to revolutionize the drug development pipeline, from delineating disease mechanisms and discovery of therapeutic targets to library screening and validation of therapeutic strategies. Moreover, since in vitro phenotypes reflect patient genetics and might predict outcomes, patient induced pluripotent stem cell (iPSCs) might eventually contribute to patient selection for clinical trials and inform individual patient treatment. This chapter focuses on the application of iPSC-derived cardiomyocytes in large-scale applications relevant to discovery of disease mechanisms and therapeutic targets for heart disease and for assessing the cardiomyopathic and proarrhythmic risk of drugs. We review the current status of large-scale screening of iPSC-derived cardiomyocyte disease models and explore new advances in cell culture, three-dimensional engineered tissues, and instrumentation that might address current weaknesses in the iPSC-cardiomyocyte technology. Our philosophy is that advancing iPSC-derived cardiomyocyte models that faithfully recapitulate disease and enable large-scale chemical or functional genomics screening could shift the paradigm of drug discovery by introducing human disease phenotype into the early stages of the development process, with the potential for increasing the safety and efficacy of new medicines.


iPSC Cardiomyocyte Phenotypic screening Drug discovery Disease modeling Cardiotoxicity 



We gratefully acknowledge support from the National Institutes of Health (NIH) (R01HL130840. R01HL128072 and R21HL141019 to MM). TM acknowledges support from AHA (Undergraduate Summer Research Program). DAMF is funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 708459.

Conflict of Interest Statement

The authors have no conflicting interests.


  1. 1.
    Harrison RK. Phase II and phase III failures: 2013-2015. Nat Rev Drug Discov. 2016;15(12):817–8.PubMedCrossRefPubMedCentralGoogle Scholar
  2. 2.
    Wong CH, et al. Estimation of clinical trial success rates and related parameters. Biostatistics. 2018; Scholar
  3. 3.
    Fordyce CB, et al. Cardiovascular drug development: is it dead or just hibernating? J Am Coll Cardiol. 2015;65(15):1567–82.PubMedCrossRefGoogle Scholar
  4. 4.
    MacDonald JS, et al. Toxicity testing in the 21st century: a view from the pharmaceutical industry. Toxicol Sci. 2009;110(1):40–6.PubMedCrossRefGoogle Scholar
  5. 5.
    Waring MJ, et al. An analysis of the attrition of drug candidates from four major pharmaceutical companies. Nat Rev Drug Discov. 2015;14(7):475–86.PubMedCrossRefGoogle Scholar
  6. 6.
    Takahashi K, et al. Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell. 2006;126(4):663–76.CrossRefGoogle Scholar
  7. 7.
    Lian X, et al. Directed cardiomyocyte differentiation from human pluripotent stem cells by modulating Wnt/β-catenin signaling under fully defined conditions. Nat Protoc. 2013;8(1):162–75.PubMedCrossRefGoogle Scholar
  8. 8.
    Burridge PW, et al. Chemically defined generation of human cardiomyocytes. Nat Methods. 2014;11(8):855–60.PubMedPubMedCentralCrossRefGoogle Scholar
  9. 9.
    McKeithan WL, et al. An automated platform for assessment of congenital and drug-induced arrhythmia with hiPSC-derived cardiomyocytes. Front Physiol. 2017;8:766.PubMedPubMedCentralCrossRefGoogle Scholar
  10. 10.
    Bedut S, et al. High-throughput drug profiling with voltage- and calcium-sensitive fluorescent probes in human iPSC-derived cardiomyocytes. Am J Physiol Heart Circ Physiol. 2016;311(1):H44–53.PubMedCrossRefPubMedCentralGoogle Scholar
  11. 11.
    Kolanowski TJ, et al. Making human cardiomyocytes up to date: Derivation, maturation state and perspectives. Int J Cardiol. 2017;241:379–86.PubMedCrossRefPubMedCentralGoogle Scholar
  12. 12.
    Yang X, et al. Engineering adolescence: maturation of human pluripotent stem cell-derived cardiomyocytes. Circ Res. 2014;114(3):511–23.PubMedPubMedCentralCrossRefGoogle Scholar
  13. 13.
    Koivumäki JT, et al. Structural immaturity of human iPSC-derived cardiomyocytes. Front Physiol. 2018;9:80.PubMedPubMedCentralCrossRefGoogle Scholar
  14. 14.
    Kane C, et al. Excitation-contraction coupling of human induced pluripotent stem cell-derived cardiomyocytes. Front Cell Dev Biol. 2015;3:59.PubMedPubMedCentralCrossRefGoogle Scholar
  15. 15.
    Dai DF, et al. Mitochondrial maturation in human pluripotent stem cell derived cardiomyocytes. Stem Cells Int. 2017;2017:5153625.PubMedPubMedCentralCrossRefGoogle Scholar
  16. 16.
    Malandraki-Miller S, et al. Changing metabolism in differentiating cardiac progenitor cells-can stem cells become metabolically flexible cardiomyocytes? Front Cardiovasc Med. 2018;5:119.PubMedPubMedCentralCrossRefGoogle Scholar
  17. 17.
    Knollmann BC. Induced pluripotent stem cell-derived cardiomyocytes: boutique science or valuable arrhythmia model? Circ Res. 2013;112(6):969–76. discussion 976PubMedPubMedCentralCrossRefGoogle Scholar
  18. 18.
    Keung W, et al. Developmental cues for the maturation of metabolic, electrophysiological and calcium handling properties of human pluripotent stem cell-derived cardiomyocytes. Stem Cell Res Ther. 2014;5(1):17.PubMedPubMedCentralCrossRefGoogle Scholar
  19. 19.
    Del Alamo JC, et al. High throughput physiological screening of iPSC-derived cardiomyocytes for drug development. Biochim Biophys Acta. 2016;1863(7 Pt B):1717–27.PubMedPubMedCentralCrossRefGoogle Scholar
  20. 20.
    Kim C, et al. Non-cardiomyocytes influence the electrophysiological maturation of human embryonic stem cell-derived cardiomyocytes during differentiation. Stem Cells Dev. 2010;19(6):783–95.PubMedCrossRefGoogle Scholar
  21. 21.
    Ma J, et al. High purity human-induced pluripotent stem cell-derived cardiomyocytes: electrophysiological properties of action potentials and ionic currents. Am J Physiol Heart Circ Physiol. 2011;301(5):H2006–17.PubMedPubMedCentralCrossRefGoogle Scholar
  22. 22.
    Pekkanen-Mattila M, et al. The effect of human and mouse fibroblast feeder cells on cardiac differentiation of human pluripotent stem cells. Stem Cells Int. 2012;2012:875059.PubMedPubMedCentralCrossRefGoogle Scholar
  23. 23.
    Zhang Q, et al. Direct differentiation of atrial and ventricular myocytes from human embryonic stem cells by alternating retinoid signals. Cell Res. 2011;21(4):579–87.PubMedCrossRefPubMedCentralGoogle Scholar
  24. 24.
    Lundy SD, et al. Structural and functional maturation of cardiomyocytes derived from human pluripotent stem cells. Stem Cells Dev. 2013;22(14):1991–2002.PubMedPubMedCentralCrossRefGoogle Scholar
  25. 25.
    Ibrahim M, et al. The structure and function of cardiac t-tubules in health and disease. Proc Biol Sci. 2011;278(1719):2714–23.PubMedPubMedCentralCrossRefGoogle Scholar
  26. 26.
    Dolnikov K, et al. Functional properties of human embryonic stem cell-derived cardiomyocytes: intracellular Ca2+ handling and the role of sarcoplasmic reticulum in the contraction. Stem Cells. 2006;24(2):236–45.PubMedCrossRefPubMedCentralGoogle Scholar
  27. 27.
    Poon E, et al. Human pluripotent stem cell-based approaches for myocardial repair: from the electrophysiological perspective. Mol Pharm. 2011;8(5):1495–504.PubMedPubMedCentralCrossRefGoogle Scholar
  28. 28.
    Nikolaev VO, et al. Cyclic AMP imaging in adult cardiac myocytes reveals far-reaching beta1-adrenergic but locally confined beta2-adrenergic receptor-mediated signaling. Circ Res. 2006;99(10):1084–91.PubMedCrossRefPubMedCentralGoogle Scholar
  29. 29.
    Perry SJ, et al. Targeting of cyclic AMP degradation to beta 2-adrenergic receptors by beta-arrestins. Science. 2002;298(5594):834–6.PubMedCrossRefPubMedCentralGoogle Scholar
  30. 30.
    Jung G, et al. Time-dependent evolution of functional vs. remodeling signaling in iPSC-derived cardiomyocytes and induced maturation with biomechanical stimulation. FASEB J. 2016;30(4):1464–79.PubMedCrossRefGoogle Scholar
  31. 31.
    Lyon AR, et al. Loss of T-tubules and other changes to surface topography in ventricular myocytes from failing human and rat heart. Proc Natl Acad Sci U S A. 2009;106(16):6854–9.PubMedPubMedCentralCrossRefGoogle Scholar
  32. 32.
    Nikolaev VO, et al. Beta2-adrenergic receptor redistribution in heart failure changes cAMP compartmentation. Science. 2010;327(5973):1653–7.PubMedCrossRefPubMedCentralGoogle Scholar
  33. 33.
    Kaumann A, et al. Activation of beta2-adrenergic receptors hastens relaxation and mediates phosphorylation of phospholamban, troponin I, and C-protein in ventricular myocardium from patients with terminal heart failure. Circulation. 1999;99(1):65–72.PubMedCrossRefGoogle Scholar
  34. 34.
    Lefkowitz RJ. G protein-coupled receptors. III. New roles for receptor kinases and beta-arrestins in receptor signaling and desensitization. J Biol Chem. 1998;273(30):18677–80.PubMedCrossRefPubMedCentralGoogle Scholar
  35. 35.
    Rapacciuolo A, et al. Protein kinase A and G protein-coupled receptor kinase phosphorylation mediates beta-1 adrenergic receptor endocytosis through different pathways. J Biol Chem. 2003;278(37):35403–11.PubMedCrossRefGoogle Scholar
  36. 36.
    Yang X, et al. Tri-iodo-l-thyronine promotes the maturation of human cardiomyocytes-derived from induced pluripotent stem cells. J Mol Cell Cardiol. 2014;72:296–304.PubMedPubMedCentralCrossRefGoogle Scholar
  37. 37.
    Parikh SS, et al. Thyroid and glucocorticoid hormones promote functional T-tubule development in human-induced pluripotent stem cell-derived cardiomyocytes. Circ Res. 2017;121(12):1323–30.PubMedPubMedCentralCrossRefGoogle Scholar
  38. 38.
    Hu D, et al. Metabolic maturation of human pluripotent stem cell-derived cardiomyocytes by inhibition of HIF1α and LDHA. Circ Res. 2018;123(9):1066–79.PubMedCrossRefPubMedCentralGoogle Scholar
  39. 39.
    Ribeiro AJ, et al. Contractility of single cardiomyocytes differentiated from pluripotent stem cells depends on physiological shape and substrate stiffness. Proc Natl Acad Sci U S A. 2015;112(41):12705–10.PubMedPubMedCentralCrossRefGoogle Scholar
  40. 40.
    Jung G, et al. Time-dependent evolution of functional vs. remodeling signaling in induced pluripotent stem cell-derived cardiomyocytes and induced maturation with biomechanical stimulation. FASEB J. 2016;30(4):1464–79.PubMedCrossRefGoogle Scholar
  41. 41.
    McBeath R, et al. Cell shape, cytoskeletal tension, and RhoA regulate stem cell lineage commitment. Dev Cell. 2004;6(4):483–95.PubMedCrossRefGoogle Scholar
  42. 42.
    Lutolf MP, et al. Synthetic biomaterials as instructive extracellular microenvironments for morphogenesis in tissue engineering. Nat Biotechnol. 2005;23(1):47–55.PubMedCrossRefGoogle Scholar
  43. 43.
    Young JL, et al. Hydrogels with time-dependent material properties enhance cardiomyocyte differentiation in vitro. Biomaterials. 2011;32(4):1002–9.PubMedCrossRefGoogle Scholar
  44. 44.
    Jacot JG, et al. Mechanobiology of cardiomyocyte development. J Biomech. 2010;43(1):93–8.PubMedCrossRefGoogle Scholar
  45. 45.
    Young JL, et al. Mechanosensitive kinases regulate stiffness-induced cardiomyocyte maturation. Sci Rep. 2014;4:6425.PubMedPubMedCentralCrossRefGoogle Scholar
  46. 46.
    Ravi M, et al. 3D cell culture systems: advantages and applications. J Cell Physiol. 2015;230(1):16–26.PubMedCrossRefGoogle Scholar
  47. 47.
    Lemoine MD, et al. Human iPSC-derived cardiomyocytes cultured in 3D engineered heart tissue show physiological upstroke velocity and sodium current density. Sci Rep. 2017;7(1):5464.PubMedPubMedCentralCrossRefGoogle Scholar
  48. 48.
    Fink C, et al. Chronic stretch of engineered heart tissue induces hypertrophy and functional improvement. FASEB J. 2000;14(5):669–79.PubMedCrossRefGoogle Scholar
  49. 49.
    Mathur A, et al. Human iPSC-based cardiac microphysiological system for drug screening applications. Sci Rep. 2015;5:8883.PubMedPubMedCentralCrossRefGoogle Scholar
  50. 50.
    Langhans SA. Three-dimensional in vitro cell culture models in drug discovery and drug repositioning. Front Pharmacol. 2018;9:6.PubMedPubMedCentralCrossRefGoogle Scholar
  51. 51.
    Ulmer BM, et al. Contractile work contributes to maturation of energy metabolism in hiPSC-derived cardiomyocytes. Stem Cell Reports. 2018;10(3):834–47.PubMedPubMedCentralCrossRefGoogle Scholar
  52. 52.
    Ronaldson-Bouchard K, et al. Advanced maturation of human cardiac tissue grown from pluripotent stem cells. Nature. 2018;556(7700):239–43.PubMedPubMedCentralCrossRefGoogle Scholar
  53. 53.
    Hirt MN, et al. Increased afterload induces pathological cardiac hypertrophy: a new in vitro model. Basic Res Cardiol. 2012;107(6):307.PubMedPubMedCentralCrossRefGoogle Scholar
  54. 54.
    Stevens KR, et al. Physiological function and transplantation of scaffold-free and vascularized human cardiac muscle tissue. Proc Natl Acad Sci U S A. 2009;106(39):16568–73.PubMedPubMedCentralCrossRefGoogle Scholar
  55. 55.
    Naito H, et al. Optimizing engineered heart tissue for therapeutic applications as surrogate heart muscle. Circulation. 2006;114(1 Suppl):I72–8.PubMedGoogle Scholar
  56. 56.
    Tulloch NL, et al. Growth of engineered human myocardium with mechanical loading and vascular coculture. Circ Res. 2011;109(1):47–59.PubMedPubMedCentralCrossRefGoogle Scholar
  57. 57.
    Giacomelli E, et al. Three-dimensional cardiac microtissues composed of cardiomyocytes and endothelial cells co-differentiated from human pluripotent stem cells. Development. 2017;144(6):1008–17.PubMedPubMedCentralCrossRefGoogle Scholar
  58. 58.
    Lemme M, et al. Atrial-like engineered heart tissue: an in vitro model of the human atrium. Stem Cell Reports. 2018;11:1378.PubMedPubMedCentralCrossRefGoogle Scholar
  59. 59.
    Mannhardt I, et al. Human engineered heart tissue: analysis of contractile force. Stem Cell Reports. 2016;7(1):29–42.PubMedPubMedCentralCrossRefGoogle Scholar
  60. 60.
    Bielawski KS, et al. Real-time force and frequency analysis of engineered human heart tissue derived from induced pluripotent stem cells using magnetic sensing. Tissue Eng Part C Methods. 2016;22(10):932–40.PubMedPubMedCentralCrossRefGoogle Scholar
  61. 61.
    Thavandiran N, et al. Design and formulation of functional pluripotent stem cell-derived cardiac microtissues. Proc Natl Acad Sci U S A. 2013;110(49):E4698–707.PubMedPubMedCentralCrossRefGoogle Scholar
  62. 62.
    Moretti A, et al. Patient-specific induced pluripotent stem-cell models for long-QT syndrome. N Engl J Med. 2010;363(15):1397–409.PubMedCrossRefGoogle Scholar
  63. 63.
    Itzhaki I, et al. Modeling of catecholaminergic polymorphic ventricular tachycardia with patient-specific human-induced pluripotent stem cells. J Am Coll Cardiol. 2012;60(11):990–1000.PubMedCrossRefGoogle Scholar
  64. 64.
    Liang P, et al. Patient-specific and genome-edited induced pluripotent stem cell-derived cardiomyocytes elucidate single-cell phenotype of Brugada syndrome. J Am Coll Cardiol. 2016;68(19):2086–96.PubMedPubMedCentralCrossRefGoogle Scholar
  65. 65.
    Karakikes I, et al. Human-induced pluripotent stem cell models of inherited cardiomyopathies. Curr Opin Cardiol. 2014;29(3):214–9.PubMedPubMedCentralCrossRefGoogle Scholar
  66. 66.
    Birket MJ, et al. Contractile defect caused by mutation in MYBPC3 revealed under conditions optimized for human PSC-cardiomyocyte function. Cell Rep. 2015;13(4):733–45.PubMedPubMedCentralCrossRefGoogle Scholar
  67. 67.
    Lan F, et al. Abnormal calcium handling properties underlie familial hypertrophic cardiomyopathy pathology in patient-specific induced pluripotent stem cells. Cell Stem Cell. 2013;12(1):101–13.PubMedPubMedCentralCrossRefGoogle Scholar
  68. 68.
    Han L, et al. Study familial hypertrophic cardiomyopathy using patient-specific induced pluripotent stem cells. Cardiovasc Res. 2014;104(2):258–69.PubMedPubMedCentralCrossRefGoogle Scholar
  69. 69.
    Sun N, et al. Patient-specific induced pluripotent stem cells as a model for familial dilated cardiomyopathy. Sci Transl Med. 2012;4(130):130ra47.PubMedPubMedCentralCrossRefGoogle Scholar
  70. 70.
    Streckfuss-Bömeke K, et al. Severe DCM phenotype of patient harboring RBM20 mutation S635A can be modeled by patient-specific induced pluripotent stem cell-derived cardiomyocytes. J Mol Cell Cardiol. 2017;113:9–21.PubMedCrossRefPubMedCentralGoogle Scholar
  71. 71.
    Wyles SP, et al. Pharmacological modulation of calcium homeostasis in familial dilated cardiomyopathy: an in vitro analysis from an RBM20 patient-derived iPSC model. Clin Transl Sci. 2016;9(3):158–67.PubMedPubMedCentralCrossRefGoogle Scholar
  72. 72.
    Ma D, et al. Generation of patient-specific induced pluripotent stem cell-derived cardiomyocytes as a cellular model of arrhythmogenic right ventricular cardiomyopathy. Eur Heart J. 2013;34(15):1122–33.PubMedCrossRefPubMedCentralGoogle Scholar
  73. 73.
    Caspi O, et al. Modeling of arrhythmogenic right ventricular cardiomyopathy with human induced pluripotent stem cells. Circ Cardiovasc Genet. 2013;6(6):557–68.PubMedCrossRefPubMedCentralGoogle Scholar
  74. 74.
    Kim C, et al. Studying arrhythmogenic right ventricular dysplasia with patient-specific iPSCs. Nature. 2013;494(7435):105–10.PubMedPubMedCentralCrossRefGoogle Scholar
  75. 75.
    Seeger T, et al. A premature termination codon mutation of MYBPC3 causes hypertrophic cardiomyopathy via chronic activation of nonsense-mediated decay. Circulation. 2019;139:799–811.PubMedCrossRefPubMedCentralGoogle Scholar
  76. 76.
    Stöhr A, et al. Contractile abnormalities and altered drug response in engineered heart tissue from Mybpc3-targeted knock-in mice. J Mol Cell Cardiol. 2013;63:189–98.PubMedCrossRefPubMedCentralGoogle Scholar
  77. 77.
    Hinson JT, et al. HEART DISEASE. Titin mutations in iPS cells define sarcomere insufficiency as a cause of dilated cardiomyopathy. Science. 2015;349(6251):982–6.PubMedPubMedCentralCrossRefGoogle Scholar
  78. 78.
    Cashman TJ, et al. Human engineered cardiac tissues created using induced pluripotent stem cells reveal functional characteristics of BRAF-mediated hypertrophic cardiomyopathy. PLoS One. 2016;11(1):e0146697.PubMedPubMedCentralCrossRefGoogle Scholar
  79. 79.
    Stillitano F, et al. Genomic correction of familial cardiomyopathy in human engineered cardiac tissues. Eur Heart J. 2016;37(43):3282–4.PubMedPubMedCentralCrossRefGoogle Scholar
  80. 80.
    Hinson JT, et al. Integrative analysis of PRKAG2 cardiomyopathy iPS and microtissue models identifies AMPK as a regulator of metabolism, survival, and fibrosis. Cell Rep. 2017;19(11):2410.PubMedCrossRefGoogle Scholar
  81. 81.
    Nakamura K, et al. iPS cell modeling of cardiometabolic diseases. J Cardiovasc Transl Res. 2013;6(1):46–53.PubMedCrossRefGoogle Scholar
  82. 82.
    Tavian D, et al. Generation of induced Pluripotent Stem Cells as disease modelling of NLSDM. Mol Genet Metab. 2017;121(1):28–34.PubMedPubMedCentralCrossRefGoogle Scholar
  83. 83.
    Wang G, et al. Modeling the mitochondrial cardiomyopathy of Barth syndrome with induced pluripotent stem cell and heart-on-chip technologies. Nat Med. 2014;20(6):616–23.PubMedPubMedCentralCrossRefGoogle Scholar
  84. 84.
    Drawnel FM, et al. Disease modeling and phenotypic drug screening for diabetic cardiomyopathy using human induced pluripotent stem cells. Cell Rep. 2014;9(3):810–21.PubMedCrossRefGoogle Scholar
  85. 85.
    Prathipati P, et al. Systems biology approaches to a rational drug discovery paradigm. Curr Top Med Chem. 2016;16(9):1009–25.PubMedCrossRefGoogle Scholar
  86. 86.
    Moffat JG, et al. Opportunities and challenges in phenotypic drug discovery: an industry perspective. Nat Rev Drug Discov. 2017;16(8):531–43.PubMedCrossRefGoogle Scholar
  87. 87.
    Vincent F, et al. Developing predictive assays: the phenotypic screening “rule of 3”. Sci Transl Med. 2015;7(293):293ps15.PubMedCrossRefGoogle Scholar
  88. 88.
    Ioannidis JP. Why most published research findings are false. PLoS Med. 2005;2(8):e124.PubMedPubMedCentralCrossRefGoogle Scholar
  89. 89.
    Osherovich L. Hedging against academic risk. Science-Business eXchange. 2011;4(15):416.CrossRefGoogle Scholar
  90. 90.
    Prinz F, et al. Believe it or not: how much can we rely on published data on potential drug targets? Nat Rev Drug Discov. 2011;10:712.PubMedCrossRefPubMedCentralGoogle Scholar
  91. 91.
    Scannell JW, et al. When quality beats quantity: decision theory, drug discovery, and the reproducibility crisis. PLoS One. 2016;11(2):e0147215.PubMedPubMedCentralCrossRefGoogle Scholar
  92. 92.
    Nelson MR, et al. The support of human genetic evidence for approved drug indications. Nat Genet. 2015;47(8):856–60.PubMedCrossRefPubMedCentralGoogle Scholar
  93. 93.
    Reddy AS, et al. Polypharmacology: drug discovery for the future. Expert Rev Clin Pharmacol. 2013;6(1):41–7.PubMedCrossRefPubMedCentralGoogle Scholar
  94. 94.
    Mullard A. New drugs cost US$2.6 billion to develop. Nat Rev Drug Discov. 2014;13:877.Google Scholar
  95. 95.
    Hoffmann P, et al. Are hERG channel inhibition and QT interval prolongation all there is in drug-induced torsadogenesis? A review of emerging trends. J Pharmacol Toxicol Methods. 2006;53(2):87–105.PubMedCrossRefPubMedCentralGoogle Scholar
  96. 96.
    Redfern WS, et al. Relationships between preclinical cardiac electrophysiology, clinical QT interval prolongation and torsade de pointes for a broad range of drugs: evidence for a provisional safety margin in drug development. Cardiovasc Res. 2003;58(1):32–45.PubMedCrossRefPubMedCentralGoogle Scholar
  97. 97.
    Sager PT, et al. Rechanneling the cardiac proarrhythmia safety paradigm: a meeting report from the Cardiac Safety Research Consortium. Am Heart J. 2014;167(3):292–300.PubMedCrossRefPubMedCentralGoogle Scholar
  98. 98.
    Lawrence CL, et al. Nonclinical proarrhythmia models: predicting Torsades de Pointes. J Pharmacol Toxicol Methods. 2005;52(1):46–59.PubMedCrossRefPubMedCentralGoogle Scholar
  99. 99.
    Kannankeril P, et al. Drug-induced long QT syndrome. Pharmacol Rev. 2010;62(4):760–81.PubMedPubMedCentralCrossRefGoogle Scholar
  100. 100.
    Gintant G, et al. Evolution of strategies to improve preclinical cardiac safety testing. Nat Rev Drug Discov. 2016;15(7):457–71.PubMedCrossRefPubMedCentralGoogle Scholar
  101. 101.
    Andrejak M, et al. Drug-induced valvular heart disease: an update. Arch Cardiovasc Dis. 2013;106(5):333–9.PubMedCrossRefPubMedCentralGoogle Scholar
  102. 102.
    Pfeiffer ER, et al. Specific prediction of clinical QT prolongation by kinetic image cytometry in human stem cell derived cardiomyocytes. J Pharmacol Toxicol Methods. 2016;81:263–73.PubMedCrossRefPubMedCentralGoogle Scholar
  103. 103.
    Watanabe H, et al. Usefulness of cardiotoxicity assessment using calcium transient in human induced pluripotent stem cell-derived cardiomyocytes. J Toxicol Sci. 2017;42(4):519–27.PubMedCrossRefPubMedCentralGoogle Scholar
  104. 104.
    Millard D, et al. Cross-site reliability of human induced pluripotent stem cell-derived cardiomyocyte based safety assays using microelectrode arrays: results from a blinded CiPA Pilot Study. Toxicol Sci. 2018;164(2):550–62.PubMedPubMedCentralCrossRefGoogle Scholar
  105. 105.
    Blinova K, et al. International multisite study of human-induced pluripotent stem cell-derived cardiomyocytes for drug proarrhythmic potential assessment. Cell Rep. 2018;24(13):3582–92.PubMedPubMedCentralCrossRefGoogle Scholar
  106. 106.
    Gilchrist KH, et al. High-throughput cardiac safety evaluation and multi-parameter arrhythmia profiling of cardiomyocytes using microelectrode arrays. Toxicol Appl Pharmacol. 2015;288(2):249–57.PubMedCrossRefPubMedCentralGoogle Scholar
  107. 107.
    Harris K, et al. Comparison of electrophysiological data from human-induced pluripotent stem cell-derived cardiomyocytes to functional preclinical safety assays. Toxicol Sci. 2013;134(2):412–26.PubMedCrossRefPubMedCentralGoogle Scholar
  108. 108.
    Blinova K, et al. Comprehensive translational assessment of human-induced pluripotent stem cell derived cardiomyocytes for evaluating drug-induced arrhythmias. Toxicol Sci. 2017;155(1):234–47.PubMedCrossRefPubMedCentralGoogle Scholar
  109. 109.
    Ando H, et al. A new paradigm for drug-induced torsadogenic risk assessment using human iPS cell-derived cardiomyocytes. J Pharmacol Toxicol Methods. 2017;84:111–27.PubMedCrossRefPubMedCentralGoogle Scholar
  110. 110.
    Yamazaki D, et al. Proarrhythmia risk prediction using human induced pluripotent stem cell-derived cardiomyocytes. J Pharmacol Sci. 2018;136(4):249–56.PubMedCrossRefPubMedCentralGoogle Scholar
  111. 111.
    Qu Y, et al. Proarrhythmia risk assessment in human induced pluripotent stem cell-derived cardiomyocytes using the Maestro MEA Platform. Toxicol Sci. 2015;147(1):286–95.PubMedCrossRefPubMedCentralGoogle Scholar
  112. 112.
    Kitaguchi T, et al. CSAHi study: Evaluation of multi-electrode array in combination with human iPS cell-derived cardiomyocytes to predict drug-induced QT prolongation and arrhythmia – effects of 7 reference compounds at 10 facilities. J Pharmacol Toxicol Methods. 2016;78:93–102.PubMedCrossRefPubMedCentralGoogle Scholar
  113. 113.
    Kitaguchi T, et al. CSAHi study: detection of drug-induced ion channel/receptor responses, QT prolongation, and arrhythmia using multi-electrode arrays in combination with human induced pluripotent stem cell-derived cardiomyocytes. J Pharmacol Toxicol Methods. 2017;85:73–81.PubMedCrossRefPubMedCentralGoogle Scholar
  114. 114.
    Nozaki Y, et al. CSAHi study: validation of multi-electrode array systems (MEA60/2100) for prediction of drug-induced proarrhythmia using human iPS cell-derived cardiomyocytes – assessment of inter-facility and cells lot-to-lot-variability. Regul Toxicol Pharmacol. 2016;77:75–86.PubMedCrossRefPubMedCentralGoogle Scholar
  115. 115.
    Nozaki Y, et al. CSAHi study-2: Validation of multi-electrode array systems (MEA60/2100) for prediction of drug-induced proarrhythmia using human iPS cell-derived cardiomyocytes: assessment of reference compounds and comparison with non-clinical studies and clinical information. Regul Toxicol Pharmacol. 2017;88:238–51.PubMedCrossRefGoogle Scholar
  116. 116.
    Grimm FA, et al. High-content assay multiplexing for toxicity screening in induced pluripotent stem cell-derived cardiomyocytes and hepatocytes. Assay Drug Dev Technol. 2015;13(9):529–46.PubMedPubMedCentralCrossRefGoogle Scholar
  117. 117.
    Csöbönyeiová M, et al. Toxicity testing and drug screening using iPSC-derived hepatocytes, cardiomyocytes, and neural cells. Can J Physiol Pharmacol. 2016;94(7):687–94.PubMedCrossRefPubMedCentralGoogle Scholar
  118. 118.
    Savalia S, et al. Cardiac arrhythmia classification by multi-layer perceptron and convolution neural networks. Bioengineering (Basel). 2018;5(2):35.PubMedCentralCrossRefGoogle Scholar
  119. 119.
    Andreotti F, et al. Comparing feature-based classifiers and convolutional neural networks to detect arrhythmia from short segments of ECG. Comput Cardiol. 2017;44:1–4.Google Scholar
  120. 120.
    Rajpurkar P, et al. Cardiologist-level arrhythmia detection with con-volutional neural networks. arXiv170701836. 2017. 2017.Google Scholar
  121. 121.
    Yeh ET, et al. Cardiovascular complications of cancer therapy: incidence, pathogenesis, diagnosis, and management. J Am Coll Cardiol. 2009;53(24):2231–47.PubMedCrossRefGoogle Scholar
  122. 122.
    Aleman BM, et al. Cardiovascular disease after cancer therapy. EJC Suppl. 2014;12(1):18–28.PubMedPubMedCentralCrossRefGoogle Scholar
  123. 123.
    Moslehi J, et al. Grounding cardio-oncology in basic and clinical science. Circulation. 2017;136(1):3–5.PubMedPubMedCentralCrossRefGoogle Scholar
  124. 124.
    Sharma A, et al. High-throughput screening of tyrosine kinase inhibitor cardiotoxicity with human induced pluripotent stem cells. Sci Transl Med. 2017;9(377):eaaf2584.PubMedPubMedCentralCrossRefGoogle Scholar
  125. 125.
    Lamore SD, et al. Deconvoluting kinase inhibitor induced cardiotoxicity. Toxicol Sci. 2017;158(1):213–26.PubMedPubMedCentralCrossRefGoogle Scholar
  126. 126.
    Talbert DR, et al. A multi-parameter in vitro screen in human stem cell-derived cardiomyocytes identifies ponatinib-induced structural and functional cardiac toxicity. Toxicol Sci. 2015;143(1):147–55.PubMedCrossRefGoogle Scholar
  127. 127.
    Moslehi JJ, et al. Tyrosine kinase inhibitor-associated cardiovascular toxicity in chronic myeloid leukemia. J Clin Oncol. 2015;33(35):4210–8.PubMedPubMedCentralCrossRefGoogle Scholar
  128. 128.
    Kawatou M, et al. Modelling Torsade de Pointes arrhythmias in vitro in 3D human iPS cell-engineered heart tissue. Nat Commun. 2017;8(1):1078.PubMedPubMedCentralCrossRefGoogle Scholar
  129. 129.
    Takeda M, et al. Development of in vitro drug-induced cardiotoxicity assay by using three-dimensional cardiac tissues derived from human induced pluripotent stem cells. Tissue Eng Part C Methods. 2018;24(1):56–67.PubMedPubMedCentralCrossRefGoogle Scholar
  130. 130.
    Amano Y, et al. Development of vascularized iPSC derived 3D-cardiomyocyte tissues by filtration Layer-by-Layer technique and their application for pharmaceutical assays. Acta Biomater. 2016;33:110–21.PubMedCrossRefGoogle Scholar
  131. 131.
    Lu HF, et al. Engineering a functional three-dimensional human cardiac tissue model for drug toxicity screening. Biofabrication. 2017;9(2):025011.PubMedCrossRefGoogle Scholar
  132. 132.
    Huebsch N, et al. Miniaturized iPS-cell-derived cardiac muscles for physiologically relevant drug response analyses. Sci Rep. 2016;6:24726.PubMedPubMedCentralCrossRefGoogle Scholar
  133. 133.
    Mannhardt I, et al. Blinded contractility analysis in hiPSC-cardiomyocytes in engineered heart tissue format: comparison with human atrial trabeculae. Toxicol Sci. 2017;158(1):164–75.PubMedPubMedCentralCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Arne A. N. Bruyneel
    • 1
  • Tyler Muser
    • 1
  • Vaidya Parthasarathy
    • 1
  • Dries Feyen
    • 1
  • Mark Mercola
    • 1
    Email author
  1. 1.Cardiovascular Institute and the Department of MedicineStanford UniversityStanfordUSA

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