@article {Morotti2020.12.17.423297, author = {Stefano Morotti and Caroline Liu and Bence Hegyi and Haibo Ni and Alex Fogli Iseppe and Lianguo Wang and Crystal M. Ripplinger and Donald M. Bers and Andrew G. Edwards and Eleonora Grandi}, title = {Quantitative cross-species translators of cardiac myocyte electrophysiology: model training, experimental validation, and applications}, elocation-id = {2020.12.17.423297}, year = {2020}, doi = {10.1101/2020.12.17.423297}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Animal experimentation is key in the evaluation of cardiac efficacy and safety of novel therapeutic compounds. However, inter-species differences in the mechanisms regulating excitation-contraction coupling can limit the translation of experimental findings from animal models to human physiology, and undermine the assessment of drugs{\textquoteright} efficacy and safety. Here, we built a suite of translators for quantitatively mapping electrophysiological responses in ventricular myocytes across species. We trained these statistical operators using a broad dataset obtained by simulating populations of our biophysically detailed computational models of action potential and Ca2+ transient in mouse, rabbit, and human. We then tested our translators against experimental data describing the response to stimuli, such as ion channel block, change in beating rate, and β-adrenergic challenge. We demonstrate that this approach is well suited to predicting the effects of perturbations across different species or experimental conditions, and suggest its integration into mechanistic studies and drug development pipelines.Competing Interest StatementThe authors have declared no competing interest.}, URL = {https://www.biorxiv.org/content/early/2020/12/18/2020.12.17.423297}, eprint = {https://www.biorxiv.org/content/early/2020/12/18/2020.12.17.423297.full.pdf}, journal = {bioRxiv} }