A novel ionic model for matured and paced atrial–like hiPSC–CMs integrating IKur and IKCa currents

Human induced pluripotent stem cells-derived cardiomyocytes have revolutionized the field of regenerative medicine, offering unparalleled potential for in-vitro modeling of normal and pathological human cardiomyocytes. The ability to produce stem cardiac myocytes in abundance has opened new avenues for drug efficacy and safety testing, as well as the study of conditions such as atrial fibrillation, a familial cardiac disorder. The development of atrial fibrillation is influenced by ion channel mutations, genetic variants, and other risk factors. Stem cells derived cardiomyocytes hold promise in personalized medicine, as they share the genetic heritage of the donor. While mathematical models have focused on immature stem cardiomyocytes phenotypes, they have primarily relied on a system of stiff ordinary differential equations. Computational modeling of diseased tissue presents an opportunity to evaluate drugs in a patient-specific manner, thereby improving therapeutic targets and ablation techniques. Previous studies categorized cell phenotypes based on action potential morphology, yet classification criteria remains ambiguous. This work introduces the first atrial-specific in-silico model of stem cells ionic currents, leveraging experimental data provided by Altomare et al. It begins by summarizing the baseline electrophysiological model and mathematical descriptions of atrial-specific additional currents. Model parameter tuning was performed through automatic optimization techniques to ensure realistic action potential shape and expedite the parameter adjustment process. The resulting model was validated against rate dependence and atrial-specific ion current blocking data. In summary, the development of an atrial-specific in-silico model represents a significant step forward in understanding cardiac electrophysiology and the potential for personalized medicine in treating conditions like atrial fibrillation. This model offers new tools for drug evaluation, therapeutic improvement, and a deeper comprehension of cardiac phenotypes. ### Competing Interest Statement The authors have declared no competing interest.