Data_Sheet_1_An in silico hiPSC-Derived Cardiomyocyte Model Built With Genetic Algorithm.PDF

The formulation of in silico biophysical models generally requires optimization strategies for reproducing experimentally observed phenomena. In electrophysiological modeling, robust nonlinear regressive methods are often crucial for guaranteeing high fidelity models. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), though nascent, have proven to be useful in cardiac safety pharmacology, regenerative medicine, and in the implementation of patient-specific test benches for investigating inherited cardiac disorders. This study demonstrates the potency of heuristic techniques at formulating biophysical models, with emphasis on a hiPSC-CM model using a novel genetic algorithm (GA) recipe we proposed. The proposed GA protocol was used to develop a hiPSC-CM biophysical computer model by fitting mathematical formulations to experimental data for five ionic currents recorded in hiPSC-CMs. The maximum conductances of the remaining ionic channels were scaled based on recommendations from literature to accurately reproduce the experimentally observed hiPSC-CM action potential (AP) metrics. Near-optimal parameter fitting was achieved for the GA-fitted ionic currents. The resulting model recapitulated experimental AP parameters such as AP durations (APD50, APD75, and APD90), maximum diastolic potential, and frequency of automaticity. The outcome of this work has implications for validating the biophysics of hiPSC-CMs in their use as viable substitutes for human cardiomyocytes, particularly in cardiac safety pharmacology and in the study of inherited cardiac disorders. This study presents a novel GA protocol useful for formulating robust numerical biophysical models. The proposed protocol is used to develop a hiPSC-CM model with implications for cardiac safety pharmacology.

在硅基生物物理模型的构建过程中，通常需要优化策略以再现实验观察到的现象。在电生理建模中，稳健的非线性回归方法对于确保模型的高保真度至关重要。由人类诱导的多能干细胞来源的心肌细胞（hiPSC-CMs）尽管尚处于起步阶段，但已被证明在心脏安全性药理学、再生医学以及患者特异性测试台的实施中用于研究遗传性心脏疾病方面具有实用价值。本研究展示了启发式技术在构建生物物理模型方面的有效性，特别强调了我们提出的创新遗传算法（GA）配方在hiPSC-CM模型中的应用。所提出的GA协议被用于开发hiPSC-CM生物物理计算机模型，通过将数学公式拟合到hiPSC-CMs中记录的五种离子电流的实验数据。剩余的离子通道的最大传导率根据文献中的建议进行缩放，以准确地再现实验观察到的hiPSC-CM动作电位（AP）指标。GA拟合的离子电流实现了近乎最优的参数拟合。该模型再现了实验AP参数，如AP持续时间（APD50、APD75和APD90）、最大舒张电位和自动节律频率。本研究的结果对于验证hiPSC-CMs在作为人类心肌细胞替代品的应用中的生物物理学具有影响，特别是在心脏安全性药理学和遗传性心脏疾病的研究中。本研究提出了一种新的GA协议，该协议可用于构建稳健的数值生物物理模型。所提出的协议被用于开发具有心脏安全性药理学意义的hiPSC-CM模型。