药源性心脏毒性是药物撤市的主要原因之一。长期以来，临床前心脏安全性评价主要依赖对人类ether-à-go-go相关基因（hERG）钾电流的抑制性检测，但该方法存在假阳性与假阴性的局限。为构建更精准的心律失常风险评估体系，美国食品药品监督管理局（FDA）提出了综合离体致心律失常风险评估（CiPA）新范式。近年来，CiPA各工作组持续优化体系。离子通道工作组通过引入生理温度与标准电压等标准化方案，弥补了非临床与临床数据不一致性的局限性，并构建了离子通道数据共享平台；计算机模拟（in-silico）工作组在生理温度下模拟心室动作电位，通过引入多维度输入条件在保持预测准确性的前提下实现更全面的风险评估；基于细胞来源逐步标准化与成熟化的人源干细胞来源的心肌细胞（hSC-CMs）评价体系，实现了通量与可重复性同步提升；心电图（ECG）工作组致力于开发并验证以J-Tpeakc为代表的新型ECG生物标志物，并通过药物浓度-QTc（C-QTc）研究及人工智能（AI）辅助诊断等新兴方法不断优化评估体系。整体而言，CiPA体系的优化不仅提升了心脏安全性评价的准确性、降低了研发成本，也为人用药品注册技术要求国际协调理事会（ICH）指导原则E14/S7BQ&A的发布奠定了实验基础。然而，实验室间的差异、离子通道评估单一性、缺乏多维多器官交互模拟等因素，仍是其全面推广应用所面临的重要挑战。未来，将CiPA与AI、心脏类器官模型相结合，有望进一步解决上述挑战。

Drug-induced cardiotoxicity is one of the primary reasons for drug withdrawal from the market. For a long time, preclinical cardiac safety assessment has primarily relied on inhibitory testing of human ether-à-go-go-related gene (hERG) potassium currents, however, this method is limited by high rates of false positives and false negatives. To establish a more precise arrhythmia risk assessment system, the US Food and Drug Administration (FDA) spearheaded the development of the comprehensive in vitro proarrhythmia assay (CiPA) paradigm. Recent years, CiPA’s various working groups have continued to refine the system. By introducing standardisation protocols such as physiological temperatures and standard voltages, the Ion Channel Working Group has addressed the limitations arising from inconsistencies between preclinical and clinical data, and has established an ion channel datasharing platform. The In Silico Working Group simulates ventricular action potentials at physiological temperatures, continuously optimising models and algorithms, and achieves a more comprehensive risk assessment by incorporating multi-dimensional input conditions whilst maintaining predictive accuracy. The evaluation system based on human stem cell-derived cardiomyocytes (hSCCMs) has demonstrated concurrent improvements in throughput and reproducibility, underpinned by progressively standardised and matured cell sources. The Electrocardiogram Working Group (ECG) is dedicated to developing and validating novel ECG biomarkers, exemplified by J-Tpeakc, whilst continually refining the assessment framework through emerging methodologies such as Concentration-QTc (C-QTc) research and artificial intelligence (AI)-assisted diagnosis. Overall, optimisation of the CiPA system not only enhances the accuracy of cardiac safety assessment and reduces R&D costs but also lays the experimental foundation for the publication of the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) guidance document E14/S7B Q&A. Nevertheless, factors such as inter-laboratory variability, the limited scope of ion channel assessments, and the lack of multi-dimensional, multi-organ interaction simulations remain significant challenges to their widespread adoption. In the future, combining CiPA with Artificial Intelligence and Cardiac Organoids is expected to help address these challenges.

R285.5

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