Marei Hany E
Department of Cytology and Histology, Faculty of Veterinary Medicine, Mansoura University, Mansoura, Egypt.
Cell Tissue Res. 2025 Aug 14. doi: 10.1007/s00441-025-03999-7.
Integrated with artificial intelligence (AI), induced pluripotent stem cell (iPSC) technology could enhance disease modeling, cellular biology, regenerative medicine, and pharmaceutical development. AI has enhanced iPSC differentiation, cultural conditions, and speed of disease-specific model development. Furthermore, AI-based massive omics database analysis exposes hidden biological tendencies, enhancing customized treatment. Investigating new AI algorithms will enable one to solve problems, including interpretability and data quality, resulting from AI's interaction with iPSC technology. These advances fundamentally alter stem cell research and therapeutic applications, therefore facilitating the emergence of regenerative medicine and precision healthcare. AI has evolved in biomedical research into a transformational technology unique in great data analysis, predictive modeling, and automation capacity. AI integration increases the development of patient-specific cell types for disease modeling, pharmacological research, and regenerative medicine by substantially improving IPSC-based technologies. Emphasizing changes in disease models, alternative methodologies, and cellular reprogramming, this work examines current advancements in the use of AI in iPSC technology. The argument on significant obstacles and possibilities reveals how AI could alter the objectives of iPSC research and implementation.
诱导多能干细胞（iPSC）技术与人工智能（AI）相结合，可以加强疾病建模、细胞生物学、再生医学和药物开发。人工智能提高了iPSC的分化、培养条件以及疾病特异性模型的开发速度。此外，基于人工智能的大规模组学数据库分析揭示了隐藏的生物学倾向，增强了个性化治疗。研究新的人工智能算法将有助于解决人工智能与iPSC技术相互作用所产生的问题，包括可解释性和数据质量。这些进展从根本上改变了干细胞研究和治疗应用，从而推动了再生医学和精准医疗的出现。人工智能在生物医学研究中已经发展成为一种在大数据分析、预测建模和自动化能力方面独一无二的变革性技术。通过大幅改进基于iPSC的技术，人工智能集成增加了用于疾病建模、药理学研究和再生医学的患者特异性细胞类型的开发。这项工作强调了疾病模型、替代方法和细胞重编程方面的变化，审视了人工智能在iPSC技术应用中的当前进展。关于重大障碍和可能性的讨论揭示了人工智能如何改变iPSC研究和应用的目标。
