Li Zuhao, Song Peiran, Li Guangfeng, Han Yafei, Ren Xiaoxiang, Bai Long, Su Jiacan
Department of Orthopedics, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China.
Organoid Research Center, Institute of Translational Medicine, Shanghai University, Shanghai, 200444, China.
Mater Today Bio. 2024 Feb 29;25:101014. doi: 10.1016/j.mtbio.2024.101014. eCollection 2024 Apr.
Traditional hydrogel design and optimization methods usually rely on repeated experiments, which is time-consuming and expensive, resulting in a slow-moving of advanced hydrogel development. With the rapid development of artificial intelligence (AI) technology and increasing material data, AI-energized design and optimization of hydrogels for biomedical applications has emerged as a revolutionary breakthrough in materials science. This review begins by outlining the history of AI and the potential advantages of using AI in the design and optimization of hydrogels, such as prediction and optimization of properties, multi-attribute optimization, high-throughput screening, automated material discovery, optimizing experimental design, and . Then, we focus on the various applications of hydrogels supported by AI technology in biomedicine, including drug delivery, bio-inks for advanced manufacturing, tissue repair, and biosensors, so as to provide a clear and comprehensive understanding of researchers in this field. Finally, we discuss the future directions and prospects, and provide a new perspective for the research and development of novel hydrogel materials for biomedical applications.
传统的水凝胶设计与优化方法通常依赖于反复实验,既耗时又昂贵,导致先进水凝胶的开发进展缓慢。随着人工智能(AI)技术的迅速发展以及材料数据的不断增加,用于生物医学应用的人工智能驱动的水凝胶设计与优化已成为材料科学领域的一项革命性突破。本综述首先概述了人工智能的历史以及在水凝胶设计与优化中使用人工智能的潜在优势,例如性能预测与优化、多属性优化、高通量筛选、自动化材料发现、优化实验设计等。然后,我们重点关注人工智能技术支持的水凝胶在生物医学中的各种应用,包括药物递送、先进制造用生物墨水、组织修复和生物传感器,以便为该领域的研究人员提供清晰而全面的理解。最后,我们讨论了未来的方向和前景,并为生物医学应用新型水凝胶材料的研发提供了新的视角。