Zhang Fuxue, Xia Bozhang, Sun Jiabei, Wang Yufei, Wang Jinjin, Xu Fengfei, Chen Junge, Lu Mei, Yao Xin, Timashev Peter, Zhang Yuanyuan, Chen Meiwan, Che Jing, Li Fangzhou, Liang Xing-Jie
CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology of China, No. 11, First North Road, Zhongguancun, Beijing 100190, China.
Sino-Danish Center for Education and Research, Sino-Danish College of University of Chinese Academy of Sciences, Beijing 100049, China.
Research (Wash D C). 2022 Oct 31;2022:9808429. doi: 10.34133/2022/9808429. eCollection 2022.
Intelligent drug delivery system based on "stimulus-response" mode emerging a promising perspective in next generation lipid-based nanoparticle. Here, we classify signal sources into physical and physiological stimulation according to their origin. The physical signals include temperature, ultrasound, and electromagnetic wave, while physiological signals involve pH, redox condition, and associated proteins. We first summarize external physical response from three main points about efficiency, particle state, and on-demand release. Afterwards, we describe how to design drug delivery using the physiological environment in vivo and present different current application methods. Lastly, we draw a vision of possible future development.
基于“刺激-响应”模式的智能药物递送系统在下一代脂质基纳米颗粒领域展现出广阔的前景。在此，我们根据信号源的来源将其分为物理刺激和生理刺激。物理信号包括温度、超声和电磁波，而生理信号涉及pH值、氧化还原状态及相关蛋白质。我们首先从效率、颗粒状态和按需释放三个要点总结外部物理响应。之后，我们描述如何利用体内生理环境设计药物递送并介绍当前不同的应用方法。最后，我们展望了可能的未来发展前景。
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