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迈向基于人工智能的细胞外囊泡精准药物递送。

Towards artificial intelligence-enabled extracellular vesicle precision drug delivery.

作者信息

Greenberg Zachary F, Graim Kiley S, He Mei

机构信息

Department of Pharmaceutics, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA.

Department of Computer & Information Science & Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL 32610, USA.

出版信息

Adv Drug Deliv Rev. 2023 Aug;199:114974. doi: 10.1016/j.addr.2023.114974. Epub 2023 Jun 23.

Abstract

Extracellular Vesicles (EVs), particularly exosomes, recently exploded into nanomedicine as an emerging drug delivery approach due to their superior biocompatibility, circulating stability, and bioavailability in vivo. However, EV heterogeneity makes molecular targeting precision a critical challenge. Deciphering key molecular drivers for controlling EV tissue targeting specificity is in great need. Artificial intelligence (AI) brings powerful prediction ability for guiding the rational design of engineered EVs in precision control for drug delivery. This review focuses on cutting-edge nano-delivery via integrating large-scale EV data with AI to develop AI-directed EV therapies and illuminate the clinical translation potential. We briefly review the current status of EVs in drug delivery, including the current frontier, limitations, and considerations to advance the field. Subsequently, we detail the future of AI in drug delivery and its impact on precision EV delivery. Our review discusses the current universal challenge of standardization and critical considerations when using AI combined with EVs for precision drug delivery. Finally, we will conclude this review with a perspective on future clinical translation led by a combined effort of AI and EV research.

摘要

细胞外囊泡(EVs),尤其是外泌体,由于其卓越的生物相容性、循环稳定性和体内生物利用度,最近作为一种新兴的药物递送方法在纳米医学领域迅速兴起。然而,EV的异质性使得分子靶向的精确性成为一个关键挑战。迫切需要破译控制EV组织靶向特异性的关键分子驱动因素。人工智能(AI)为指导工程化EV在药物递送精确控制方面的合理设计带来了强大的预测能力。本综述重点关注通过将大规模EV数据与AI相结合来开发AI指导的EV疗法,并阐明其临床转化潜力,以实现前沿的纳米递送。我们简要回顾了EV在药物递送中的现状,包括当前的前沿进展、局限性以及推动该领域发展的注意事项。随后,我们详细阐述了AI在药物递送中的未来以及它对精确EV递送的影响。我们的综述讨论了当前标准化的普遍挑战以及将AI与EV结合用于精确药物递送时的关键注意事项。最后,我们将结合AI和EV研究的共同努力,对未来的临床转化前景进行总结。

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