Current strategies in tailoring methods for engineered exosomes and future avenues in biomedical applications

微泡 再生医学 纳米技术 药物输送 外体 灵活性(工程) 计算机科学 组织工程 材料科学 细胞生物学 计算生物学 生物 医学 生物医学工程 小RNA 干细胞 生物化学 基因 统计 数学
作者
Ankita Mishra,Prerna Singh,Irfan Qayoom,Abhay Prasad,Ashok Kumar
出处
期刊:Journal of Materials Chemistry B [The Royal Society of Chemistry]
卷期号:9 (32): 6281-6309 被引量:34
标识
DOI:10.1039/d1tb01088c
摘要

Exosomes are naturally occurring nanovesicles of endosomal origin, responsible for cellular communication. Depending on the cell type, exosomes display disparity in the cargo and are involved in up/down regulation of different biological pathways. Naturally secreted exosomes, owing to their inherent delivery potential, non-immunogenic nature and limited structural resemblance to the cells have emerged as ideal candidates for various drug delivery and therapeutic applications. Moreover, the structural versatility of exosomes provides greater flexibility for surface modifications to be made in the native configuration, by different methods, like genetic-engineering, chemical procedures, physical methods and microfluidic-technology, to enhance the cargo quality for expanded biomedical applications. Post isolation and prior to engineering exosomes for various applications, the internal and external structural compositions of exosomes are studied via different techniques. Efficiency and scalability of the exosome modification methods are pivotal in determining the scope of the technique for clinical applications. This review majorly focuses on different methods employed for engineering exosomes, and advantages/disadvantages associated with different tailoring approaches, along with the efficacy of engineered exosomes in biomedical applications. Further, the review highlights the importance of a relatively recent avenue for delivery of exosomes via scaffold-based delivery of naïve/engineered exosomes for regenerative medicine and tissue engineering. This review is based on the recent knowledge generated in this field and our comprehension in this domain.
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