计算生物学
免疫系统
信使核糖核酸
医学
生物信息学
生物
遗传学
免疫学
基因
作者
Lifeng Xu,Chao Li,Rui Liao,Qin Xiao,Xiaoran Wang,Zhuo Zhao,Weijun Zhang,Xiaoyan Ding,Yuxue Cao,Larry Cai,Joseph Rosenecker,Shan Guan,Jie Tang
标识
DOI:10.1021/acs.molpharmaceut.4c00863
摘要
The COVID-19 pandemic has spotlighted the potential of in vitro transcribed (IVT) mRNA vaccines with their demonstrated efficacy, safety, cost-effectiveness, and rapid manufacturing. Numerous IVT mRNA vaccines are now under clinical trials for a range of targets, including infectious diseases, cancers, and genetic disorders. Despite their promise, IVT mRNA vaccines face hurdles such as limited expression levels, nonspecific targeting beyond the liver, rapid degradation, and unintended immune activation. Overcoming these challenges is crucial to harnessing the full therapeutic potential of IVT mRNA vaccines for global health advancement. This review provides a comprehensive overview of the latest research progress and optimization strategies for IVT mRNA molecules and delivery systems, including the application of artificial intelligence (AI) models and deep learning techniques for IVT mRNA structure optimization and mRNA delivery formulation design. We also discuss recent development of the delivery platforms, such as lipid nanoparticles (LNPs), polymers, and exosomes, which aim to address challenges related to IVT mRNA protection, cellular uptake, and targeted delivery. Lastly, we offer insights into future directions for improving IVT mRNA vaccines, with the hope to spur further progress in IVT mRNA vaccine research and development.
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