Honglei Zhang

Lipid nanoparticle (LNP)‐mRNA technology has profoundly transformed the biomedical landscape, establishing itself as a highly versatile and powerful platform with substantial therapeutic and prophylactic potential across a wide range of diseases. This review summarizes recent advances in LNP delivery systems aimed at unlocking the full potential of RNA therapeutics. Key focuses include: 1) the design and screening of novel lipid molecules to improve mRNA delivery efficiency and targeting; 2) optimization of administration routes, LNP surface functionalization, and formulation components; and 3) advances in lyophilized LNP formulations. We also highlight the growing integration of artificial intelligence (AI) for designing next‐generation LNPs and overcoming existing translational barriers. Furthermore, the review provides a comprehensive overview of clinical applications of RNA‐LNPs in infectious diseases, cancer immunotherapy, gene therapy, cell‐based therapeutics, and RNAi‐LNP therapeutics, offering systematic strategies to enhance delivery efficacy and translational capacity. Finally, we discuss the future directions and unresolved challenges, including multimodal fusion delivery methodology of LNP and non‐LNP carriers, the interdisciplinary integration of various fields, and the bottleneck of extrahepatic delivery strategies, offering systematic insights into the translational pathway of mRNA‐LNP therapeutics.

Analogs of the mRNA 5′-cap are indispensable for mRNA translation, stability, translation efficiency, and immunogenicity, with emerging potential applications in novel preventive and therapeutic interventions. Here, this study presents a novel approach for designing mRNA Cap1 analogs with optimized biological activity. We leveraged the power of generative pre-trained transformer (GPT) architecture to generate novel cap analog sequences. A discriminative model is then employed to select promising candidates based on their predicted expression levels. Our results demonstrate that the GPT-based generative model significantly outperforms a traditional recurrent neural network (RNN) in terms of perplexity, indicating its superior ability to generate diverse and accurate cap analog sequences. Furthermore, the expression screening model achieves high accuracy in identifying potential high-expression candidates. Then, we synthesized a set of designed novel trinucleotide mRNA Cap1 analogs with modified ribose and incorporated it into mRNA using T7 polymerase. A series of experiments revealed that mRNA capped with YK-CAP-01–06 analogs exhibited increased translation efficiency and decapping enzyme stability compared to the commercially available cap-analog-capped mRNA. Finally, the potential application value was explored by constructing OVA, RSV preF- and VZV gE-mRNA vaccines, which resulted in significant (vs. controls) inhibition of tumor growth and an increase in IgG antibody levels in mice.

YK-201, YK-202, and YK-209 exhibit superior mRNA delivery efficiency both in vitro and in vivo and enable muscle-selective mRNA delivery, inducing robust humoral immune responses and exhibit good tolerance formulated with RSV-preF-mRNA vaccine.

Messenger RNA (mRNA) therapeutics hold significant potential across a wide range of medical applications.