Lipidinanopartikkelien koostumuksen optimointi endosomaalisen paon ja RNA:n kuljetuksen tehostamiseksi

RNA therapies have attracted increasing interest due to their broad potential applications. However, the use of RNA is limited by its large size, negative charge, susceptibility to degradation, and poor cellular uptake. To address these challenges, lipid nanoparticles (LNPs) have been developed for RNA delivery. Although LNP-based RNA therapeutics have demonstrated clinical efficacy, efficient endosomal escape remains the most significant bottleneck in RNA delivery. The aim of this review is to examine how the lipid composition of LNPs can be optimized to enhance endosomal escape and improve RNA delivery. This review discusses the endosomal system, the structure of LNPs, and key mechanisms of endosomal escape. In particular, it focuses on the effects of different lipid components on the efficiency of RNA delivery. Based on the literature, endosomal escape is unlikely to rely on a single mechanism, but rather on the combined effects of multiple mechanisms. One particularly critical factor in endosomal escape is the protonation of ionizable lipids in the acidic environment of the endosome. The most effective lipid nanoparticle (LNP) formulations have been shown to contain ionizable lipids with a pKa in the range of approximately 6.2–6.9. Furthermore, lipid molecular shape has a significant impact on endosomal escape, as cone-shaped lipids that promote the formation of the inverted hexagonal phase have been consistently associated with enhanced membrane destabilization and improved RNA delivery. Overall, the findings suggest that lipid nanoparticle composition must be optimized holistically and in a target-specific manner to achieve RNA delivery that is both effective and safe. In the future, as lipid nanoparticle compositions continue to evolve, RNA therapies could potentially be applied more broadly in the treatment of various diseases, and the use of artificial intelligence may provide a promising tool for optimizing LNP formulations.