Laboratory for Molecular Design of Pharmaceutics, Faculty of Pharmaceutical Sciences, Hokkaido University, Kita-12, Nishi-6, Kita-Ku, Sapporo 060-0812, Japan.
Laboratory for Molecular Design of Pharmaceutics, Faculty of Pharmaceutical Sciences, Hokkaido University, Kita-12, Nishi-6, Kita-Ku, Sapporo 060-0812, Japan.
J Control Release. 2020 Nov 10;327:467-476. doi: 10.1016/j.jconrel.2020.08.031. Epub 2020 Aug 25.
Although great advances have been made in the delivery of short RNAs by lipid nanoparticles (LNPs), the optimal formulation composition and physicochemical properties of LNPs for long RNA (including mRNA) remain unclear. In the present study, we optimized the lipid composition of liver-targeted mRNA-loaded LNPs that were prepared with pH-sensitive cationic lipids that had been previously designed for siRNA delivery through a two stepped design of experiment (DoE). Multiple responses including physicochemical properties, gene expression, and liver-specificity were analyzed in order, not only to understand the role of each formulation parameter, but also to examine parameters that would be difficult to predict. We found that particle size and the PEG-to-phospholipid (PEG/PL) ratio were additional key factors for liver-specific gene expression in addition to the other formulation factors. The optimized formulation showed a better gene expression compared to other lipid formulations from industry leaders. These findings suggest that a "DoE with multiple responses" approach can be used to predict significant parameters and permit optimized formulations to be prepared more efficiently.
尽管在通过脂质纳米粒 (LNP) 递送短 RNA 方面取得了重大进展，但对于长 RNA（包括 mRNA）的 LNP 的最佳配方组成和理化性质仍不清楚。在本研究中，我们通过两步实验设计 (DoE) 优化了先前设计用于 siRNA 递送的 pH 敏感阳离子脂质制备的肝靶向 mRNA 负载 LNP 的脂质组成。我们依次分析了多种反应，包括理化性质、基因表达和肝脏特异性，不仅要了解每个配方参数的作用，还要检查那些难以预测的参数。我们发现，除了其他配方因素外，粒径和聚乙二醇与磷脂的比例（PEG/PL）也是肝脏特异性基因表达的另外两个关键因素。与来自行业领导者的其他脂质配方相比，优化的配方显示出更好的基因表达。这些发现表明，“具有多响应的 DoE”方法可用于预测重要参数，并允许更有效地制备优化的配方。
