Mihaila Radu, Ruhela Dipali, Keough Edward, Cherkaev Elena, Chang Silvia, Galinski Beverly, Bartz René, Brown Duncan, Howell Bonnie, Cunningham James J
Sirna Therapeutics, 1700 Owens Street, Fourth Floor, San Francisco, CA 94158, USA.
Sirna Therapeutics, 1700 Owens Street, Fourth Floor, San Francisco, CA 94158, USA.
Mol Ther Nucleic Acids. 2017 Jun 16;7:246-255. doi: 10.1016/j.omtn.2017.04.003. Epub 2017 Apr 12.
Lipid nanoparticles (LNPs) have been used to successfully deliver small interfering RNAs (siRNAs) to target cells in both preclinical and clinical studies and currently are the leading systems for in vivo delivery. Here, we propose the use of an ordinary differential equation (ODE)-based model as a tool for optimizing LNP-mediated delivery of siRNAs. As a first step, we have used a combination of experimental and computational approaches to develop and validate a mathematical model that captures the critical features for efficient siRNA-LNP delivery in vitro. This model accurately predicts mRNA knockdown resulting from novel combinations of siRNAs and LNPs in vitro. As demonstrated, this model can be effectively used as a screening tool to select the most efficacious LNPs, which can then further be evaluated in vivo. The model serves as a starting point for the future development of next generation models capable of capturing the additional complexity of in vivo delivery.
在临床前和临床研究中,脂质纳米颗粒(LNPs)已成功用于将小干扰RNA(siRNAs)递送至靶细胞,目前是体内递送的主要系统。在此,我们提出使用基于常微分方程(ODE)的模型作为优化LNP介导的siRNAs递送的工具。作为第一步,我们结合实验和计算方法来开发和验证一个数学模型,该模型捕获了体外有效siRNA-LNP递送的关键特征。该模型准确预测了体外新型siRNAs和LNPs组合导致的mRNA敲低。如所示,该模型可有效用作筛选工具,以选择最有效的LNPs,然后可在体内进一步评估。该模型是未来开发能够捕获体内递送额外复杂性的下一代模型的起点。