纳米颗粒
纳米技术
药物输送
材料科学
生物系统
粒径
粒子(生态学)
人口
航程(航空)
功能(生物学)
化学
生物
复合材料
人口学
物理化学
社会学
进化生物学
生态学
作者
Albert Kamanzi,Yifei Gu,Radin Tahvildari,Zachary Friedenberger,Xingqi Zhu,Romain Berti,Marty Kurylowicz,Dominik Witzigmann,Jayesh A. Kulkarni,Jerry Leung,John Andersson,Andreas Dahlin,Fredrik Höök,Mark Sutton,Pieter R. Cullis,Sabrina Leslie
出处
期刊:ACS Nano
[American Chemical Society]
日期:2021-11-29
卷期号:15 (12): 19244-19255
被引量:33
标识
DOI:10.1021/acsnano.1c04862
摘要
Nanoparticles are a promising solution for delivery of a wide range of medicines and vaccines. Optimizing their design depends on being able to resolve, understand, and predict biophysical and therapeutic properties, as a function of design parameters. While existing tools have made great progress, gaps in understanding remain because of the inability to make detailed measurements of multiple correlated properties. Typically, an average measurement is made across a heterogeneous population, obscuring potentially important information. In this work, we develop and apply a method for characterizing nanoparticles with single-particle resolution. We use convex lens-induced confinement (CLiC) microscopy to isolate and quantify the diffusive trajectories and fluorescent intensities of individual nanoparticles trapped in microwells for long times. First, we benchmark detailed measurements of fluorescent polystyrene nanoparticles against prior data to validate our approach. Second, we apply our method to investigate the size and loading properties of lipid nanoparticle (LNP) vehicles containing silencing RNA (siRNA), as a function of lipid formulation, solution pH, and drug-loading. By taking a comprehensive look at the correlation between the intensity and size measurements, we gain insights into LNP structure and how the siRNA is distributed in the LNP. Beyond introducing an analytic for size and loading, this work allows for future studies of dynamics with single-particle resolution, such as LNP fusion and drug-release kinetics. The prime contribution of this work is to better understand the connections between microscopic and macroscopic properties of drug-delivery vehicles, enabling and accelerating their discovery and development.
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