Mildner R, Hak S, Parot J, Hyldbakk A, Borgos S E, Some D, Johann C, Caputo F
Wyatt Technology, Hochstrasse 12a, 56307 Dernbach, Germany.
Department of Biotechnology and Nanomedicine, SINTEF Industry, Trondheim, Norway.
Eur J Pharm Biopharm. 2021 Jun;163:252-265. doi: 10.1016/j.ejpb.2021.03.004. Epub 2021 Mar 18.
Lipid-based nanoparticles for RNA delivery (LNP-RNA) are revolutionizing the nanomedicine field, with one approved gene therapy formulation and two approved vaccines against COVID-19, as well as multiple ongoing clinical trials. As for other innovative nanopharmaceuticals (NPhs), the advancement of robust methods to assess their quality and safety profiles-in line with regulatory needs-is critical for facilitating their development and clinical translation. Asymmetric-flow field-flow fractionation coupled to multiple online optical detectors (MD-AF4) is considered a very versatile and robust approach for the physical characterisation of nanocarriers, and has been used successfully for measuring particle size, polydispersity and physical stability of lipid-based systems, including liposomes and solid lipid nanoparticles. However, the unique core structure of LNP-RNA, composed of ionizable lipids electrostatically complexed with RNA, and the relatively labile lipid-monolayer coating, is more prone to destabilization during focusing in MD-AF4 than previously characterised nanoparticles, resulting in particle aggregation and sample loss. Hence characterisation of LNP-RNA by MD-AF4 needs significant adaptation of the methods developed for liposomes. To improve the performance of MD-AF4 applied to LNP-RNA in a systematic and comprehensive manner, we have explored the use of the frit-inlet channel where, differently from the standard AF4 channel, the particles are relaxed hydrodynamically as they are injected. The absence of a focusing step minimizes contact between the particle and the membrane, reducing artefacts (e.g. sample loss, particle aggregation). Separation in a frit-inlet channel enables satisfactory reproducibility and acceptable sample recovery in the commercially available MD-AF4 instruments. In addition to slice-by-slice measurements of particle size, MD-AF4 also allows to determine particle concentration and the particle size distribution, demonstrating enhanced versatility beyond standard sizing measurements.
用于RNA递送的脂质纳米颗粒(LNP-RNA)正在彻底改变纳米医学领域,有一种已获批的基因治疗制剂和两种获批的抗COVID-19疫苗,还有多项正在进行的临床试验。与其他创新纳米药物(NPhs)一样,开发符合监管要求的稳健方法来评估其质量和安全性概况,对于促进其开发和临床转化至关重要。与多个在线光学检测器联用的不对称流场流分级分离法(MD-AF4)被认为是一种非常通用且稳健的纳米载体物理表征方法,已成功用于测量脂质基系统(包括脂质体和固体脂质纳米颗粒)的粒径、多分散性和物理稳定性。然而,LNP-RNA独特的核心结构由与RNA静电复合的可电离脂质组成,以及相对不稳定的脂质单层涂层,在MD-AF4聚焦过程中比以前表征的纳米颗粒更容易失稳,导致颗粒聚集和样品损失。因此,用MD-AF4对LNP-RNA进行表征需要对为脂质体开发的方法进行重大调整。为了系统全面地提高应用于LNP-RNA的MD-AF4的性能,我们探索了使用烧结入口通道,与标准AF4通道不同,颗粒在注入时通过流体动力学方式得以松弛。没有聚焦步骤可最大程度减少颗粒与膜之间的接触,减少假象(如样品损失、颗粒聚集)。在烧结入口通道中进行分离可在市售MD-AF4仪器中实现令人满意的重现性和可接受的样品回收率。除了逐片测量粒径外,MD-AF4还能够确定颗粒浓度和粒径分布,显示出超越标准尺寸测量的增强通用性。