Multiparametric approach for the evaluation of lipid nanoparticles for siRNA delivery

Abstract

Nanoparticle-mediated siRNA delivery is a complex process that requires transport across numerous extracellular and intracellular barriers. As such, the development of nanoparticles for efficient delivery would benefit from an understanding of how parameters associated with these barriers relate to the physicochemical properties of nanoparticles. Here, we use a multiparametric approach for the evaluation of lipid nanoparticles (LNPs) to identify relationships between structure, biological function, and biological activity. Our results indicate that evaluation of multiple parameters associated with barriers to delivery such as siRNA entrapment, pKa, LNP stability, and cell uptake as a collective may serve as a useful prescreening tool for the advancement of LNPs in vivo. This multiparametric approach complements the use of in vitro efficacy results alone for prescreening and improves in vitro-in vivo translation by minimizing false negatives. For the LNPs used in this work, the evaluation of multiple parameters enabled the identification of LNP pKa as one of the key determinants of LNP function and activity both in vitro and in vivo. It is anticipated that this type of analysis can aid in the identification of meaningful structure-function-activity relationships, improve the in vitro screening process of nanoparticles before in vivo use, and facilitate the future design of potent nanocarriers.

Keywords: RNAi; drug carrier; gene silencing; thiol-yne.

Fig. 1.

(A) Schematic of cellular delivery pathway via LNPs. The most common barriers to delivery and the physicochemical LNP properties evaluated in this manuscript are listed in parentheses. (B) Synthetic scheme for the preparation of 32 unique lipidoids via the 1,4-Michael addition of a small library of primary amines (red) to propargyl acrylate followed by radical initiated thiol-yne photoaddition with 1-decanethiol. The entire lipid library was formulated into LNPs and used to evaluate correlations between gene silencing and each barrier and physicochemical property listed in A.

Fig. 2.

(A) Dose-dependent knockdown of firefly luciferase via LNP-siRNA in a HeLa cell line expressing both firefly and Renilla luciferase. Results are presented as the luciferase expression normalized to the Renilla expression; (white bars) 50 ng siRNA, (gray bars) 25 ng siRNA, (black bars) 10 ng siRNA. Error bars represent SD, n = 6. (B) Correlation between in vitro luciferase (at 25 ng siRNA) and in vivo FVII gene expression. Vertical error bars represent SD, n = 6, horizontal error bars represent SD, n = 3. Dotted lines represent the 50% in vitro and in vivo gene expression levels. (Top Left) False positives, (Bottom Right) false negatives. Compounds that give better than 50% knockdown in vivo are highlighted in blue.

Fig. 3.

LNPs that give better than 50% knockdown in vivo are highlighted in blue. (A) Extracellular FRET of all 32 LNPs as a function of time. (B) Correlation between in vitro percent of gene expression and extracellular FRET (measured after 2 h). Black vertical error bars represent SD, n = 6. (C) Correlation between in vitro percent gene expression and cell uptake. Black vertical error bars represent SD, n = 6. Horizontal error bars represent SD, n = 2. (D) Relationship between in vitro percent gene expression and intracellular FRET; (+) and (−) indicate the presence and absence of an intracellular FRET signal, respectively. (E) Relationship between in vitro percent gene expression and hemolysis at pH 5.5. (+) and (−) indicate hemolysis greater or less than 10% (after normalization to the negative control).

Fig. 4.

(A) Correlation between the extracellular FRET signal after 2 h of incubation in serum containing media and LNP pKa. (B) Correlation between cell uptake of LNPs after 2 h incubation in serum containing media and LNP pKa. (C) Correlation between LNP-mediated cell hemolysis at pH 5.5 and LNP pKa. (D) Correlation between LNP pKa and in vitro gene expression after transfection with 25 ng siRNA. LNPs that give better than 50% knockdown in vivo are highlighted in blue. Vertical error bars represent SD, n = 6.

Fig. 5.

A heat-map representation of the physicochemical properties and cellular functions of the LNP library from Fig. 1B plotted against their in vivo gene expression (black line) after administration of a 1 mg siRNA per kilogram dose. The color gradient assignment for each parameter is as follows; entrapment (light orange < 40%, orange = 40–80%, red > 80%); pKa (light orange < 4, orange = 4–6, red > 6); extracellular stability (light orange < 1.6, orange = 1.6–2.1, red > 2.1); Log₁₀ uptake (red > 4.9, light orange < 4.9) au, intracellular stability (red > 0, light orange ≤ 0) au, hemolysis at pH 5.5 (light orange < 33.3%, orange = 33.3–66.7%, red > 66.7%), in vitro gene expression (red > 50%, light orange < 50%).