(T1330-01-05) Optimizing Lipid Nanoparticles (LNPs) Processing for siRNA Delivery by Microfluidics System

Purpose: The success of mRNA vaccines during the COVID-19 pandemic has greatly accelerated the development of nucleic acid delivery. In addition to mRNA therapy, interfering RNA technology could be used to treat many diseases that cannot be targeted by small molecules.^1,2 However, the successful application of RNAi technology in pharmaceutical applications depends on developing efficient and targeted delivery systems. Nanoparticles, particularly lipid nanoparticles (LNPs) fabricated by microfluidics, have emerged as a promising platform for RNAi.^3-5 In this study, we aimed to explore and optimize the formulation of LNPs for short interfering RNA (siRNA) delivery, leveraging a microfluidics system with a flow-focusing approach. As new findings arise in this breakthrough technology, it is increasingly important to rely on robust preparation methods to tune the physicochemical and compositional aspects of LNPs to better deliver this nuanced cargo.

Methods: To prepare siRNA-LNP, a microfluidics device was used. Briefly, the lipids, including 1,2-dioleoyl-3-trimethylammonium-propane chloride salt (DOTAP), 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC), cholesterol, and 1,2-dimyristoyl-rac-glycero-3-methoxypolyethylene glycol-2000 (DMG-PEG 2000) at the appropriate ratio were dissolved in ethanol. The siRNA (349 bps) was diluted in PBS buffer. Our investigation delves into the interplay between various critical parameters and how they impact the resultant particles: total flow rate (TFR), nitrogen-to-phosphate (N:P) ratio of lipid and RNA, depth of microfluidics channels, and concentration of lipid blends. Dialysis devices (10K MWCO) were used to remove residual solvent and non-entrapped siRNA. The particle size, polydispersity index (PDI), and zeta potential were measured using Malvern Zetasizer. The encapsulation efficiency (EE) was measured using the RiboGreen RNA quantification method. Design of experiments was employed to evaluate the relationship between pH and concentration of two buffers (PBS and sodium acetate) on the physicochemical properties of siRNA-LNPs.

Results: TFR study: The results identified an optimal flow rate of 8 mL/min, balancing the reduction in particle size with a narrow PDI, which is crucial for uniform siRNA delivery. N:P ratio study: The results showed that a 10:1 N:P ratio is ideal for maintaining particle stability and reproducibility. Notably, at lower N:P ratios, we observed challenges such as chip clogging and less desirable particle characteristics, underscoring the importance of this delicate balance in LNP formulation. Chip depth study: Our results indicated that a 100 µm chip depth size is optimal for achieving desirable particle size and polydispersity at the studied processing parameters, essential for various therapeutic applications. This parameter plays a critical role in controlling the hydrodynamic size of the LNPs, with shallower channels favoring the production of smaller particles. Lipid concentration study: The study highlighted the impact of lipid amounts on LNP properties. We determined that a 25 mg/mL lipid concentration is optimal among the parameters studied, ensuring adequate encapsulation efficiency and stability of the LNPs while avoiding issues like increased turbidity and chip clogging. Effects of pH and concentration of PBS buffer: With decreasing concentration, both zeta potential and EE significantly increased. The result also indicated that the zeta potential contributes to the overall charge balance and surface interaction, affecting the encapsulation process. Effects of pH and concentration of sodium acetate buffer: The pH in the range of 3.5~5.5 and the concentration in the range of 5~40 mM were not significant factors affecting the physicochemical properties of siRNA-LNPs.

Conclusion: Overall, this study represents a significant step forward in understanding the process impacts on the physicochemical characteristics of RNA-based therapeutics. By establishing these parameters, we have provided an understanding of developing effective nucleic acid delivery systems. Future research will extend these findings, exploring commercially available materials to enhance LNP versatility and applicability in various contexts.

References: (1) Kulkarni, J. A.; Witzigmann, D.; Thomson, S. B.; Chen, S.; Leavitt, B. R.; Cullis, P. R.; van der Meel, R. The Current Landscape of Nucleic Acid Therapeutics. Nat. Nanotechnol. 2021, 16, 630−643.
(2) Huang, X.; Kong, N.; Zhang, X.; Cao, Y.; Langer, R.; Tao, W. The Landscape of mRNA Nanomedicine. Nat. Med. 2022, 28, 2273−2287.
(3) Hu, B.; Zhong, L.; Weng, Y.; Peng, L.; Huang, Y.; Zhao, Y.; Liang, X. J. Therapeutic siRNA: State of the Art. Signal Transduct. Target. Ther. 2020, 5, 101.
(4) Kulkarni, J. A.; Witzigmann, D.; Leung, J.; Tam, Y. Y. C.; Cullis, P. R. On the Role of Helper Lipids in Lipid Nanoparticle Formulations of siRNA. Nanoscale 2019, 11, 21733−21739.
(5) Chen, S.; Tam, Y. Y. C.; Lin, P. J. C.; Sung, M. M. H.; Tam, Y. K.; Cullis, P. R. Influence of Particle Size on the in vivo Potency of Lipid Nanoparticle Formulations of siRNA. J. Controlled Release 2016, 235, 236−244.

Acknowledgements: Declaration of competing interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported.

Fifgure 1. Effect of TFR(A), N/P ratio (B), chip depth (C), and lipid component concentration (D) on particle size, PDI, zeta potential, and appearance of siRNA-LNPs.

Figure 2. Surface response plots showing the effect of pH and concentration of PBS buffer on particle size (A), PDI (B), zeta potential (C), and encapsulation efficiency (D) of siRNA-LNPs

Figure 3. Surface response plots showing the effect of pH and concentration of sodium acetate buffer on particle size (A), PDI (B), zeta potential (C), and encapsulation efficiency (D) of siRNA-LNPs