The Implementation of Response Surface Methodology in the Optimization of Lipid Nanoparticle Preparation for Vaccine Development

Abstract

Lipid nanoparticles (LNPs) are the delivery system behind the success story of mRNA vaccines and the development of DNA and peptide vaccines. LNPs should have particle sizes ranging from 60 to 150 nm for such applications. Achieving such particle size criteria can be challenging in the LNP preparation using a micromixer system with different parameters: i.e., the N/P ratio, aqueous flow rate (AFR) and total flow rate (TFR). Such an issue can be addressed by applying response surface methodology (RSM). Therefore, in this study, we implemented RSM to optimize LNP preparation parameters, including the N/P ratio and AFR. TFR remained constant at 1 mL.min–1 since, from a previous study, it is not a critical parameter for achieving the desired LNP size. Here, we used the pDNA of ACE-2 as a dummy nucleotide. Particle sizes of the resulting LNPs were determined using a dynamic light scattering (DLS) method. Our results indicate that AFR is a significant factor in determining LNP size, whereas the N/P ratio does not have a significant impact on LNP size. We achieved an LNP size of 104.00 nm by applying the N/P ratio of 32.0000 and AFR of 0.9621 mL.min–1. Our results showed that RSM could ease the optimization process in the preparation of LNP, which may support the acceleration of vaccine development.