Quantitative Visualization of Lipid Nanoparticle Fusion as a Function of Formulation and Process Parameters.

Lipid nanoparticles (LNPs) have proven to be promising delivery vehicles for RNA-based vaccines and therapeutics, particularly in LNP formulations containing ionizable cationic lipids that undergo protonation/deprotonation in response to buffer pH changes. These nanoparticles are typically formulated using a rapid mixing technique at low pH, followed by a return to physiological pH that triggers LNP-LNP fusion. A detailed understanding of these dynamic processes is crucial to optimize the overall performance and efficiency of LNPs. However, knowledge gaps persist regarding how particle formation mechanisms impact drug loading and delivery functions. In this work, we employ single-molecule Convex Lens-induced Confinement (CLiC) microscopy in combination with Förster resonance energy transfer (FRET) measurements to study LNP fusion dynamics in relation to various formulation parameters, including lipid concentration, buffer conditions, drug loading ratio, PEG-lipid concentrations, and ionizable lipid selection. Our results reveal a strong correlation between the measured fusion dynamics and the formulation parameters used; these findings are consistent with DLS and Cryo-TEM-based assays. These measurements offer a cost-effective method for characterizing and screening potential drug candidates and can provide additional insights into their design, with opportunities for optimization.