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

Area of Science:

• Biotechnology
• Materials Science
• Nanotechnology

Background:

• Lipid nanoparticles (LNPs) are crucial delivery systems for RNA therapeutics and vaccines.
• Ionizable cationic lipids in LNPs respond to pH changes, influencing nanoparticle behavior.
• Current LNP formulation methods lack detailed understanding of particle formation and its impact on drug delivery.

Purpose of the Study:

• To investigate the dynamic fusion processes of lipid nanoparticles (LNPs).
• To correlate LNP fusion dynamics with critical formulation parameters.
• To identify how particle formation mechanisms influence drug loading and delivery efficiency.

Main Methods:

• Utilized single-molecule Convex Lens-induced Confinement (CLiC) microscopy.
• Employed Förster resonance energy transfer (FRET) measurements to analyze LNP fusion.
• Varied formulation parameters including lipid concentration, buffer conditions, drug loading, PEG-lipid concentration, and ionizable lipid type.

Main Results:

• Demonstrated a strong correlation between LNP fusion dynamics and specific formulation parameters.
• Findings were validated using Dynamic Light Scattering (DLS) and Cryo-Transmission Electron Microscopy (Cryo-TEM).
• Identified key relationships between formulation variables and LNP fusion behavior.

Conclusions:

• Single-molecule CLiC and FRET provide a cost-effective method for LNP characterization.
• These techniques offer valuable insights for optimizing LNP design and drug candidate screening.
• Understanding fusion dynamics is critical for enhancing the performance of RNA delivery vehicles.