Multi-detector frit-inlet asymmetric flow field-flow fractionation method development for nanoparticle mixtures:...

Area of Science:

• Nanomedicine and Drug Delivery
• Analytical Chemistry
• Biotechnology

Background:

• Lipid-based nanoparticles (LNPs) are vital for novel therapeutics, including gene therapies and mRNA vaccines.
• Standardized analytical methods are essential for LNP quality control and regulatory approval.
• Physicochemical characterization of LNPs is critical for their successful transition from research to clinical application.

Purpose of the Study:

• To develop and validate a robust protocol for the physicochemical analysis of LNPs using Frit-Inlet Asymmetric Flow Field-Flow Fractionation (FI-AF4).
• To characterize LNP size, morphology, and polydispersity in the presence of biological media.
• To evaluate the suitability of different Multi-Angle Light Scattering (MALS) fit models for LNP sub-populations.

Main Methods:

• A Frit-Inlet Asymmetric Flow Field-Flow Fractionation (FI-AF4) method was developed for separating Lipid-based nanoparticles (LNPs).
• Online detectors including Ultraviolet (UV), Multi-Angle Light Scattering (MALS), and Dynamic Light Scattering (DLS) were coupled with FI-AF4.
• Preliminary particle size and polydispersity were assessed using DLS and Nanoparticle Tracking Analysis (NTA) to guide method development.

Main Results:

• The FI-AF4-UV-MALS-DLS technique successfully separated LNPs from protein-containing media (bovine serum albumin).
• Simultaneous online analysis revealed distinct LNP sub-populations not detectable by other methods.
• Analysis of particle morphology showed significant differences across subpopulations, with coated sphere and random coil models providing the best fit (R² > 0.95).

Conclusions:

• The developed FI-AF4-UV-MALS-DLS protocol offers a robust and versatile method for LNP physicochemical characterization.
• This method enables detailed analysis of LNP attributes, including size and morphology, supporting quality control and regulatory compliance.
• Implementing this protocol aids in generating reliable data essential for LNP drug development from bench-to-bedside.