Time-dependent particle size increase during lipid nanoparticle purification by cross-flow filtration

Area of Science:

• Biotechnology
• Nanotechnology
• Pharmaceutical Sciences

Background:

• Lipid nanoparticles (LNPs) are crucial for drug delivery, but scalable purification methods beyond dialysis are needed.
• Cross-flow filtration (CFF) is a time- and resource-efficient purification technique with potential for LNP processing.

Purpose of the Study:

• To investigate the impact of CFF on LNP characteristics and process performance.
• To evaluate CFF as a scalable alternative to dialysis for LNP purification.

Main Methods:

• Parameter study involving variations in membrane and operational parameters during CFF.
• Pre-dilution approach to reduce ethanol content.
• Integration of at-line dynamic light scattering (DLS) for real-time size monitoring.
• Comprehensive off-line analyses for LNP characterization.

Main Results:

• CFF processing resulted in increased LNP size and altered size distribution, dependent on processing time.
• High lipid recoveries (86-89%) were achieved, with other LNP characteristics remaining constant.
• CFF-purified LNPs exhibited reduced size increase during 14-day storage compared to dialyzed LNPs.

Conclusions:

• CFF is a viable and scalable method for LNP purification, offering high lipid recovery and improved storage stability.
• Integration of process analytical technology (PAT) with CFF enables real-time LNP size monitoring.
• Further understanding of CFF-based LNP processing can advance size-controlled LNP production.