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Lipid nanoparticle (LNP) characterization

In recent years, interest in lipid nanoparticles (LNPs) within the pharmaceutical industry has surged and been driven by promising research on their ability to act as delivery vehicles that are able to overcome the limitations of free therapeutics in the body. LNPs can efficiently package therapeutics and navigate biological barriers to safely transport and deliver their content to targeted sites at desired time points. These particles have evolved from their earliest form as liposomes to other lipid nanocarrier types that are more bioavailable and easier to manufacture, such as solid lipid nanoparticles, nanostructured lipid carriers, and cationic lipid-nucleic acid complexes. Most notably, cationic lipid-nucleic acid complexes have been used as critical components of COVID-19 vaccines as mRNA delivery vectors. These LNPs are spherical vesicles composed of ionizable cationic lipids, PEGylated lipids, cholesterol, and phospholipids. The ionizable lipids provide the LNPs the ability to respond to pH changes in the environment: protecting the nucleic acid content within the LNP encapsulant during transportation, aiding diffusion across plasma membranes into target cells, and enabling site-specific and time-specific release of the mRNA. Ongoing research continues to explore LNPs for other applications including new mRNA vaccines and therapies, DNA gene therapies, and CRISPR gene-editing therapies.

Monitoring quality at different stages of the manufacturing process with TEM

To assure the safety and efficacy of the final LNP product for therapeutic use, it is vital to monitor its quality at all stages of the manufacturing process. Transmission electron microscopy (TEM) is a valuable technique for inspecting samples to gain crucial information on the following quality parameters:

  • Overall morphology
  • Particle size distribution
  • Circularity distribution
  • Particle class distribution
  • Lamellarity
  • Membrane thickness

Classifying LNPs with cryoTEM

Cryogenic transmission electron microscopy (cryoTEM) is a technique that is particularly suited to LNP analysis. CryoTEM involves the deposition of a sample onto a thin supporting film, rapid vitrification of the sample by plunge-freezing in liquid ethane, and subsequent imaging under cryogenic conditions. The technique preserves the sample near to its native conformation, allowing for the direct visualization of the morphology (see Figure 1), size distribution, constituent LNP particle types, and product stability or aggregation state of the sample. Furthermore, the internal density of LNPs can be observed with cryoTEM, offering insight into the packaging efficiency or ratio of filled and empty particles of the sample, while an evaluation of the signal-to-noise ratio of the image background provides information on the sample’s purity.

In combination with Vironova’s proprietary software, VAS, accurate statistical data can be obtained for size distribution (see Figure 2), circularity distribution, particle class distribution (see Figure 3), lamellarity, and membrane thickness.

LNPs particle morphologies

Figure 1. cryoTEM image displaying the variation in morphology of LNPs.

Size and circularity distributions

Circularity and particle size distribution analyses respectively provide information about the shape and size of the LNPs in a sample. 

LNPs size and circularity 1

Figure 2. Representative histograms displaying the size distribution (left) and circularity distribution (right), as determined from semi-automated detection.

LNPs particle class  distribution

Figure 3.. A representative histogram (left) displaying the particle class distribution, as determined from semi-automated detection. The corresponding image (right) shows the detected and classified particles overlaid with green/blue/purple outlines.

Type 1: LNPs displaying a homogeneous high internal density
Type 2: LNPs displaying a distinct outer shell and minute internal density
Type 3: LNPs displaying a multi-compartmental feature with a heterogeneous internal density distribution
Type 4: LNPs that cannot be unambiguously classified into the above 3 classes.

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