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Accelerating ScienceAnalyteGuru / Liquid Chromatography / Understand Your Lipid Nanoparticle Composition with a Universal Detector

Understand Your Lipid Nanoparticle Composition with a Universal Detector

By Yi Zhang, 03.23.2022

The role of lipid nanoparticles

Lipid nanoparticles (LNP) play a key role in mRNA-based vaccine and therapeutics. LNPs encapsulate mRNAs, protecting them from degradation before the uptake by target cells or tissues. The identification, ratio and purity of the lipid components in LNP formulation are regarded as critical quality attributes (CQAs) for safety and efficacy, and thus must be accurately monitored.

Why do you need a charged aerosol detector?

Traditional UV detection can’t be used, as lipids have no chromophore. A charged aerosol detector (CAD) generates uniform signal response for any non- or semi-volatile compound, making it an ideal system for LNP compositional analysis. CAD also is more sensitive than alternative lipid detection systems, such as refractive index or evaporative light scattering detectors (ELSD). Over the past few years, charged aerosol detection has been adopted as the standard technology for COVID-19 vaccine release assays at both Moderna and Pfizer/BioNTech.

Sissi White, senior product applications specialist at Thermo Fisher Scientific, recently developed a simple UHPLC-CAD method for the characterization and quantification of lipid components of LNP formulations.

With the method:

  • Baseline separation was achieved for lipids and their impurities within 10 minutes, using a Thermo Scientific™ Accucore™ C30 column on a Thermo Scientific™ Vanquish™ Flex UHPLC system.
  • Sensitive and reproducible detection was obtained for all lipids, including cholesterol, with detection limits at ~10 ug/mL, using a Vanquish charged aerosol detector.

Figure 3. Overlaid chromatograms of calibration standards using the FA method

Download the application note to learn more.

Visit our new vaccine webpages to discover a full suite of analytical solutions for vaccine characterization.

Yi Zhang

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