LIPID NANOPARTICLES — GET TO KNOW THEM ANALYTICALLY

Importance of the Topic

Lipid nanoparticles (LNPs) are at the heart of modern mRNA vaccine delivery strategies, providing a safe and efficient vehicle for genetic material. Detailed analytical profiling of their lipid composition and potential impurities is essential to ensure consistent performance and regulatory compliance.

Objectives and Study Overview

This study aimed to develop a rapid, sensitive LC-MS workflow to identify and quantify the four core lipids in LNP formulations, detect degradants and trace impurities, and evaluate lot-to-lot or supplier-related variations in raw materials.

Methodology and Instrumentation

The BioAccord LC-MS platform combined high-resolution chromatography with mass detection to achieve comprehensive lipid profiling.

• Chromatography: ACQUITY UPLC I-Class with a CSH C18 column and a binary gradient of acetonitrile, isopropanol and formate buffer.
• Mass spectrometry: ACQUITY RDa detector in positive ESI mode, scanning m/z 50–2000 with optimized cone and fragmentation voltages.
• Data processing: UNIFI Scientific Information System with a custom lipid library for accurate mass screening and spectral matching.

Results and Discussion

• Single lipid detection: Each standard lipid (MC3, DSPC, DMG-PEG-2000 and cholesterol) was resolved and identified with high mass accuracy.
• Low-level sensitivity: Limits of detection were 5 pg/µL for MC3, DSPC and DMG-PEG-2000, and 250 pg/µL for cholesterol, demonstrating robust trace analysis capability.
• Lipid complex analysis: Spiked samples revealed additional peaks corresponding to unknown impurities, confirmed by spectral difference plots and retention time alignment.
• PEGylated lipid profiling: The PEG-lipid exhibited multiple charge states and a distribution of chain lengths, underscoring the need for high-resolution MS data.

Benefits and Practical Applications

The described workflow supports quality control of LNP raw materials and final formulations by providing:

• Simultaneous identification of core components and degradants.
• Trace-level impurity detection to ensure product safety.
• A rapid method compatible with process development and regulatory testing.

Future Trends and Potential Uses

Advancements in lipidomics and MS software will enable deeper insight into nanoparticle heterogeneity, facilitate high-throughput screening of novel lipid candidates, and support machine learning algorithms for predictive quality monitoring. Integration with automated sample prep and data analytics promises to enhance throughput and standardization in biotherapeutic manufacturing.

Conclusion

The BioAccord LC-MS system delivers a fast, reliable platform for comprehensive analysis of LNP components, offering sensitivity, specificity and flexibility required for vaccine and gene therapy development.

Reference

Rapid Analysis of Lipid Nanoparticle Components Using BioAccord LC-MS System, Waters application note, 2021.