Characterizing and Monitoring Impurities in Lipid Nanoparticle Components Using the BioAccord™ LC-MS System with waters_connect™ Software

Importance of the Topic

Lipid nanoparticles (LNPs) are essential carriers for nucleic-acid therapeutics and vaccines. Ensuring the safety and efficacy of these formulations requires rigorous identification and monitoring of trace impurities in lipid raw materials and final LNP compositions. Advanced analytical workflows that combine sensitive detection with confident structural confirmation can streamline development and quality control.

Objectives and Study Overview

This study demonstrates how the BioAccord LC-MS System paired with the waters_connect informatics platform and UNIFI App can be employed to:

• Detect low-level impurities in lipid raw materials and formulated LNPs
• Use data-independent MSE acquisition and in silico fragmentation tools for rapid structural identification
• Implement a unified workflow for both screening and routine monitoring

Methodology and Used Instrumentation

A benchtop Time-of-Flight LC-MS setup was used under the following conditions:

• Liquid chromatography: ACQUITY Premier Binary Solvent Manager, ACQUITY Premier CSH Phenyl-Hexyl column (1.7 µm, 2.1 × 50 mm), 50 °C column, 8 °C autosampler, gradient of 0.1% formic acid in water and acetonitrile, 0.4 mL/min flow, 3 µL injection
• Mass spectrometry: BioAccord with ESI+ mode, 50–2000 m/z range, 1.5 kV capillary voltage, 30 V cone, 100–150 V fragmentation ramp, 350 °C desolvation
• Informatics: waters_connect platform with UNIFI App for MSE processing, in silico fragmentation, compound screening and transformation searches

Main Results and Discussion

• In Silico Fragmentation Matching: Known lipid structures (.mol files) were imported into the UNIFI library. Enabling predicted fragment generation allowed automatic mapping of experimental high-energy ions to structural fragments for SM-102 and cholesterol.

• Raw Material Screening: Dlin-MC3-DMA samples revealed multiple impurity peaks. A set of common transformations (oxidation, reduction, desaturation) was specified in the processing method. Accurate mass matching of precursor and fragment ions enabled annotation of these impurities.

• Localization of Oxidation: By comparing experimental fragments with two candidate oxidation structures (amine vs. double-bond epoxide), key fragment ions confirmed that oxidation occurred on the primary amine headgroup.

• Compositional Impurity Monitoring: A four-lipid mixture spiked with 0.1% DOTMA was analyzed. Item-tagging of known components and impurities allowed reliable detection and tracking of the low-level DOTMA peak across samples.

Benefits and Practical Applications

• Integrated acquisition and analysis workflow reduces manual interpretation time
• High sensitivity and accurate mass data enable detection of impurities at trace levels
• Benchtop MS design and SmartMS automation extend MS capabilities to non-expert and resource-limited labs
• Methods and item tags can be migrated to downstream workflows (single quadrupole MS, ELSD) for routine QC

Future Trends and Potential Uses

• Wider adoption of compact LC-MS platforms in manufacturing and QC environments for real-time impurity monitoring
• Expansion of in silico fragmentation libraries to cover novel lipid modifications and degradants
• Integration with laboratory information management systems for automated data review and reporting
• Application to other nanoparticle and lipid-based drug delivery systems beyond mRNA vaccines

Conclusion

The BioAccord LC-MS System combined with waters_connect and UNIFI App offers a streamlined, sensitive, and confident approach to characterize and monitor impurities in lipid nanoparticle raw materials and formulations. Data-independent MSE acquisition and in silico fragmentation accelerate structural elucidation, while item tagging supports routine tracking of known contaminants. This workflow enhances the robustness of LNP development and quality control processes.

References

• Isaac G et al. Rapid Analysis of Lipid Nanoparticle Components Using BioAccord LC-MS System. Waters Application Note 720007296, June 2021.
• Han D et al. Lipid Nanoparticle Analysis: Leveraging MS to Reduce Risk. Waters Application Note 720007716, Sept 2022.
• DeLaney K et al. Optimized ELSD Workflow for Improved Detection of Lipid Nanoparticle Components. Waters Application Note 720007740, Oct 2022.