Targeted LC-MS/MS detection of lipid impurities in lipid nanoparticles

Importance of Topic

Lipid nanoparticles (LNPs) emerged as a pivotal delivery system for mRNA vaccines during the COVID-19 pandemic. Their stability and efficacy depend on lipid integrity, as lipid oxidation can inactivate encapsulated mRNA. Rigorous monitoring of lipid purity is therefore essential in formulation development and quality control to ensure vaccine potency and safety.

Objectives and Study Overview

This work presents a targeted HPLC-MS/MS workflow to detect lipid-related impurities in LNP formulations without requiring reference impurities. The approach covers method optimization, impurity screening in raw materials, quantification of major lipids, and stability monitoring of formulated LNP batches.

Methodology and Instrumentation

• Sample preparation used the Cayman LNP-0315 kit, containing cholesterol, DSPC, PEG-lipid ALC-0159, and ionizable lipid ALC-0315. Stearic acid standard addressed DSPC hydrolysis products.
• Formulation employed the KNAUER IJM NanoScaler with turbulent mixing at 6 ml/min and an organic/aqueous ratio of 1:3; LNPs were diluted to 10 % ethanol before analysis.
• Chromatography used a phenyl-hexyl UHPLC column and a methanol/acetonitrile gradient with 5 mM ammonium acetate modifier.
• Mass spectrometry detection applied scheduled MRM transitions in both positive and negative electrospray modes to capture parent lipids and expected degradation products.

Used Instrumentation

• KNAUER AZURA HPLC system (Pumps, Autosampler, Column Thermostat)
• Phenomenex Kinetex® 1.7 µm phenyl-hexyl column (2.1 × 50 mm)
• Sciex Triple Quad™ 5500+ mass spectrometer
• Software: ClarityChrom® 9.0 for LC control; SCIEX OS 3.1 for MS operation

Main Results and Discussion

Major lipids—cholesterol, DSPC, ALC-0159, and ALC-0315—were baseline-separated within a 10-minute gradient and calibrated over relevant concentration ranges (R²>0.99). Targeted MRM allowed identification of ALC-0315 N-oxide, acyl losses, head-group cleavage, carboxylated species, and DSPC hydrolysis products. Recovery of lipids in three LNP lots ranged from 70 % to 90 %. Relative impurity levels remained constant across empty and RNA-loaded formulations, indicating no artifact from mixing. A short‐term stability study showed a pronounced increase of ALC-0315 N-oxide at room temperature, especially in RNA-loaded LNPs.

Benefits and Practical Applications

This HPLC-MS/MS protocol enables simultaneous quantification of major lipids and surveillance of diverse impurity classes without individual standards. High retention time precision supports routine QC in vaccine and therapeutic LNP manufacturing. The method can flag oxidative or hydrolytic degradation early and guide raw‐material screening.

Future Trends and Potential Uses

Expanding impurity libraries to cover novel lipid excipients, integrating real-time LC-MS monitoring in process analytical technology (PAT) workflows, and automating data evaluation with machine learning could further streamline LNP quality assurance. Adapting the method to emerging lipid chemistries and scaling to high‐throughput formats will broaden its applicability.

Conclusion

A comprehensive HPLC-MS/MS approach was developed for precise detection and relative quantification of lipid impurities in LNP formulations. It addresses the need for robust lipid quality control in mRNA vaccine production, offering flexibility to detect known and unforeseen degradation products. Stability data highlight the importance of storage conditions to limit oxidative pathways.

Reference

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