Raw Material Identification of mRNA Lipid Nanoparticle Components with the Agilent Vaya Raman Spectrometer

Significance of the Topic

Lipid nanoparticles (LNPs) have become indispensable carriers for nucleic-acid therapeutics, notably mRNA vaccines. Ensuring the identity and purity of raw lipid and nonlipid excipients directly influences product efficacy, stability, and safety. Rapid, non-destructive verification of these materials through their original packaging streamlines quality control and supports compliance with current Good Manufacturing Practice (cGMP).

Objectives and Study Overview

This application note evaluates the Agilent Vaya handheld Raman spectrometer—leveraging spatially offset Raman spectroscopy (SORS)—for in-container identification of key mRNA LNP components. The study demonstrates method development for four excipient categories: lipids, buffers, organic solvents, and cryoprotectants, analyzed through transparent and opaque containers without sample preparation.

Methodology and Instrumentation

The Vaya spectrometer automatically optimizes acquisition parameters once the container type is specified. Performance qualification ensured instrument readiness before data collection. Samples were analyzed in their original packaging:

• Lipids: clear glass and amber vials
• Buffers: white HDPE bottles
• Organic solvents: clear and amber glass containers
• Cryoprotectants: white HDPE bottles

Instrumentation:

• Agilent Vaya Raman raw material identity verification system
• Spatially offset Raman spectroscopy (SORS) capability for subsurface analysis

Main Results and Discussion

The Vaya system reliably distinguished all excipients through various container types. Key spectral features included:

• Lipids: CH2/CH3 deformation at ~1440 cm⁻¹; C=C stretching at ~1673 cm⁻¹; PO stretching at ~949 cm⁻¹; C=O stretching at ~1700 cm⁻¹
• Buffers: N–H bending (1500–1700 cm⁻¹) in Tris; SO₃ stretching at ~1046 cm⁻¹ in HEPES; C=O stretching at ~1700 cm⁻¹ in citric acid
• Organic Solvents: C–O stretching at ~1035 cm⁻¹ in methanol; C–C skeletal vibration at ~921 cm⁻¹ in acetonitrile; C–C stretching at ~882 cm⁻¹ and C–O stretching at ~1050 cm⁻¹ in ethanol
• Cryoprotectants: distinct sugar signatures such as torsion CH₂ and C–C stretching in sucrose; CH deformation at ~850 cm⁻¹ in maltose; C–O–C deformation at ~841 cm⁻¹ in trehalose; in-phase/out-phase C–C–O stretching at ~878/1050 cm⁻¹ in mannitol and sorbitol

Benefits and Practical Applications

Implementing the Vaya SORS system enables:

• Non-invasive raw material verification directly in quarantine areas
• Reduction of sample handling, cross-contamination risk, and testing time
• Efficient compliance with cGMP raw material identification requirements

Future Trends and Opportunities

Advancements may include:

• Integration with laboratory information management systems (LIMS) for real-time data tracking
• Extension of in-container Raman ID to other biopharmaceutical raw materials and packaging types
• Enhanced detector sensitivity and chemometric models for even more complex formulations

Conclusion

The handheld Agilent Vaya Raman spectrometer, utilizing SORS, effectively identifies diverse mRNA LNP excipients through various packaging materials. This approach simplifies raw material quality control, minimizes disruptions in the manufacturing workflow, and upholds regulatory standards.

Reference

• Bulbake, U.; Doppalapudi, S.; Kommineni, N.; Khan, W. Liposomal Formulations in Clinical Use: An Updated Review. Pharmaceutics 2017, 9(2), 12. DOI: 10.3390/pharmaceutics9020012
• Challener, C. Excipients Impact Stability in mRNA-LNP Formulations. Pharmaceutical Technology 2023, 47(3), 20–22, 32.
• Prullière, F.; Presly, O. Identifying Raw Materials Inside Containers Using a Handheld Raman Spectrometer, Agilent Technologies White Paper, Publication No. 5994-2091EN, 2020.
• Czamara, K.; Majzner, M. Z.; Pacia, K.; Kochan, A.; Baranska, M. Raman Spectroscopy of Lipids: A Review. J. Raman Spectrosc. 2015, 46(1), 4–20. DOI: 10.1002/jrs.4607