Improving Routine Analysis of Insulin Analogues Using the ACQUITY QDa Detector

Importance of the Topic

The analysis of insulin analogues is essential in biopharmaceutical QC to ensure accurate identification, purity assessment and biosimilar comparability of these closely related proteins.

Study Objectives and Overview

This study demonstrates an LC-UV/MS workflow using the ACQUITY QDa Detector to improve routine analysis of insulin analogues, focusing on purity, comparability and identity testing across multiple commercial samples.

Methodology

An optimized UPLC method was developed for intact insulin analysis and peptide mapping following USP monograph protocols with modifications for MS compatibility. Intact proteins (0.35 mg/mL) were separated on a CSH C18 column at 60 °C, using a 20 min gradient (20–30% B) with 0.1% formic acid in water (A) and acetonitrile (B). Digestion for peptide mapping employed Glu-C at 37 °C, with a scaled 15 min gradient on a peptide column.

Used Instrumentation

• ACQUITY UPLC H-Class Bio System with TUV Detector (λ=215 nm)
• ACQUITY QDa Detector (ESI+, 350–1250 m/z, probe temp. 500 °C)
• ACQUITY UPLC CSH C18 Column, 1.7 µm, 2.1×100 mm
• Empower 3 Software for data acquisition

Results and Discussion

Impurity assessment by intact analysis showed improved resolution of insulin and m-cresol, with up to 8-fold higher SNR for low-abundance impurities using MS detection versus UV. Comparability testing of three insulin sources revealed identical retention but distinct molecular weights (5808 Da vs. 5823 Da) and differing impurity profiles, highlighting MS specificity. Peptide mapping identified characteristic fragments (F1–F4); sequence variants in Sample 3 (N→K, KT→E) altered retention and confirmed by mass shifts, supporting molecular-level identity testing.

Benefits and Practical Applications

• Enhanced sensitivity and specificity for impurity and identity assessment
• Cost-effective integration of MS into existing LC-UV workflows
• Streamlined QC in regulated environments
• Improved confidence in biosimilar comparability and drug batch consistency

Future Trends and Applications

Further integration of low-cost MS detectors in routine QC, automation of LC-MS workflows, expansion to other biotherapeutics and incorporation of advanced data analysis and real-time monitoring are expected to advance biopharma analytics.

Conclusion

The ACQUITY QDa Detector combined with UPLC provides a robust, efficient and regulatory-ready workflow for enhanced analysis of insulin analogues, improving detection of impurities, ensuring accurate identity tests and supporting biosimilar comparability in quality control.

References

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