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Updated: Dec 20, 2025

A Quantitative Glycomics and Proteomics Combined Purification Strategy
Published on: March 8, 2016
High-Throughput Analysis of Fluorescently Labeled N-Glycans Derived from Biotherapeutics Using an Automated
Ximo Zhang1, Corey E Reed1, Robert E Birdsall1
1Scientific Operations, Waters Corporation, Milford, MA, USA.
Automated N-glycan analysis using liquid chromatography-mass spectrometry (LC-MS) significantly boosts biotherapeutic development productivity. This high-throughput workflow streamlines glycan characterization, improving efficiency by 90% for critical drug quality assessments.
Area of Science:
- Biopharmaceutical Analysis
- Analytical Chemistry
- Glycobiology
Background:
- Protein glycosylation is critical for biotherapeutic efficacy and safety, necessitating robust monitoring throughout drug development.
- Traditional glycan analysis methods are often resource-intensive, limiting throughput and efficiency in characterizing glycoprofiles.
- Developing faster, more automated analytical platforms is crucial for timely biopharmaceutical characterization.
Purpose of the Study:
- To evaluate a comprehensive, automated liquid chromatography-mass spectrometry (LC-MS) platform for high-throughput released glycan analysis.
- To develop and optimize a rapid (5-minute) LC-FLR-MS method for N-glycan profiling.
- To demonstrate the platform's utility in biopharmaceutical comparability testing using infliximab samples.
Main Methods:
- Automated N-glycan release and fluorescent labeling using a robotic liquid handling system (2-hour process).
- Development of a 5-minute LC-FLR-MS method incorporating an integrated glycan library for identification.
- Application of the optimized workflow to analyze 48 released glycan samples from six infliximab batches.
Main Results:
- The automated workflow achieved N-glycan release and labeling in under 2 hours, minimizing user intervention.
- The 5-minute LC-FLR-MS method provided consistent relative abundance of critical glycan species (e.g., high mannose, sialylated glycans) with a mean %RSD of 5.3%.
- Data acquisition, processing, and reporting for 48 samples were completed within 6 hours, a 90% throughput improvement over conventional methods.
Conclusions:
- The developed comprehensive LC-MS workflow significantly enhances productivity and throughput for released glycan analysis.
- This automated, rapid glycan screening approach is suitable for various biopharmaceutical development stages, including process optimization and clone selection.
- The platform offers a robust solution for efficient and reliable glycan characterization, crucial for biotherapeutic quality control.
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