GlycoWorks RapiFluor-MS Automation Using the Andrew+ Pipetting Robot

Importance of the Topic

Biopharmaceutical glycosylation patterns influence safety efficacy and process consistency and require robust analytics Rapid and reliable N-glycan profiling supports quality control and accelerates drug development

Objectives and Study Overview

This study aimed to implement and verify an automated N-glycan labeling workflow using the GlycoWorks RapiFluor-MS kit on the Andrew+ pipetting robot Performance criteria included matching manual preparations within 25 percent deviation in total signal and 5 percent in relative glycan distribution

Methodology and Instrumentation

The manual protocol was adapted to automation by replacing individual reaction tubes with SBS compliant 96-well Lo-Bind PCR plates and integrating connected heating and vacuum modules Critical steps included protein denaturation deglycosylation fluorescent labeling and HILIC cleanup During optimization consumable formats were evaluated to minimize nonspecific losses at the dilution and transfer stages
Key instrumentation

• Andrew+ pipetting robot with single and multichannel electronic pipettes
• SBS format Peltier thermo module
• Microelution HILIC µElution plate with vacuum manifold
• Domino labware carriers for tips reservoirs and plates

Key Results and Discussion

Initial automation yielded only 54 percent glycan recovery relative to manual methods while maintaining stable relative distributions The major source of loss was traced to an intermediate dilution plate By eliminating the storage transfer and performing final dilution directly within the HILIC µElution plate the recovery improved to 88 percent Relative area deviations remained below 2.6 percent and automated total area reproducibility surpassed manual pipetting

Benefits and Practical Applications

The automated workflow offers

• Significant time and labor savings
• Reduced variability and error risk
• Enhanced throughput for routine glycan analysis
• Cost efficient deployment and easy method transfer
• Relief of analytical bottlenecks in regulated laboratories

Future Trends and Applications

Advances may include integration with laboratory information systems higher sample multiplexing new fluorescent and MS responsive labels miniaturized formats and AI driven data analysis for deeper glycan profiling and quality monitoring

Conclusion

The optimized eight-sample GlycoWorks RapiFluor-MS protocol on Andrew+ achieves reproducible high yield N-glycan labeling comparable to manual methods while reducing analyst burden and instrument downtime effectively streamlining biopharma glycan analytics

References

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4. Koza S M McCall S A Lauber M A Quality Control and Automation Friendly GlycoWorks RapiFluor-MS Application Note Waters 2020
5. Reed C E Fournier J Vamvoukas N Automated Preparation of MSSensitive Fluorescently Labeled N-Glycans with a Commercial Pipetting Robot SLAS Technology Transl Life Sci Innov 2018 23 6 550–559
6. ANSI SLAS 2-2004 R2012 American National Standards Institute 2004