Protein glycosylation can impact the efficacy and safety of biotherapeutics and therefore needs to be well characterized and monitored throughout the drug product life cycle. Glycosylation is commonly assessed by fluorescent labeling of released glycans, which provides comprehensive information of the glycoprofile but can be resource-intensive regarding sample preparation, data acquisition, and data analysis. In this work, we evaluate a comprehensive solution from sample preparation to data reporting using a liquid chromatography–mass spectrometry (LC-MS)-based analytical platform for increased productivity in released glycan analysis. To minimize user intervention and improve assay robustness, a robotic liquid handling platform was used to automate the release and labeling of N-glycans within 2 h. To further increase the throughput, a 5 min method was developed on a liquid chromatography–fluorescence–mass spectrometry (LC-FLR-MS) system using an integrated glycan library based on retention time and accurate mass. The optimized method was then applied to 48 released glycan samples derived from six batches of infliximab to mimic comparability testing encountered in the development of biopharmaceuticals. Consistent relative abundance of critical species such as high mannose and sialylated glycans was obtained for samples within the same batch (mean percent relative standard deviation [RSD] = 5.3%) with data being acquired, processed, and reported in an automated manner. The data acquisition and analysis of the 48 samples were completed within 6 h, which represents a 90% improvement in throughput compared with conventional LC-FLR-based methods. Together, this workflow facilitates the rapid screening of glycans, which can be deployed at various stages of drug development such as process optimization, bioreactor monitoring, and clone selections, where high-throughput and improved productivity are particularly desired.

N-Glycan analysis is routinely performed for biotherapeutic protein characterization. A recently introduced N-glycan analysis kit using RapiFluor-MS (RFMS) labeling provides time savings over reductive amination labeling methods while also providing enhanced fluorescence (FLR) and mass spectrometry (MS) responses. This article demonstrates the semiautomation of this kit using an Andrew Alliance pipetting robot that promises further gains in productivity. This robotic platform uses standard manual pipettors and an optically guided arm to facilitate the automation of manual procedures. The manual RFMS protocol includes two heating and cooling steps during protein denaturation and de-N-glycosylation. However, the current Andrew Alliance automated platform cannot move reaction tubes to and from different heating blocks. As a result, samples prepared using the automated procedure remain in a computer-controlled Peltier effect heating block, requiring reoptimization of denaturation and de-N-glycosylation temperatures. Using hydrophilic interaction liquid chromatography to monitor the RFMS-labeled glycan profiles, the authors demonstrated the reproducibility of the automated protocol with percent relative standard deviations (RSDs) of 9%–19% for the total area and 0.8%–20% for the relative areas of major and minor glycoforms. Overall, the automated platform presented here proves to be a convenient and reliable solution for N-glycan preparation and analysis.