Glycans play a crucial role in various biological processes, including cell signalling, immune response, and protein functionality. Their structural diversity and complexity make their analysis challenging, but essential for understanding their functional importance in biology. Since they naturally lack light-emitting properties, derivatization with fluorophores is required to enable their detection and analysis. Fluorescence detection offers several advantages in glycan analysis, including higher sensitivity and the ability to detect low concentrations of analytes. In this study, I aim to develop an analytical HPLC method for glycans with fluorescence detection that allows efficient characterization and quantification of these biomolecules. Furthermore, I apply the principles of Quality by Design (QbD) to ensure robustness and reliability in the development of analytical methods.
Applying the QbD principles to the development of analytical methods enables a systematic and comprehensive approach to achieve the desired analytical performance. The QbD framework enables a proactive approach to method development that includes risk assessment, experimental design, and multivariate analysis. This approach ensures method robustness, minimizes variability and improves method understanding, ultimately leading to reliable and reproducible glycan analysis.
In the laboratory, I used solid-phase extraction (SPE) methods to purify glycan samples, eliminate interfering substances, and reduce matrix effects. By carefully selecting appropriate SPE sorbents and optimizing extraction conditions, I achieved efficient removal of excess fluorescent markers used for detection. This step is crucial as a high fluorescence background can affect the sensitivity and accuracy of glycan quantification. In addition, I implemented QbD principles throughout the method development process, which enabled thorough characterization of critical method parameters, risk assessment and identification of critical process parameters (CPPs) and critical quality attributes (CQAs).
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