Application Note: Raman-based nutrient control in bioprocessing optimizes viable cell density and protein glycation
Production of protein therapeutics by mammalian cells is the most widely used bioprocess because of its ability to properly produce and fold a recombinant protein…
60-70% of biopharmaceuticals are produced by this bioprocess. Bioreactor parameters affect cell metabolic processes and detailed bioreactor knowledge is needed to achieve a balanced and consistent metabolic state of cultured cells.
Critical process parameters in bioprocessing include pH, dissolved oxygen (DO), temperature and agitation rate. Glucose is a critical process parameter because it affects the cell’s metabolic profile, production of waste products and post-translational non-enzymatic glycation of proteins. Glycation can also lead to generation of advanced glycation end products, which results in binding inhibition, loss of therapeutic function and, in some cases, can generate an unwanted immunogenic response. Glycation can be minimised through careful control of glucose concentration in the process. Recent research has shown that online measurements of glucose can optimise fed-batch strategies to improve cell density and titer, and increase process robustness. Continuous glucose measurements offer important bioprocess information for process understanding and enables feedback control feed conditions from process development (PD) to manufacturing.
The study by Berry et al. describes rapid generation of Raman spectroscopy for feedback control of a CHO cell bioprocess where glycation of the monoclonal antibody (mAb) was identified as a critical quality attribute. This note describes a Raman method to enable automatic glucose setpoint control strategies in order to minimise unwanted glycation of the mAb. More specifically, it describes an online feedback control system for glucose concentration based on continuous in situ Raman spectral analysis.
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