Quick generation of R aman spectroscopy based in‐process glucose control to influence biopharmaceutical protein product quality during mammalian cell culture

Mitigating risks to biotherapeutic protein production processes and products has driven the development of targeted process analytical technology (PAT); however implementing PAT during development without significantly increasing program timelines can be difficult. The development of a monoclonal antibody expressed in a Chinese hamster ovary (CHO) cell line via fed-batch processing presented an opportunity to demonstrate capabilities of altering percent glycated protein product. Glycation is caused by pseudo-first order, non-enzymatic reaction of a reducing sugar with an amino group. Glucose is the highest concentration reducing sugar in the chemically defined media (CDM), thus a strategy controlling glucose in the production bioreactor was developed utilizing Raman spectroscopy for feedback control. Raman regions for glucose were determined by spiking studies in water and CDM. Calibration spectra were collected during 8 bench scale batches designed to capture a wide glucose concentration space. Finally, a PLS model capable of translating Raman spectra to glucose concentration was built using the calibration spectra and spiking study regions. Bolus feeding in mammalian cell culture results in wide glucose concentration ranges. Here we describe the development of process automation enabling glucose setpoint control. Glucose-free nutrient feed was fed daily, however glucose stock solution was fed as needed according to online Raman measurements. Two feedback control conditions were executed where glucose was controlled at constant low concentration or decreased stepwise throughout. Glycation was reduced from ∼9% to 4% using a low target concentration but was not reduced in the stepwise condition as compared to the historical bolus glucose feeding regimen.