title: Automated dynamic fed-batch process and media optimization for high productivity cell culture process development.
abstract: Current industry practices for large-scale mammalian cell cultures typically employ a standard platform fed-batch process with fixed volume bolus feeding. Although widely used, these processes are unable to respond to actual nutrient consumption demands from the culture, which can result in accumulation of by-products and depletion of certain nutrients. This work demonstrates the application of a fully automated cell culture control, monitoring, and data processing system to achieve significant productivity improvement via dynamic feeding and media optimization. Two distinct feeding algorithms were used to dynamically alter feed rates. The first method is based upon on-line capacitance measurements where cultures were fed based on growth and nutrient consumption rates estimated from integrated capacitance. The second method is based upon automated glucose measurements obtained from the Nova Bioprofile FLEX® autosampler where cultures were fed to maintain a target glucose level which in turn maintained other nutrients based on a stoichiometric ratio. All of the calculations were done automatically through in-house integration with a Delta V process control system. Through both media and feed strategy optimization, a titer increase from the original platform titer of 5 to 6.3 g/L was achieved for cell line A, and a substantial titer increase of 4 to over 9 g/L was achieved for cell line B with comparable product quality. Glucose was found to be the best feed indicator, but not all cell lines benefited from dynamic feeding and optimized feed media was critical to process improvement. Our work demonstrated that dynamic feeding has the ability to automatically adjust feed rates according to culture behavior, and that the advantage can be best realized during early and rapid process development stages where different cell lines or large changes in culture conditions might lead to dramatically different nutrient demands.
authors: Oceanside Pharma Technical Development, Genentech, Inc, 1 Antibody Way, Oceanside, California 92056, USA.
authors: Franklin
authors: F
authors: Lu
authors: Poh Choo
authors: PC
authors: Toh
authors: Iain
authors: I
authors: Burnett
authors: Feng
authors: F
authors: Li
authors: Terry
authors: T
authors: Hudson
authors: Ashraf
authors: A
authors: Amanullah
authors: Jincai
authors: J
authors: Li
mesh_terms: D000465:Algorithms; D000596:Amino Acids / Q000378:metabolism; D000818:Animals; D000911:Antibodies, Monoclonal / Q000032:analysis / Q000378:metabolism; D001331:Automation / Q000379:methods*; D061249:Batch Cell Culture Techniques / Q000379:methods*; D019149:Bioreactors; D016466:CHO Cells; D006224:Cricetinae; D003470:Culture Media; D005947:Glucose / Q000378:metabolism; D019344:Lactic Acid / Q000378:metabolism
chemical_list: D000596:Amino Acids; D000911:Antibodies, Monoclonal; D003470:Culture Media; D019344:Lactic Acid; D005947:Glucose