Oceanside Pharma Technical Development, Genentech, Inc, 1 Antibody Way, Oceanside, California 92056, USA.
Biotechnol Bioeng. 2013 Jan;110(1):191-205. doi: 10.1002/bit.24602. Epub 2012 Sep 1.
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.
目前大规模哺乳动物细胞培养的工业实践通常采用标准平台分批补料工艺，采用固定体积的批量进料。虽然这种工艺被广泛应用，但它无法响应培养物的实际营养消耗需求，这可能导致副产物积累和某些营养物质耗尽。本工作展示了全自动细胞培养控制、监测和数据处理系统的应用，通过动态进料和培养基优化实现了显著的生产力提高。两种不同的进料算法用于动态改变进料速率。第一种方法基于在线电容测量，根据从集成电容估计的生长和营养消耗速率来进料。第二种方法基于从 Nova Bioprofile FLEX®自动进样器获得的自动葡萄糖测量，根据目标葡萄糖水平来进料，从而根据化学计量比维持其他营养物质。所有计算都是通过与 Delta V 过程控制系统的内部集成自动完成的。通过培养基和进料策略的优化，细胞系 A 的原始平台滴度从 5 增加到 6.3 g/L，细胞系 B 的滴度从 4 大幅增加到 9 g/L 以上，同时保持了类似的产品质量。葡萄糖被发现是最佳的进料指示剂，但并非所有细胞系都受益于动态进料，优化的进料培养基对工艺改进至关重要。我们的工作表明，动态进料能够根据培养物的行为自动调整进料速率，其优势在早期和快速的工艺开发阶段最为明显，在这些阶段，不同的细胞系或培养条件的较大变化可能导致截然不同的营养需求。
