Mehdizadeh Hamidreza, Lauri David, Karry Krizia M, Moshgbar Mojgan, Procopio-Melino Renee, Drapeau Denis
Advanced Manufacturing Technology, Pfizer Inc., Peapack, NJ.
Bioprocess R&D, Pfizer Inc., Andover, MA.
Biotechnol Prog. 2015 Jul-Aug;31(4):1004-13. doi: 10.1002/btpr.2079. Epub 2015 Apr 18.
Raman-based multivariate calibration models have been developed for real-time in situ monitoring of multiple process parameters within cell culture bioreactors. Developed models are generic, in the sense that they are applicable to various products, media, and cell lines based on Chinese Hamster Ovarian (CHO) host cells, and are scalable to large pilot and manufacturing scales. Several batches using different CHO-based cell lines and corresponding proprietary media and process conditions have been used to generate calibration datasets, and models have been validated using independent datasets from separate batch runs. All models have been validated to be generic and capable of predicting process parameters with acceptable accuracy. The developed models allow monitoring multiple key bioprocess metabolic variables, and hence can be utilized as an important enabling tool for Quality by Design approaches which are strongly supported by the U.S. Food and Drug Administration.
基于拉曼光谱的多变量校准模型已被开发出来,用于细胞培养生物反应器内多个过程参数的实时原位监测。所开发的模型具有通用性,因为它们适用于基于中国仓鼠卵巢(CHO)宿主细胞的各种产品、培养基和细胞系,并且可以扩展到大型中试和生产规模。使用不同的基于CHO的细胞系以及相应的专有培养基和工艺条件的几个批次已被用于生成校准数据集,并且模型已使用来自单独批次运行的独立数据集进行了验证。所有模型都已被验证具有通用性,并且能够以可接受的准确度预测过程参数。所开发的模型允许监测多个关键生物过程代谢变量,因此可以用作质量源于设计方法的重要支持工具,该方法得到了美国食品药品监督管理局的大力支持。