Integration of high‐throughput analytics and cell imaging enables direct early productivity and product quality assessment during Chinese Hamster ovary cell line development for a complex multi‐subunit vaccine antigen. (6th November 2019) - Li, Xiangming; Zhang, Yujian; Jing, Li; Fu, Zongming; Ma, Ou; Ganguly, Jishna; Vaidya, Nilesh; Sisson, Richard; Naginskaya, Jennifer; Chinthala, Avinash; Cui, Minggang; Yamagata, Ryan; et al.
Abstract: Mammalian cell line generation typically includes stable pool generation, single cell cloning and several rounds of clone selection based on cell growth, productivity and product quality criteria. Individual clone expansion and phenotype‐based ranking is performed initially for hundreds or thousands of mini‐scale cultures, representing the major operational challenge during cell line development. Automated cell culture and analytics systems have been developed to enable high complexity clone selection workflows; while ensuring traceability, safety, and quality of cell lines intended for biopharmaceutical applications. Here we show that comprehensive and quantitative assessment of cell growth, productivity, and product quality attributes are feasible at the 200–1, 200 cell colony stage, within 14 days of the single cell cloning in static 96‐well plate culture. The early cell line characterization performed prior to the clone expansion in suspension culture can be used for a single‐step, direct selection of high quality clones. Such clones were comparable, both in terms of productivity and critical quality attributes (CQAs), to the top‐ranked clones identified using an established iterative clone screening approach. Using a complex, multi‐subunit antigen as a model protein, we observed stable CQA profiles independently of the cell culture format during the clonal expansion as well as in the batch and fed‐batch processes. In conclusion, we propose an accelerated clone selection approach that can be readily incorporated into various cell line development workstreams, leading to significant reduction of the project timelines and resource requirements.