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Process development and optimization of continuous capture with three‐column periodic counter‐current chromatography
Author(s) -
Shi Ce,
Zhang QiLei,
Jiao Biao,
Chen XuJun,
Chen Ran,
Gong Wei,
Yao ShanJing,
Lin DongQiang
Publication year - 2021
Publication title -
biotechnology and bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/bit.27689
Subject(s) - residence time (fluid dynamics) , productivity , column (typography) , chromatography , process (computing) , yield (engineering) , chemistry , process engineering , mathematics , materials science , computer science , engineering , composite material , geometry , geotechnical engineering , connection (principal bundle) , economics , macroeconomics , operating system
Continuous capture with affinity chromatography is one of the most important units for continuous manufacturing of monoclonal antibody (mAb). Due to the complexity of three‐column periodic counter‐current chromatography (3C‐PCC), three approaches (experimental, model‐based, and simplified approaches) were studied for process development and optimization. The effects of residence time for interconnected load ( RT C ), breakthrough percentage of the first column for interconnected load ( s ) and feed protein concentration ( c 0 ) on productivity and capacity utilization were focused. The model‐based approach was found superior to the experimental approach in process optimization and evaluation. Two phases of productivity were observed and the optimal RT C for the maximum productivity was located at the boundary of the two phases. The comprehensive effects of the operating parameters ( RT C , s , and c 0 ) were evaluated by the model‐based approach, and the operation space was predicted. The best performance of 34.5 g/L/h productivity and 97.6% capacity utilization were attained for MabSelect SuRe LX resin under 5 g/L concentration at RT C = 2.8 min and s = 87.5%. Moreover, a simplified approach was suggested to obtain the optimal RT C for the maximum productivity. The results demonstrated that model‐assisted tools are useful to determine the optimum conditions for 3C‐PCC continuous capture with high productivity and capacity utilization.