CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 先进机器人
Operation condition design based on the qualitative and quantitative analysis for glycosylation reactions
Yuhan Nan; Jing Wang; Jinlin Zhou; Long Cheng
2017
Conference Name36th Chinese Control Conference (CCC)
Conference DateJUL 26-28, 2017
Conference PlaceDalian
CountryChina
AbstractGlycosylation reactions play a significant role on the targeted therapy of monoclonal antibody drug. In this paper, a new method implemented by combination of qualitative analysis and quantitative analysis is introduced to optimize the operating conditions of glycosylation reaction output. First, gain matrix based on ANOVA design is presented to evaluate the relationship between reaction output (different glycan classes) and system input (glycosylation enzymes). Due to the high dimension and high nonlinearity of glycosylation reactions, the singular value decomposition of process gain matrix is adopted to qualitatively analyze the effect of glycosylation enzymes in order to find the appropriate operation variables. Furthermore, genetic algorithm is used to quantitatively optimize the operation conditions for desired target of monoclonal antibody drug. The quantitative operation conditions are consistent with the reaction mechanism and qualitative analysis results of process gain.
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/23124
Collection复杂系统管理与控制国家重点实验室_先进机器人
Recommended Citation
GB/T 7714
Yuhan Nan,Jing Wang,Jinlin Zhou,et al. Operation condition design based on the qualitative and quantitative analysis for glycosylation reactions[C],2017.
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