Rapid analysis of multiple parameters of CHO cell culture media using Raman spectroscopy

被引:0
|
作者
Yan X. [1 ]
Shen L.-J. [1 ]
Xu W.-Y. [2 ]
Pan H.-H. [2 ]
Nie L. [1 ]
Wang H.-B. [2 ]
Li W.-L. [1 ]
Qu H.-B. [1 ]
机构
[1] Pharmaceutical Informatics Institute, Zhejiang University, Hangzhou
[2] Zhejiang Hisun Pharmaceutical Co., Ltd., Taizhou
关键词
CHO cell culture; Monoclonal antibody; Partial least squares; Raman spectroscopy; Rapid analysis;
D O I
10.3969/j.issn.1003-9015.2019.04.013
中图分类号
学科分类号
摘要
In order to rapidly analyze Chinese hamster ovary (CHO) cell culture media, samples were collected during bioreactor runs and reference values of glucose concentration, lactate concentration, glutamate concentration, glutamine concentration, viable cell density, total cell density, cell viability and monoclonal antibody titer were obtained off-line. Raman spectra of cell culture supernatants were collected and partial least squares (PLS) was used to develop multivariate calibration models between Raman spectra and parameters. Reasonable principal component numbers, high coefficient of determination (R2), low root mean square error of calibration (RMSEC), low root mean square error of prediction (RMSEP), and slight differences between RMSEC and RMSEP were observed in each model, which demonstrates satisfactory predictive capacity of the developed models. The results show that the proposed method is expected to be used in off-line and rapid determination of multiple parameters in CHO cell culture processes, which can provide guidelines for in-line real-time monitoring and feedback control. © 2019, Editorial Board of "Journal of Chemical Engineering of Chinese Universities". All right reserved.
引用
收藏
页码:872 / 877
页数:5
相关论文
共 17 条
  • [1] Whelan J., Craven S., Glennon B., In situ Raman spectroscopy for simultaneous monitoring of multiple process parameters in mammalian cell culture bioreactors, Biotechnology Progress, 28, 5, pp. 1355-1362, (2012)
  • [2] Li B., Ryan P.W., Ray B.H., Et al., Rapid characterization and quality control of complex cell culture media solutions using Raman spectroscopy and chemometrics, Biotechnology and Bioengineering, 107, 2, pp. 290-301, (2010)
  • [3] Li B., Ray B.H., Leister K.J., Et al., Performance monitoring of a mammalian cell based bioprocess using Raman spectroscopy, Analytica Chimica Acta, 796, pp. 84-91, (2013)
  • [4] Abu-Absi N.R., Kenty B.M., Cuellar M.E., Et al., Real time monitoring of multiple parameters in mammalian cell culture bioreactors using an in-line Raman spectroscopy probe, Biotechnology and Bioengineering, 108, 5, pp. 1215-1221, (2011)
  • [5] Berry B., Moretto J., Matthews T., Et al., Cross-scale predictive modeling of CHO cell culture growth and metabolites using Raman spectroscopy and multivariate analysis, Biotechnology Progress, 31, 2, pp. 566-577, (2015)
  • [6] Mehdizadeh H., Lauri D., Karry K.M., Et al., Generic Raman-based calibration models enabling real-time monitoring of cell culture bioreactors, Biotechnology Progress, 31, 4, pp. 1004-1013, (2015)
  • [7] Matthews T.E., Berry B.N., Smelko J., Et al., Closed loop control of lactate concentration in mammalian cell culture by Raman spectroscopy leads to improved cell density, viability, and biopharmaceutical protein production, Biotechnology and Bioengineering, 113, 11, pp. 2416-2424, (2016)
  • [8] Kozma B., Hirsch E., Gergely S., Et al., On-line prediction of the glucose concentration of CHO cell cultivations by NIR and Raman spectroscopy: Comparative scalability test with a shake flask model system, Journal of Pharmaceutical and Biomedical Analysis, 145, pp. 346-355, (2017)
  • [9] Andre S., Lagresle S., Hannas Z., Et al., Mammalian cell culture monitoring using in situ spectroscopy: Is your method really optimised?, Biotechnology Progress, 33, 2, pp. 308-316, (2017)
  • [10] Andre S., Lagresle S., Da Sliva A., Et al., Developing global regression models for metabolite concentration prediction regardless of cell line, Biotechnology and Bioengineering, 114, 11, pp. 2550-2559, (2017)