Interest of locally weighted regression to overcome nonlinear effects during in situ NIR monitoring of CHO cell culture parameters and antibody glycosylation.

Autor: Zavala-Ortiz DA; Laboratoire Réactions et Génie des Procédés, Université de Lorraine, CNRS, Vandœuvre-lès-Nancy, France.; Tecnológico Nacional de México, Instituto Tecnológico de Veracruz, Veracruz, Veracruz, Mexico., Ebel B; Laboratoire Réactions et Génie des Procédés, Université de Lorraine, CNRS, Vandœuvre-lès-Nancy, France., Li MY; Laboratoire Réactions et Génie des Procédés, Université de Lorraine, CNRS, Vandœuvre-lès-Nancy, France., Barradas-Dermitz DM; Tecnológico Nacional de México, Instituto Tecnológico de Veracruz, Veracruz, Veracruz, Mexico., Hayward-Jones PM; Tecnológico Nacional de México, Instituto Tecnológico de Veracruz, Veracruz, Veracruz, Mexico., Aguilar-Uscanga MG; Tecnológico Nacional de México, Instituto Tecnológico de Veracruz, Veracruz, Veracruz, Mexico., Marc A; Laboratoire Réactions et Génie des Procédés, Université de Lorraine, CNRS, Vandœuvre-lès-Nancy, France., Guedon E; Laboratoire Réactions et Génie des Procédés, Université de Lorraine, CNRS, Vandœuvre-lès-Nancy, France.
Jazyk: angličtina
Zdroj: Biotechnology progress [Biotechnol Prog] 2020 Jan; Vol. 36 (1), pp. e2924. Date of Electronic Publication: 2019 Oct 14.
DOI: 10.1002/btpr.2924
Abstrakt: Animal cell culture processes have become the standard platform to produce therapeutic proteins such as recombinant monoclonal antibodies (mAb). Since the mAb quality could be subject to significant changes depending on manufacturing process conditions, real time monitoring and control systems are required to ensure mAb specifications mainly glycosylation and patient safety. Up to now, real time monitoring glycosylation of proteins has received scarce attention. In this article, the use of near infrared (NIR) to monitor mAb glycosylation has been reported for the first time. Whereas monitoring models are mainly constructed using linear partial least squares regressions (PLSR), evidences presented in this study indicate nonlinearity relationship between in situ captured spectra and compound concentrations, compromising the PLSR performances. A novel and simple approach was proposed to fit nonlinearity using the locally weighted regression (LWR). The LWR models were found to be more appropriate for handling information contained in spectra so that real time monitoring of cultures were accurately performed. Moreover, for the first time, the LWR calibration models allowed mAb glycosylation to be monitored, in a real time manner, by using in situ NIR spectroscopy. These results represent a further step toward developing active-control feedback of animal cell processes, particularly for ensuring properties of biologics.
(© 2019 American Institute of Chemical Engineers.)
Databáze: MEDLINE
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