Chemometrics and in-line near infrared spectroscopic monitoring of a biopharmaceutical Chinese hamster ovary cell culture: Prediction of multiple cultivation variables

Clavaud, Matthieu; Roggo, Yves; Daeniken, Ralph Von; Liebler, André; Schwabe, J. O.

doi:10.1016/j.talanta.2013.03.044

Cited by 69 publications

(58 citation statements)

References 11 publications

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“…Furthermore, other spectroscopy-based methods such as such as NIR, MIR, and fluorescence spectroscopy have been used to monitor CHO culture process parameters. [22][23][24] Results from preliminary studies indicate Raman is an excellent candidate for process monitoring and inline measurement of cell culture process parameters. In this study, we build upon previous work to generate generic calibration models using a comprehensive data pool from several mammalian cell culture batches.…”

mentioning

confidence: 99%

Generic Raman‐based calibration models enabling real‐time monitoring of cell culture bioreactors

Mehdizadeh

Lauri

Karry

et al. 2015

Biotechnology Progress

102

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Raman-based multivariate calibration models have been developed for real-time in situ monitoring of multiple process parameters within cell culture bioreactors. Developed models are generic, in the sense that they are applicable to various products, media, and cell lines based on Chinese Hamster Ovarian (CHO) host cells, and are scalable to large pilot and manufacturing scales. Several batches using different CHO-based cell lines and corresponding proprietary media and process conditions have been used to generate calibration datasets, and models have been validated using independent datasets from separate batch runs. All models have been validated to be generic and capable of predicting process parameters with acceptable accuracy. The developed models allow monitoring multiple key bioprocess metabolic variables, and hence can be utilized as an important enabling tool for Quality by Design approaches which are strongly supported by the U.S. Food and Drug Administration.

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mentioning

confidence: 99%

Generic Raman‐based calibration models enabling real‐time monitoring of cell culture bioreactors

Mehdizadeh

Lauri

Karry

et al. 2015

Biotechnology Progress

102

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“…Another example of monitoring CHO cell cultivations with NIRS is presented by Clavaud et al [27]. A FT-NIR device fiber optic transflection probe (1 mm pathlength) was connected to the bioreactor.…”

Section: In-linementioning

confidence: 99%

Near-infrared spectroscopy in upstream bioprocesses

Hoehse¹,

Alves-Rausch²,

Prediger³

et al. 2015

Pharmaceutical Bioprocessing

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The quality of upstream processes and their products strongly depends on the control of all influencing parameters. However, several relevant parameters are not measured in standard bioreactor systems. Near-infrared spectroscopy (NIRS) is one promising technology capable of becoming the missing link in sensor technology. This review gives an overview of the technological principles and the technological progress. A broad range of possible applications is presented, forming in its entirety a valuable toolbox for process risk mitigation. Recent applications of NIRS in upstream bioprocesses are discussed. Moreover, the review includes regulatory aspects in implementation, calibration and validation of NIRS instrumentation and models. Key termProcess trajectory: Road of process evolution that displays whether an actual batch process runs similar to good historical batches.

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“…PCA has been widely used for grouping of bioprocess runs, outlier detection, and phase segregation purposes . On the other hand, PLSR modeling is used predominantly for the purpose of predictively understanding process‐to‐product relationships or for model calibration such as for spectroscopic devices . In spectroscopy‐based bioprocess monitoring, it has been shown that numerous variables such as metabolites, cell density, and titer can be predicted based on the spectra .…”

Section: Introductionmentioning

confidence: 99%

“…10,11,19 On the other hand, PLSR modeling is used predominantly for the purpose of predictively understanding process-to-product relationships 6,7,10,11 or for model calibration such as for spectroscopic devices. [20][21][22][23] In spectroscopy-based bioprocess monitoring, it has been shown that numerous variables such as metabolites, cell density, and titer can be predicted based on the spectra. [24][25][26] Recent examples illustrate the application of PLSR-based calibration models to monitor several amino acids in cell culture processes.…”

Section: Introductionmentioning

confidence: 99%

Decision Tree‐PLS (DT‐PLS) algorithm for the development of process: Specific local prediction models

Narayanan

Sokolov

Butté

2019

Biotechnology Progress

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This work presents a novel multivariate statistical algorithm, Decision Tree‐PLS (DT‐PLS), to improve the prediction and understanding of dynamic processes based on local partial least square regression (PLSR) models for characteristic process groups defined based on Decision Tree (DT) analysis. The DT‐PLS algorithm is successfully applied to two different cell culture data sets, one obtained from bioreactors of 3.5 L lab scale and the other obtained from the 15 ml ambr microbioreactor system. Substantial improvement in the predictive capabilities of the model can be achieved based on the localization compared to the classical PLSR approach, which is implemented in the commercially available packages. Additionally, the differences in the model parameters of the local models suggest that the governing process variables vary for the different process regimes indicating the different states of the cell under different process conditions.

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Chemometrics and in-line near infrared spectroscopic monitoring of a biopharmaceutical Chinese hamster ovary cell culture: Prediction of multiple cultivation variables

Cited by 69 publications

References 11 publications

Generic Raman‐based calibration models enabling real‐time monitoring of cell culture bioreactors

Generic Raman‐based calibration models enabling real‐time monitoring of cell culture bioreactors

Near-infrared spectroscopy in upstream bioprocesses

Decision Tree‐PLS (DT‐PLS) algorithm for the development of process: Specific local prediction models

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