Enhancing cross‐scale Raman in‐line monitoring capability of cell culture process in large‐scale manufacturing

Abstract This study introduces an approach to enhance the Raman calibration model cross‐scale prediction capabilities in cell cultures. Our investigation centers on the improvement of Raman calibration models along with the scaling‐up of mammalian cell culture processes. Initially, we observed that integrating data from a 50 L run into the original dataset at lab‐scale was an effective strategy for improving prediction accuracy on 1000 L run. Further investigation indicated that this improvement could be attributed to the similarity between the spectra of 50 L with 1000 L. Subsequent investigation unveiled that the spectral variations primarily stemmed from differences between the instruments. This was verified through a direct comparison of two Raman analyzers. Then two pairwise spectral transformation methods, direct standardization (DS) and piecewise DS, both exhibited superior performance in predicting. This research underscores the importance of Raman spectral transfer method to alleviate instrument‐to‐instrument variations in cross‐scale monitoring of cell culture processes.

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Publication Details

Journal
AIChE Journal
Published
2024-09-09
DOI
https://doi.org/10.1002/aic.18608
Citations
2
Primary Topic
Viral Infectious Diseases and Gene Expression in Insects
Type
article
Field-Weighted Citation Impact
0.47
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article

Enhancing cross‐scale Raman in‐line monitoring capability of cell culture process in large‐scale manufacturing

S.B. Dong, Ziran Tang, Zhijun Zhang, Gong Chen et al.
2 citations
AIChE Journal
Viral Infectious Diseases and Gene Expression in Insects
0.47
article

Enhancing cross‐scale Raman in‐line monitoring capability of cell culture process in large‐scale manufacturing

S.B. Dong, Ziran Tang, Zhijun Zhang, Gong Chen, Huilin Zhu, Zhe Lang, Hang Zhou, Yang Yang, Weichang Zhou, Shaofan Yan
article en
2 citations

Abstract

Abstract This study introduces an approach to enhance the Raman calibration model cross‐scale prediction capabilities in cell cultures. Our investigation centers on the improvement of Raman calibration models along with the scaling‐up of mammalian cell culture processes. Initially, we observed that integrating data from a 50 L run into the original dataset at lab‐scale was an effective strategy for improving prediction accuracy on 1000 L run. Further investigation indicated that this improvement could be attributed to the similarity between the spectra of 50 L with 1000 L. Subsequent investigation unveiled that the spectral variations primarily stemmed from differences between the instruments. This was verified through a direct comparison of two Raman analyzers. Then two pairwise spectral transformation methods, direct standardization (DS) and piecewise DS, both exhibited superior performance in predicting. This research underscores the importance of Raman spectral transfer method to alleviate instrument‐to‐instrument variations in cross‐scale monitoring of cell culture processes.

AIChE JournalVol. 71(1)
WuXi AppTec (China) (CN)
Openalex Percentile: Top 35%
Viral Infectious Diseases and Gene Expression in Insects
0.47
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Enhancing cross‐scale Raman in‐line monitoring capability of cell culture process in large‐scale manufacturing — S.B. Dong, Ziran Tang, et al. · AIChE Journal (2024) | TGRS Research Map | TGRS