A Novel Raman‐Chromatography Assembly for Automated Calibration and In‐Line Monitoring in Bioprocessing

Optical spectroscopic techniques have been successfully employed in bioprocessing as process analytical technology for real-time process monitoring in numerous applications. The implementation of spectroscopy-based PAT techniques commonly necessitates the generation of representative process data used for calibration and validation of multivariate statistical models for analyzing the sample composition in real-time. To automate the generation of such data, we present a novel assembly of a commercially available chromatography system in combination with a Raman spectrometer for fast and accurate acquisition of Raman spectra. Using the ultra-/diafiltration (UF/DF) process as a case study, our methodology involved the preparation of representative calibration and validation mixtures of phosphate and citrate buffer and lysozyme as a model protein. Chemometric PLS models were calibrated and validated using these datasets, and applied to in-line recorded Raman spectra during a UF/DF experiment. The primary results demonstrated that the novel assembly provides robust and precise offline measurement of Raman spectra, which directly compare with in-line record data. The chemometric PLS models showed good alignment in calibration and validation datasets (R2 and Q2), and could be used to simultaneously monitor the buffer and protein concentrations in real-time during UF/DF. This study provides a simple, commercially available setup for automated acquisition of Raman spectra and demonstrates its straightforward application to bioprocess monitoring.

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Publication Details

Journal
Engineering in Life Sciences
Published
2025-09-01
DOI
https://doi.org/10.1002/elsc.70044
Citations
1
Primary Topic
Spectroscopy and Chemometric Analyses
Type
article
Field-Weighted Citation Impact
0.75
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article

A Novel Raman‐Chromatography Assembly for Automated Calibration and In‐Line Monitoring in Bioprocessing

Robin Schiemer, Michael Schmitt, Fabian Willems, Lars Robbel et al.
1 citations
Engineering in Life Sciences
Spectroscopy and Chemometric Analyses
0.75
article

A Novel Raman‐Chromatography Assembly for Automated Calibration and In‐Line Monitoring in Bioprocessing

Robin Schiemer, Michael Schmitt, Fabian Willems, Lars Robbel, Jürgen Hubbuch, Cunlong Wang, Jakob Heyer‐Müller, Matthias Lopinski
article en
1 citations

Abstract

Optical spectroscopic techniques have been successfully employed in bioprocessing as process analytical technology for real-time process monitoring in numerous applications. The implementation of spectroscopy-based PAT techniques commonly necessitates the generation of representative process data used for calibration and validation of multivariate statistical models for analyzing the sample composition in real-time. To automate the generation of such data, we present a novel assembly of a commercially available chromatography system in combination with a Raman spectrometer for fast and accurate acquisition of Raman spectra. Using the ultra-/diafiltration (UF/DF) process as a case study, our methodology involved the preparation of representative calibration and validation mixtures of phosphate and citrate buffer and lysozyme as a model protein. Chemometric PLS models were calibrated and validated using these datasets, and applied to in-line recorded Raman spectra during a UF/DF experiment. The primary results demonstrated that the novel assembly provides robust and precise offline measurement of Raman spectra, which directly compare with in-line record data. The chemometric PLS models showed good alignment in calibration and validation datasets (R2 and Q2), and could be used to simultaneously monitor the buffer and protein concentrations in real-time during UF/DF. This study provides a simple, commercially available setup for automated acquisition of Raman spectra and demonstrates its straightforward application to bioprocess monitoring.

Engineering in Life SciencesVol. 25(9)
Karlsruhe Institute of Technology (DE), Philipps University of Marburg (DE)
Openalex Percentile: Top 26%
Spectroscopy and Chemometric Analyses
0.75
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