A new flow cell and chemometric protocol for implementing in‐line Raman spectroscopy in chromatography

On‐line monitoring tools for downstream chromatographic processing (DSP) of biotherapeutics can enable fast actions to correct for disturbances in the upstream, gain process understanding, and eventually lead to process optimization. While UV/Vis spectroscopy is mostly assessing the protein's amino acid composition and the application of Fourier transform infrared spectroscopy is limited due to strong water interactions, Raman spectroscopy is able to assess the secondary and tertiary protein structure without significant water interactions. The aim of this work is to implement the Raman technology in DSP, by designing an in‐line flow cell with a reduced dead volume of 80 μL and a reflector to increase the signal intensity as well as developing a chemometric modeling path. In this context, measurement settings were adjusted and spectra were taken from different chromatographic breakthrough curves of IgG1 in harvest. The resulting models show a small average RMSEP of 0.12 mg/mL, on a broad calibration range from 0 to 2.82 mg/mL IgG1. This work highlights the benefits of model assisted Raman spectroscopy in chromatography with complex backgrounds, lays the fundamentals for in‐line monitoring of IgG1, and enables advanced control strategies. Moreover, the approach might be extended to further critical quality attributes like aggregates or could be transferred to other process steps.

[1]  Harald Kolmar,et al.  At-line mid infrared spectroscopy for monitoring downstream processing unit operations , 2015 .

[2]  Massimo Morbidelli,et al.  Design and operation of a continuous integrated monoclonal antibody production process , 2017, Biotechnology progress.

[3]  Harald Kolmar,et al.  Mid-infrared spectroscopy-based antibody aggregate quantification in cell culture fluids. , 2013, Biotechnology journal.

[4]  R L Fahrner,et al.  Real-time control of purified product collection during chromatography of recombinant human insulin-like growth factor-I using an on-line assay. , 1998, Journal of chromatography. A.

[5]  Ludovic Duponchel,et al.  Mammalian cell culture monitoring using in situ spectroscopy: Is your method really optimised? , 2017, Biotechnology progress.

[6]  J. Hubbuch,et al.  Advances in downstream processing of biologics - Spectroscopy: An emerging process analytical technology. , 2017, Journal of chromatography. A.

[7]  Ron Kohavi,et al.  A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection , 1995, IJCAI.

[8]  A S Rathore,et al.  Process analytical technology (PAT) for biopharmaceutical products , 2010, Analytical and bioanalytical chemistry.

[9]  Brian Glennon,et al.  In situ Raman spectroscopy for simultaneous monitoring of multiple process parameters in mammalian cell culture bioreactors , 2012, Biotechnology progress.

[10]  G. Downey Vibrational spectroscopy in studies of food origin. , 2013 .

[11]  Alan G. Ryder,et al.  Applications of Raman Spectroscopy in Biopharmaceutical Manufacturing: A Short Review , 2017, Applied spectroscopy.

[12]  B. Ripley,et al.  Robust Statistics , 2018, Encyclopedia of Mathematical Geosciences.

[13]  D. Barh,et al.  Proteome scale comparative modeling for conserved drug and vaccine targets identification in Corynebacterium pseudotuberculosis , 2014, BMC Genomics.

[14]  R. A. van den Berg,et al.  Centering, scaling, and transformations: improving the biological information content of metabolomics data , 2006, BMC Genomics.

[15]  Anurag S. Rathore,et al.  Comparison of PAT based approaches for making real‐time pooling decisions for process chromatography – use of feed forward control , 2015 .

[16]  S. Engelsen,et al.  Interval Partial Least-Squares Regression (iPLS): A Comparative Chemometric Study with an Example from Near-Infrared Spectroscopy , 2000 .

[17]  Anurag S. Rathore,et al.  Application of process analytical technology for downstream purification of biotherapeutics , 2015 .

[18]  Jürgen Hubbuch,et al.  Real‐time monitoring and control of the load phase of a protein A capture step , 2016, Biotechnology and bioengineering.

[19]  Daan J.A. Crommelin,et al.  Methods for structural analysis of protein pharmaceuticals , 2005 .

[20]  Massimo Morbidelli,et al.  Process performance and product quality in an integrated continuous antibody production process , 2017, Biotechnology and bioengineering.

[21]  Harald Kolmar,et al.  Host cell protein quantification by fourier transform mid infrared spectroscopy (FT‐MIR) , 2013, Biotechnology and bioengineering.

[22]  Zai-Qing Wen,et al.  Raman spectroscopy of protein pharmaceuticals. , 2007, Journal of pharmaceutical sciences.

[23]  Massimo Morbidelli,et al.  Robust factor selection in early cell culture process development for the production of a biosimilar monoclonal antibody , 2017, Biotechnology progress.

[24]  M. Morbidelli,et al.  Online control of the twin-column countercurrent solvent gradient process for biochromatography. , 2013, Journal of chromatography. A.

[25]  Richard D. Braatz,et al.  Assessment of Recent Process Analytical Technology (PAT) Trends: A Multiauthor Review , 2015 .

[26]  S. Wold,et al.  PLS-regression: a basic tool of chemometrics , 2001 .

[27]  M. Hubert,et al.  Robust methods for partial least squares regression , 2003 .

[28]  Terrence M. Dobrowsky,et al.  Quick generation of Raman spectroscopy based in‐process glucose control to influence biopharmaceutical protein product quality during mammalian cell culture , 2016, Biotechnology progress.

[29]  A. Savitzky,et al.  Smoothing and Differentiation of Data by Simplified Least Squares Procedures. , 1964 .

[30]  Carl-Fredrik Mandenius,et al.  On-line monitoring of downstream bioprocesses , 2016 .

[31]  R. Barnes,et al.  Standard Normal Variate Transformation and De-Trending of Near-Infrared Diffuse Reflectance Spectra , 1989 .

[32]  Rekha Gautam,et al.  Review of multidimensional data processing approaches for Raman and infrared spectroscopy , 2015, EPJ Techniques and Instrumentation.

[33]  Rasmus Bro,et al.  Variable selection in regression—a tutorial , 2010 .

[34]  Holly J. Butler,et al.  Using Raman spectroscopy to characterize biological materials , 2016, Nature Protocols.