Prediction of filamentous process performance attributes by CSL quality assessment using mid-infrared spectroscopy and chemometrics

Alexandra Hofer; Donya Kamravamanesh; Judit Bona-Lovasz; Andreas Limbeck; Bernhard Lendl; Christoph Herwig; Jens Fricke

doi:10.1016/j.jbiotec.2017.11.010

Prediction of filamentous process performance attributes by CSL quality assessment using mid-infrared spectroscopy and chemometrics

J Biotechnol. 2018 Jan 10:265:93-100. doi: 10.1016/j.jbiotec.2017.11.010. Epub 2017 Nov 23.

Authors

Alexandra Hofer¹, Donya Kamravamanesh¹, Judit Bona-Lovasz², Andreas Limbeck³, Bernhard Lendl³, Christoph Herwig⁴, Jens Fricke⁵

Affiliations

¹ Research Area Biochemical Engineering, Institute of Chemical, Environmental and Biological Engineering, Vienna University of Technology, Gumpendorferstrasse 1a - 166/4, A-1060 Vienna, Austria.
² Sandoz GmbH, Novartis Technical Operations - Anti-Infectives, Process Development, Biochemiestrasse 10, 6250 Kundl, Austria.
³ Institute of Chemical Technology and Analytics, Vienna University of Technology, Getreidemarkt 9/164 AC, A-1060 Vienna, Austria.
⁴ Research Area Biochemical Engineering, Institute of Chemical, Environmental and Biological Engineering, Vienna University of Technology, Gumpendorferstrasse 1a - 166/4, A-1060 Vienna, Austria; CD Laboratory on Mechanistic and Physiological Methods for Improved Bioprocesses, Vienna University of Technology, Gumpendorferstrasse 1a - 166/4, A-1060 Vienna, Austria.
⁵ Research Area Biochemical Engineering, Institute of Chemical, Environmental and Biological Engineering, Vienna University of Technology, Gumpendorferstrasse 1a - 166/4, A-1060 Vienna, Austria; CD Laboratory on Mechanistic and Physiological Methods for Improved Bioprocesses, Vienna University of Technology, Gumpendorferstrasse 1a - 166/4, A-1060 Vienna, Austria. Electronic address: jens.fricke@tuwien.ac.at.

PMID: 29174594
DOI: 10.1016/j.jbiotec.2017.11.010

Abstract

Every biopharmaceutical production process aims for control strategies to achieve process robustness in order to ensure consistent product quality. Process variability can origin from process parameters, the biological nature as well as from high lot-to-lot variability of raw materials. In filamentous processes raw materials with very complex matrices, such as corn steep liquor (CSL), are used, which are especially challenging to characterize. In this study, CSL was characterized in detail for its ingredients presenting an overall composition of its matrix of 50 analyzed components (19 amino acids, 5 organic acids, 8 reducing sugars, 7 water-soluble vitamins and 11 trace elements/minerals) in order to facilitate analytical reduction to fingerprinting methods FT-MIR was evaluated as fast and non-destructive spectroscopic fingerprinting method for adequate assessment of CSL quality. Feasibility of this method was shown by the correlation of certain bands in the spectra to substance groups present in CSL, such as the Amide I and II band and amino acids, respectively. Additionally, applicability of FT-MIR could be shown for classification of different CSL lots differing in provider and corn quality as well as for predictability of process performance attributes. The latter was demonstrated on a fed-batch filamentous fungi process for the production of antibiotics. By multivariate data analysis, it could be shown that CSL quality assessment via FT-MIR can be used for the prediction of maximal biomass generated in the process, with a correlation coefficient R² of 0.964, as well as for the prediction of an unwanted impurity. The combination of a fast and easy method for CSL quality assessment and correlations of this quality with process performance attributes may facilitate the establishment of a risk-based acceptance criteria for raw material quality release of CSL. As CSL is a frequent used raw material, we believe that this method will also be useful for other processes and that CSL quality assessment is of high relevance in academia and industry.

Keywords: Corn steep liquor; Filamentous fungi; Mid-infrared spectroscopy; Raw material quality assessment; Raw material quality control release.

MeSH terms

Acremonium / metabolism
Anti-Bacterial Agents / metabolism
Fermentation
Fourier Analysis
Spectrophotometry, Infrared
Zea mays / chemistry*

Substances

Anti-Bacterial Agents