- Poster presentation
- Open Access
NIR-spectroscopy for bioprocess monitoring & control
© Sandor et al.; licensee BioMed Central Ltd. 2013
Published: 4 December 2013
The Quality by Design (QbD) approach shows significant benefit in classical pharmaceutical industry and is now on the cusp to a stronger influence on biopharmaceutical applications. Monitoring the critical process parameters (CPP) applying process analytical technologies (PAT) during biotechnological cell cultivations is of high importance in order to maintain a high efficiency and quality of a bioprocess. For parameters like glucose concentration, total cell count (TCC) or viability a robust online prediction is in many applications not yet possible. This gap can be closed with the help of NIR spectroscopy (NIRS), which provides quantitative prediction of single analytes in real-time.
For accurate process control based on NIR spectroscopy, special care has to be taken while building the calibration model [1, 2]. In cell cultivation almost all analytes are confounded and show large correlation coefficients. Therefore, partial least square (PLS) models are not able to discriminate between the signals of the different analytes. Especially, analytes like glucose or glutamine which are strongly confounded with cell growth need to be evaluated carefully as cell growth is the analyte causing the largest changes in NIR spectra throughout a cultivation run. Spiking experiments are the most efficient way in order to break correlations between critical analytes like glucose and other nutrients or TCC. This strategy should be followed in order to build robust calibration models without correlations [3, 4]. Another very critical issue occurring in cell cultivation are batch-to-batch variations. As it is recommended in good modeling practice , for robust models it is crucial to use several complete batches for validation which are not part of the calibration set rather than cross validation .
Materials and methods
CHO-K01 cells (Cell Culture Technology, University of Bielefeld), were cultivated in a BIOSTAT® C plus bioreactor (Sartorius Stedim Biotech) with a 7.5 L working volume. In total, eight cultivation runs were performed, each lasting six days on average. Sampling was performed every three to six hours, and reference analytics of the critical process parameters, such as TCC, viability (TC10 automated cell counter, Bio-Rad), glucose, lactate, glutamine, etc. (YSI 2700, YSI Inc.) were determined in the laboratory.
NIR results for calibration models and validation by external data sets.
No. Cal. No. Val. Batches (Samples)
TCC (·106 cell/mL)
The Ingold port adaption of a free beam NIR spectrometer is tailored for optimal bioprocess monitoring and control. The device shows an excellent signal to noise ratio dedicated to a large free aperture and therefore a large sample volume. This can be seen particularly in the batch trajectories which show a high reproducibility. The robust and compact design withstands rough process environments as well as SIP/CIP cycles.
Robust free beam NIR process analyzers are indispensable tools within the PAT/QbD framework for real-time process monitoring and control. They enable multiparametric, non-invasive measurements of analyte concentrations and process trajectories. Free beam NIR spectrometers are an ideal tool to define golden batches and process borders in the sense of QbD. Moreover, sophisticated data analysis both quantitative and MSPC yields directly to a far better process understanding. Information can be provided online in easy to interpret graphs which allow the operator to make fast and knowledge-based decisions. This finally leads to higher stability in process operation, better performance and less failed batches.
- Cervera A, Petersen N: Application of near- infrared spectroscopy for monitoring and control of cell culture and fermentation. Biotechnology Progress. 2009, 25: 1561-1581.PubMedGoogle Scholar
- Rodrigues L, Vieira L, Cardoso J P, Menezes JC: The use of NIR as a multi-parametric in situ monitoring technique in filamentous fermentation systems. Talanta. 2008, 75: 1356-1361.View ArticlePubMedGoogle Scholar
- Arnold SA, Crowley J, Woods N, Harvey LM, McNeil B: In-situ near infrared spectroscopy to monitor key analytes in mammalian cell cultivation. Biotechnology and bioengineering. 2003, 84: 13-19.View ArticlePubMedGoogle Scholar
- Vaidyanathan S, Macaloney G, Harvey LM, McNeil B: Assessment of the Structure and Predictive Ability of Models Developed for Monitoring Key Analytes in a Submerged Fungal Bioprocess Using Near-Infrared Spectroscopy. Applied Spectroscopy. 2001, 55: 444-453.View ArticleGoogle Scholar
- Henriques JG, Buziol S, Stocker E, Voogd A, Menezes JC: Monitoring Mammalian Cell Cultivations for Monoclonal Antibody Production Using Near-Infrared Spectroscopy. Optical Sensor Systems in Biotechnology. Edited by: Rao G. 2010, Place: Springer, Berlin, Heidelberg, 2010: 29-72.Google Scholar
- Hakemeyer C, Strauss U, Werz S, Jose GE, Folque F, Menezes JC: At-line NIR spectroscopy as effective PAT monitoring technique in Mab cultivations during process development and manufacturing. Talanta. 2012, 90: 12-21.View ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.