Online monitoring of a bioprocess based on a multi‐analyser system and multivariate statistical process modelling

Multivariate statistical process control (MSPC) was for the first time applied to analyse data from a bioprocess on-line multi-analyser system consisting of an electronic nose (EN), a near-infrared spectroscope (NIRS), a mass spectrometer (MS) and standard bioreactor probes. One hundred and fifty sensor signals from the electronic nose, 1050 wavelength signals from the NIRS, carbon dioxide evolution rate calculated from mass spectrometer signals and standard bioreactor data (eg amount of substrate fed) were interrogated for their ability to model a bioprocess using MSPC. The models obtained were validated on a recombinant Escherichia coli fed-batch process for tryptophan production. Limiting trajectories were defined in the MSPC models for warning, action, and process experience with respect to biomass and tryptophan concentrations. The results showed the capacity and robustness of MSPC models for monitoring with multi-analysers and allowed a comparison of the different analysers' suitability for this kind of data processing. Furthermore, the results demonstrate that MSPC models provide a functional and versatile framework for coping with large information flows and are also suited to a variety of other bioprocessing monitoring and control tasks. © 2002 Society of Chemical Industry

[1]  Carl-Fredrik Mandenius,et al.  Electronic nose for estimation of product concentration in mammalian cell cultivation , 2000 .

[2]  G. Barrie Wetherill,et al.  Statistical Process Control , 1991 .

[3]  Carl-Fredrik Mandenius,et al.  Integration of distributed multi-analyzer monitoring and control in bioprocessing based on a real-time expert system. , 2003, Journal of biotechnology.

[4]  Carl-Fredrik Mandenius,et al.  Assessment of the Performance of a Fed‐Batch Cultivation from the Preculture Quality Using an Electronic Nose , 2002, Biotechnology progress.

[5]  T. Bachinger,et al.  Searching for process information in the aroma of cell cultures. , 2000, Trends in biotechnology.

[6]  Linda M. Harvey,et al.  Deconvolution of near-infrared spectral information for monitoring mycelial biomass and other key analytes in a submerged fungal bioprocess , 2001 .

[7]  Carl-Fredrik Mandenius,et al.  Physiologically Motivated Monitoring of Fermentation Processes by Means of an Electronic Nose , 2001 .

[8]  S Albert,et al.  Multivariate statistical monitoring of batch processes: an industrial case study of fermentation supervision. , 2001, Trends in biotechnology.

[9]  D Matteuzzi,et al.  A near‐infrarod spectroscopy technique for the control of fermentation processes: An application to lactic acid fermentation , 1994, Biotechnology and bioengineering.

[10]  Gunnar Lidén,et al.  Predicting Fermentability of Wood Hydrolyzates with Responses from Electronic Noses , 1999, Biotechnology progress.

[11]  Dirk Weuster-Botz,et al.  Continuous computer controlled production of formate dehydrogenase (FDH) and isolation on a pilot scale , 1994 .

[12]  Svante Wold,et al.  Modelling and diagnostics of batch processes and analogous kinetic experiments , 1998 .

[13]  S. Schmidt,et al.  Near infrared spectroscopy in fermentation and quality control for amino acid production , 1998 .

[14]  W R Strohl,et al.  Acetate metabolism by Escherichia coli in high-cell-density fermentation , 1994, Applied and environmental microbiology.

[15]  Gary D. Christian,et al.  On-line spectrophotometric determination of phosphate in bioprocesses by sequential injection , 1995 .

[16]  H M Davey,et al.  Rapid analysis of high-dimensional bioprocesses using multivariate spectroscopies and advanced chemometrics. , 2000, Advances in biochemical engineering/biotechnology.

[17]  T. Eklöv,et al.  Selection of variables for interpreting multivariate gas sensor data , 1999 .

[18]  Barry Lennox,et al.  Application of multivariate statistical process control to batch operations , 2000 .

[19]  John F. MacGregor,et al.  Multivariate SPC charts for monitoring batch processes , 1995 .

[20]  Sten Bay Jørgensen,et al.  Supervision of fed-batch fermentations , 1999 .

[21]  J. E. Jackson.  A User's Guide to Principal Components , 1991 .

[22]  Vaidyanathan,et al.  At-line monitoring of a submerged filamentous bacterial cultivation using near-infrared spectroscopy. , 2000, Enzyme and microbial technology.

[23]  M Hoare,et al.  Near-infrared spectroscopy for bioprocess monitoring and control. , 1999, Biotechnology and bioengineering.

[24]  T. Bachinger,et al.  Monitoring cellular state transitions in a production-scale CHO-cell process using an electronic nose. , 2000, Journal of biotechnology.

[25]  R. W. Marshall,et al.  Detection and simultaneous identification of microorganisms from headspace samples using an electronic nose. , 1997 .

[26]  John F. MacGregor,et al.  Multi-way partial least squares in monitoring batch processes , 1995 .

[27]  S. Enfors,et al.  Glucose overflow metabolism and mixed-acid fermentation in aerobic large-scale fed-batch processes with Escherichia coli , 1999, Applied Microbiology and Biotechnology.

[28]  B. McNeil,et al.  Near-Infrared Spectroscopic Determination of Acetate, Ammonium, Biomass, and Glycerol in an Industrial Escherichia Coli Fermentation , 1996 .

[29]  Ingemar Lundström,et al.  Catalytic metals and field-effect devices—a useful combination , 1990 .

[30]  Michael P. Craven,et al.  The prediction of bacteria type and culture growth phase by an electronic nose with a multi-layer perceptron network , 1998 .

[31]  A. J. Morris,et al.  Multivariate statistical process control of an industrial fluidised-bed reactor , 2000 .

[32]  P. Mårtensson,et al.  Estimation of biomass and specific growth rate in a recombinant Escherichia coli batch cultivation process using a chemical multisensor array. , 1998, Journal of biotechnology.

[33]  H. Lidén,et al.  On-line determination of non-volatile or low-concentration metabolites in a yeast cultivation using an electronic nose , 2000 .

[34]  Mark R. Riley,et al.  Simultaneous measurement of glucose and glutamine in insect cell culture media by near infrared spectroscopy. , 1997 .