Monitoring of Submerged Bioprocesses

Abstract

Monitoring is an important exercise in the operation of submerged bioprocesses and is a subject that has attracted intense research activity in recent years. In order to achieve optimal production or conversion, the factors that influence the performance of a bioprocess should be measured, preferably on-line, so that the process can be monitored in real-time and appropriate control or remedial action implemented. Such measurements can be achieved either in situ or ex situ. Ideally, in situ approaches are desirable. Where such an option is difficult to implement, ex situ approaches with appropriate sample handling techniques can be employed. In cases where direct analytical information is not available, inferential approaches can be adopted. In addition, analytical information not yet accessible on-line can be obtained off-line. Computational techniques have enabled the compilation of measurement data before utilizing the information for process diagnosis. Current developments in the different measurement technologies are presented with a critical assessment of their potential application in industrial production or process development.

Use of at‐line and in‐situ near‐infrared spectroscopy to monitor biomass in an industrial fed‐batch Escherichia coli process

“…While such at-line measurements represent an improvement over traditional off-line methods and are close to real-time analysis, the ideal approach is monitoring on-line, preferably in-situ where the analyser is in direct contact in the process stream, therefore enabling accurate determination of analytes in real-time. At present, despite much research effort, such real-time monitoring in an industrial context is usually restricted to parameters such as off-gas determination, temperature, dissolved oxygen, and pH (Vaidyanathan et al, 1999a).…”

Real‐time update of calibration model for better monitoring of batch processes using spectroscopy

“…Improvements in spectrometers, detectors, and optics, along with the availability of powerful, yet inexpensive computers, have led to many new and useful applications (Harms et al, 2002;Marose et al, 1999;Schügerl, 2001;Vaidyanathan et al, 1999). These sensor systems offer many advantages, such as rapid, noninvasive, and simultaneous monitoring of metabolites, in situ sterilizability, long-term stability, and low need for maintenance.…”

Assessment of near‐infrared spectral information for rapid monitoring of bioprocess quality

“…However, given the fact that a typical NIR spectrum encompasses information regarding almost all the constituents of the sample matrix, there are few case studies (Hagman and Sivertson, 1998, among the few) that have investigated the spectral details for applications in bioprocess quality assessment or qualitative bioprocess monitoring, in a composite manner. Such information would be invaluable in providing operator-level assistance on the progress of a bioprocess, in industrial-scale productions (Montague, 1997;Vaidyanathan et al, 1999a). Principal component analysis can be useful in extracting information for such purposes.…”

“…Despite this, it is widely recognized that the control of these processes is, as yet, suboptimal (Dochain and Perrier, 1997;Glassey et al, 2000;Montague, 1997). One major contributor to this problem is the lack of reliable, multi-analyte real-time (or near-real-time) information upon which to base an assessment of culture performance, and thus, to use for critical decision making for control purposes (Montague, 1997;Olsson et al, 1998;Vaidyanathan et al, 1999a;Zhou and Mulchandani, 1995). Thus, at present, despite considerable advances in control, such assessments/decisions are typically based on process data produced by infrequent sampling which often has a significant time delay built in, and may, in many cases, be an inferential measurement.…”