Journal
CHEMIE INGENIEUR TECHNIK
Volume 88, Issue 6, Pages 764-776Publisher
WILEY-V C H VERLAG GMBH
DOI: 10.1002/cite.201500101
Keywords
Bioprocess monitoring; Mechanistic modeling; Raman spectroscopy; Soft sensor
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Funding
- Sandoz GmbH
- Austrian research funding association (FFG) under the scope of the COMET program within the research project Industrial Methods for Process Analytical Chemistry (imPACts)'' [843546]
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A soft sensor that combines data from Raman spectroscopy and off-gas analyzers with a dynamic mechanistic bioprocess model was investigated for online monitoring of the physiological characteristics of Penicillium chrysogenum fed-batch cultivations. A systematic workflow based on nonlinear observability analysis was established for accelerating and improving the process of soft-sensor development. Using in situ Raman spectroscopy, it was possible to perform accurate and frequent measurements of the penicillin concentration in the bioreactor, which were combined with measurements of respiratory rates. Using a particle filter algorithm, the soft sensor allowed for the online estimation of the biomass concentration, the specific growth rate, and the specific penicillin production rate.
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