Online‐Infrarotspektroskopie in der Bioprozessanalytik

Haake, Claas; Landgrebe, Daniel; Scheper, Thomas; Rhiel, Martin

doi:10.1002/cite.200900042

Cited by 13 publications

(6 citation statements)

References 41 publications

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“…4 and Supporting Information, Table S1). Several review articles on infrared and fluorescence spectroscopy [89,94,110,[121][122][123][124] are summarized in Supporting Information, Table S2, sorted by the type of spectroscopy with a short description of the topics covered in each.…”

Section: Optical Sensor Systems: Spectroscopic Sensorsmentioning

confidence: 99%

Sensor systems for bioprocess monitoring

Biechele

Busse

Solle

et al. 2015

Engineering in Life Sciences

173

158

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The ability to measure all process variables is of great importance in the field of bioprocess monitoring and control, and continuous, real‐time measurements are highly desired. The more complete and real‐time the measurements are, the more stable, reproducible, and efficient the process can be, leading to reproducibly high‐quality products. This additional information allows the operator to better document the entire process. The process analytical technologies initiative of the US Food and Drug Administration is strongly related to the analysis and control of biopharmaceutical processes. The aim of the initiative is to create processes, generating products of ensured quality by measuring quality‐related process variables. The quality of the product is enhanced by a deep understanding of the process, which is enabled by an effective and suitable sensor system. The aim of this review is to provide an overview of current and emerging sensors for bioprocess monitoring. Sensors directly interfaced to bioreactors for measuring important variables from the gas phase, such as oxygen and carbon dioxide concentration, are discussed, as well as sensors for the monitoring of the biomass concentration and morphology and of the changing medium composition. Furthermore, sensor systems are discussed. These involve sensors (especially biosensors) that are not implemented directly inside the bioreactor but rather are used in conjunction with sample‐taking systems such as flow injection analysis. A major focus is given to spectroscopic sensors, which are noninvasive and offer interesting options for a simultaneous analysis of various compounds. Since data handling is extremely important for this kind of sensor, chemometrics are also included. Soft sensors are discussed as technology that allows a user to incorporate more process data as it become available. Finally, the current state of disposable sensor technology is presented. These sensors are needed for the growing area of disposable and continuous biomanufacturing.

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Section: Optical Sensor Systems: Spectroscopic Sensorsmentioning

confidence: 99%

Sensor systems for bioprocess monitoring

Biechele

Busse

Solle

et al. 2015

Engineering in Life Sciences

173

158

View full text Add to dashboard Cite

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“…However, the applicability of this technique is limited due to the strong infrared absorption of water below wave numbers of 4000 cm -1 . NIR spectroscopy has been reported to be a suitable tool for monitoring of substrates and products in biotechnology [38,44]. Hydrogen bonds which exhibit distinctive stretch vibrations between 3600 and 2400 cm -1 allow for the detection of molecules that contain hydrogen bound to a heteroatom.…”

Section: Infrared Spectroscopymentioning

confidence: 99%

Optimization of Insect Cell Based Protein Production Processes - Online Monitoring, Expression Systems, Scale Up

Druzinec

Salzig

Brix

et al. 2013

Yellow Biotechnology II

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“…This indicates the demand of sufficient sensor equipment for efficient online monitoring. Promising methods for online monitoring of concentration trends of the relevant metabolites, nutrients and biomass are optical or acoustical spectroscopy [23][24][25]. However, the industrial use of these techniques in biotechnological processes is rare due to high costs and operation-related adaption.…”

Section: Motivation For Mathematical Growth Modelingmentioning

confidence: 99%

Bioprocess monitoring and control via adaptive sensor calibration

Krause

Birle

Hussein

et al. 2011

Engineering in Life Sciences

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To ensure optimal product quality of bioprocesses, it is necessary to develop intelligent control systems with integrated monitoring of key parameters. Having optimal yeast propagation in brewing technology is important to increase the efficiency of subsequent processes. Major drawbacks are: lacks in online detection of yeast attributes and temporal control schemes. One solution is to accurately detect essential process parameters combined with expert knowledge of linguistic control mechanisms. Those needs can be fulfilled by fuzzy logic or state observers including process dynamics associated with accurate multivariate calibration of sensing devices. Ultrasonic‐based devices could monitor key parameter but their inline implementation is limited due to influences of the temperature and gas bubbles. Thus, incipient stages for calibration of the device including temperature dependencies using time and frequency properties of ultrasonic waves are presented. A multivariate model using offline measurements with a maximum prediction error of 0.48 g/100 g is reported in this study. Additionally, we show preliminary results of a mechanistic model for the temperature dependency of yeast growth adapted from the literature (biomass and ethanol production, substrate consumption). The results will lead to flexible control of temperature and aeration resulting in vital yeast and enhanced transparency of propagation progress according to the demands.

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Online‐Infrarotspektroskopie in der Bioprozessanalytik

Cited by 13 publications

References 41 publications

Sensor systems for bioprocess monitoring

Sensor systems for bioprocess monitoring

Optimization of Insect Cell Based Protein Production Processes - Online Monitoring, Expression Systems, Scale Up

Bioprocess monitoring and control via adaptive sensor calibration

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