On-line measurement of the substrate concentrations in Pichia pastoris fermentations using FT-IR/ATR

Dahlbacka, John; Weegar, Jan; Weymarn, Niklas von; Fagervik, Kaj

doi:10.1007/s10529-012-0868-9

Cited by 11 publications

(7 citation statements)

References 18 publications

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“…The application of IR-spectroscopy combined with PLS-modeling has been reported in several works to show immense potential to overcome the lack of monitoring strategies within the fermentation area, offering the possibility for multicomponent prediction (Dahlbacka et al 2012;Fayolle et al 2000;Genkawa et al 2012;Koch et al 2014;Kornmann et al 2004;Landgrebe et al 2010;Lourenço et al 2012;Pollard et al 2001;Sakhamuri et al 2001). The versatility of this combined strategy has been reported for various processes covering mammalian cell culture, antibiotic fermentation with filamentous fungi, lactic acid fermentation, wine fermentation and, as studied in this work, yeast fermentation processes (dos Santos et al 2017;Roychoudhury et al 2006;Sakhamuri et al 2001;Sandor et al 2013;Sivakesava et al 2001).…”

Section: Discussionmentioning

confidence: 99%

“…Thus, apart from increased robustness and affordability, novel technology tailors the spectrometer to this highly informative region. The versatility of MIRS in combination with multivariate calibration models such as partial-least-squares (PLS) has been demonstrated and reviewed in several publications as a powerful tool for monitoring of fermentation processes (Dahlbacka et al 2012;Fayolle et al 2000;Genkawa et al 2012;Koch et al 2014;Kornmann et al 2004;Landgrebe et al 2010;Lourenço et al 2012;Pollard et al 2001;Sakhamuri et al 2001).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Monitoring yeast fermentations by nonlinear infrared technology and chemometrics—understanding process correlations and indirect predictions

Pontius

Junicke

Gernaey

et al. 2020

Appl Microbiol Biotechnol

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Monitoring yeast fermentations by nonlinear infrared technology and chemometrics—understanding process correlations and indirect predictions

Pontius

Junicke

Gernaey

et al. 2020

Appl Microbiol Biotechnol

View full text Add to dashboard Cite

show abstract

“…There have been many reports on the use of NIR or middle‐IR (MIR), especially using ATR probes, for the measurement of glucose and other medium components in microbial and plant cell processes . Using an instrumentation system that employs a proprietary signal processing algorithm, it was shown that NIR can be used to monitor glycerol, methanol, and biomass concentration in the fermentation of Pichia pastoris .…”

Section: Sensors Commonly Used In Bioprocessmentioning

confidence: 99%

Advances in process monitoring tools for cell culture bioprocesses

Zhao

Zhou

et al. 2015

Engineering in Life Sciences

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Practical applicationThis review summarizes recent progress and current status of bioprocess monitoring. There has been an increasing emphasis on the applications of process analytical tools in bioprocessing for biologics manufacturing. The integration of in-line, on-line and at-line sensors and the real-time characterization of the physiological state of cells will lead to robust processes and enhanced product quality. AbstractThe productivity of cell culture manufacturing for biologics has increased momentously in the past decades. Increasingly, the process research efforts are devoted into improving product quality and consistency. Consistent process performance and successful implementation of quality by design (QbD) practice requires well-utilized process analytical technology (PAT). This review summarizes recent progress and current status of bioprocess monitoring. Many sensors for bioprocess monitoring have been available for decades while new ones, especially spectrometric sensors, are making their way into cell culture bioprocesses. On-line sampling devices have grown mature in the past decade thus making many instruments traditionally used for off-line analysis available for at-line use. With a general trend of using better defined medium for cell cultivation and increasing emphasis of process analytical tools, the spectrometric methods are also making headway in cell culture process monitoring. The integration of those sensing technologies will be important to advance the real-time monitoring of the state of cellular physiology for the control for process consistency and product quality.

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“…Further applications included mammalian cell cultures, 23,24 bacterial, 25–28 and yeast fermentations. 29–31…”

Section: Introductionmentioning

confidence: 99%

“…Further applications included mammalian cell cultures, 23,24 bacterial, [25][26][27][28] and yeast fermentations. [29][30][31] Within optical fibers, light is transmitted by total internal reflection. Transmission ranges depend on material properties: the lower wavelength limit is determined by electronic absorption (band gap edge), while the higher wavelength limit depends on the multi-phonon edge.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Fiber Optic and Conduit Attenuated Total Reflection (ATR) Fourier Transform Infrared (FT-IR) Setup for In-Line Fermentation Monitoring

et al. 2016

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The performance of a fiber optic and an optical conduit in-line attenuated total reflection mid-infrared (IR) probe during in situ monitoring of Penicillium chrysogenum fermentation were compared. The fiber optic probe was connected to a sealed, portable, Fourier transform infrared (FT-IR) process spectrometer via a plug-and-play interface. The optical conduit, on the other hand, was connected to a FT-IR process spectrometer via a knuckled probe with mirrors that had to be adjusted prior to each fermentation, which were purged with dry air. Penicillin V (PenV) and its precursor phenoxyacetic acid (POX) concentrations were determined by online high-performance liquid chromatography and the obtained concentrations were used as reference to build partial least squares regression models. Cross-validated root-mean-square errors of prediction were found to be 0.2 g L (POX) and 0.19 g L (PenV) for the fiber optic setup and 0.17 g L (both POX and PenV) for the conduit setup. Higher noise-levels and spectrum-to-spectrum variations of the fiber optic setup lead to higher noise of estimated (i.e., unknown) POX and PenV concentrations than was found for the conduit setup. It seems that trade-off has to be made between ease of handling (fiber optic setup) and measurement accuracy (optical conduit setup) when choosing one of these systems for bioprocess monitoring.

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On-line measurement of the substrate concentrations in Pichia pastoris fermentations using FT-IR/ATR

Cited by 11 publications

References 18 publications

Monitoring yeast fermentations by nonlinear infrared technology and chemometrics—understanding process correlations and indirect predictions

Monitoring yeast fermentations by nonlinear infrared technology and chemometrics—understanding process correlations and indirect predictions

Advances in process monitoring tools for cell culture bioprocesses

Comparison of Fiber Optic and Conduit Attenuated Total Reflection (ATR) Fourier Transform Infrared (FT-IR) Setup for In-Line Fermentation Monitoring

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