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Quality Control of fermentation broths

AN-NIR-099

2021-12

Quality Control of fermentation broths

Multiparameter determination within one minute


Summary

Cell fermentation processes are a reliable production method for small molecules and protein-based active pharmaceutical ingredients (APIs), allowing pharmaceutical companies to optimize the production process and reduce time to market. The fermentation process requires monitoring of many different parameters to ensure optimal production. These quality parameters include (but are not limited to) pH, bacterial content, potency, glucose, and concentration of reducing sugars. Traditional laboratory analysis takes a significant amount of time and requires different analytical techniques to monitor these quality parameters in the fermentation process.

Near-infrared spectroscopy (NIRS) offers a faster and more cost-efficient alternative to traditional methods for the determination of critical parameters in fermentation broths at any stage of the fermentation process.


Experimental equipment

DS2500 Solid Analyzer.
Figure 1. DS2500 Solid Analyzer.

Fermentation broth samples taken at different fermentation times were measured in reflection mode with the Metrohm DS2500 Solid Analyzer. Because the samples were dark in color (yellow-brown), they were measured without needing to use the gold reflector and required no sample preparation. The Metrohm software package Vision Air Complete was used for all data acquisition and prediction model development.

Table 1. Hardware and software equipment overview
Equipment Metrohm number
DS2500 Solid Analyzer 2.922.0010
NIRS transflection vessel 6.7401.000
NIRS Mini Sample Cup Holder for DS25006.7430.040
Vision Air 2.0 Complete 6.6072.208


Result

The obtained Vis-NIR spectra (Figure 2) were used to create prediction models for quantification of the bacterial, glucose, and reducing sugars concentration, as well as the pH and potency. The quality of the prediction models was evaluated using the correlation diagram, which displays a high correlation between the Vis-NIR prediction and the reference values. The respective figures of merit (FOM) display the expected precision of a prediction during routine analysis. Potency (Figures 7 and 8) was measured with two different laboratory methods as described in Table 8.

Vis-NIR spectra of fermentation broth samples taken at different fermentation times and analyzed on a DS2500 Solid Analyzer.
Figure 2. Vis-NIR spectra of fermentation broth samples taken at different fermentation times and analyzed on a DS2500 Solid Analyzer.

Result pH in fermentation broths

Correlation diagram for the prediction of pH in fermentation broth using a DS2500 Solid Analyzer. The lab value was evaluated using a pH meter.
Figure 3. Correlation diagram for the prediction of pH in fermentation broth using a DS2500 Solid Analyzer. The lab value was evaluated using a pH meter.
Table 2. Figures of merit for the prediction of pH in fermentation broth using a DS2500 Solid Analyzer.
Figures of meritValue
R20.6461
Standard error of calibration0.1645
Standard error of cross-validation0.1686
Standard error of validation0.0997

Result bacterial concentration in fermentation broths

Correlation diagram for the prediction of bacterial concentration in fermentation broth using a DS2500 Solid Analyzer. The lab value was evaluated using UV-Vis spectrophotometry.
Figure 4. Correlation diagram for the prediction of bacterial concentration in fermentation broth using a DS2500 Solid Analyzer. The lab value was evaluated using UV-Vis spectrophotometry.
Table 3. Figures of merit for the prediction of bacterial concentration in fermentation broth using a DS2500 Solid Analyzer.
Figures of meritValue
R20.7086
Standard error of calibration4.6884 CFU/mL
Standard error of cross-validation4.7429 CFU/mL
Standard error of validation5.0916 CFU/mL

Result glucose content in fermentation broths

Correlation diagram for the prediction of glucose concentration in fermentation broth using a DS2500 Solid Analyzer. The lab value was evaluated using HPLC.
Figure 5. Correlation diagram for the prediction of glucose concentration in fermentation broth using a DS2500 Solid Analyzer. The lab value was evaluated using HPLC.
Table 4. Figures of merit for the prediction of glucose content in fermentatoin broth using a DS2500 Solid Analyzer.
Figures of meritValue
R20.9165
Standard error of calibration0.6938%
Standard error of cross-validation0.7896%
Standard errror of validation0.8628%

Result reducing sugars content in fermentation broths

Correlation diagram for the prediction of reducing sugars in fermentation broth using a DS2500 Solid Analyzer. The lab value was evaluated using HPLC.
Figure 6. Correlation diagram for the prediction of reducing sugars in fermentation broth using a DS2500 Solid Analyzer. The lab value was evaluated using HPLC.
Table 5. Figures of merit for the prediction of sugars content in fermentation broth using a DS2500 Solid Analyzer.
Figures of meritValue
R20.9863
Standard error of calibration0.4767%
Standard error of cross-validation0.6821%
Standard error of validation1.2429%

Result potency in fermentation broths

Correlation diagram for the prediction of potency in fermentation broth using a DS2500 Solid Analyzer. The lab value was evaluated using UV-Vis spectrophotometry.
Figure 7. Correlation diagram for the prediction of potency in fermentation broth using a DS2500 Solid Analyzer. The lab value was evaluated using UV-Vis spectrophotometry.
Table 6. Figures of merit for the prediction of potency in fermentation broth using a DS2500 Solid Analyzer.
Figures of meritValue
R20.9083
Standard error of calibration2295 u/mL
Standard error of cross-validation2968 u/mL
Standard error of validation2089 u/mL

Result potency in fermentation broths

Correlation diagram for the prediction of potency in fermentation broth using a DS2500 Solid Analyzer. The lab value was evaluated using HPLC + PCR.
Figure 8. Correlation diagram for the prediction of potency in fermentation broth using a DS2500 Solid Analyzer. The lab value was evaluated using HPLC + PCR.
Table 7. Figures of merit for the prediction of potency in fermentation broth using a DS2500 Solid Analyzer.
Figures of meritValue
R20.9156
Standard error of calibration1913 u/mL
Standard error of cross-validation2172 u/mL
Standard error of validation1168 u/mL

Conclusion

This application note demonstrates the feasibility to determine key parameters of the quality control of the fermentation process with NIR spectroscopy. The main advantages of Vis-NIR spectroscopy over wet chemical methods are that running costs are significantly lower and time-to-result is significantly reduced. Additionally, no chemicals are required, and the technique is non-destructive to the samples.

Table 8. Time to result overview for the different quality parameters
ParameterMethodTime to result
pHpH Meter∼ 3–5 minutes
Bacterial concentrationUV-Vis∼ 8 hours (sample preparation) + ∼ 1 minute (UV-Vis)
Glucose and reducing sugars concentrationHPLC∼ 30–45 minutes
PotencyUV-Vis∼ 7minutes (sample preparation) + ∼ 1 minute (UV-Vis)
PotencyHPLC + PCR∼ 1hour (sample preparation) + ∼ 20 minutes (HPLC + PCR)
İletişim

Metrohm Turkey

Ayazağa Mah. Azerbaycan Cad. No. 3I
34396 İstanbul

İletişim

Internal reference: AW NIR CN-0017-112021