AN-NIR-099

2021-12

Quality Control of fermentation broths

Multiparameter determination within one minute

概要

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

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 DS2500	6.7430.040
Vision Air 2.0 Complete	6.6072.208

DS2500 Solid Analyzer

2.922.0010

ラボおよび生産環境における品質管理用の堅牢な近赤外分光法。DS2500 Analyzerは、生産チェーン全体に沿った固形物、クリーム、およびオプションとしての液体のルーチン分析に実績のあるフレキシブルなソリューションです。頑丈な仕様により、DS2500 Analyzerは粉塵、湿気、振動や温度変動に強い為、過酷な生産環境での使用に理想的です。DS2500は400 ～ 2500 nmのスペクトル範囲全体をカバーし、1分以内に正確で再現性の高い結果を提供します。DS2500 Analyzerは製薬業界の要件を満たしており、簡単な操作により日常的な作業においてユーザーをサポートします。装置に完全に適応した付属品により、　顆粒のような粒の荒い固形物、またはクリームのような半固形液体サンプルなどのあらゆる困難なタイプのサンプルにおいても、最良の結果を得ることができます。固形物の測定においては、9つまでのサンプルのシリーズの自動測定を可能にするMultiSample Cupを使用することで、生産性を高めることができます。

NIRSトランスフレクション容器、オプティカルフラット

6.7401.000

液体のスペクトル測定のためのオプティカルフラットのトランスフレクション容器。以下の装置との組み合わせが可能です:NIRS DS2500 Analyzer (注文番号: 2.922.0010); NIRS XDS MasterLab Analyzer (注文番号: 2.921.1310); NIRS XDS MultiVial Analyzer (注文番号: 2.921.1120); NIRS XDS RapidContent Analyzer (注文番号: 2.921.1110); NIRS XDS RapidContent Analyzer - Solids (注文番号: 2.921.1210);

DS2500 ホルダー

6.7430.040

以下のものに用いられるホルダー:サンプル容器小 (6.7402.030); DS2500 Iris (6.7425.100);

Vision Air 2.0 Complete

6.6072.208

Vision Air - 汎用性に優れた分光法ソフトウェア。Vision Air Complete は、規制環境下での使用のための、操作の容易な最新のソフトウェアソリューションです。Vision Air の利点の概要: 調整済みのユーザーインターフェースを伴う個別のソフトウェアアプリケーションにより、直観的かつ容易な操作が保証されます。; 作業手順の容易な作成およびメンテナンス; 安全かつ容易なデータ管理のための SQL データベース; バージョン Vision Air Complete (66072208) には、可視近赤外分光法を用いた品質管理のための全てのアプリケーションが含まれています: 装置管理およびデータ管理のためのアプリケーション; メソッド開発のためのアプリケーション; ルーチン分析のためのアプリケーション; その他の Vision Air Complete ソリューション: 66072207 (Vision Air Network Complete); 66072209 (Vision Air Pharma Complete); 66072210 (Vision Air Pharma Network Complete);

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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.

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 merit	Value
R²	0.6461
Standard error of calibration	0.1645
Standard error of cross-validation	0.1686
Standard error of validation	0.0997

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 merit	Value
R²	0.7086
Standard error of calibration	4.6884 CFU/mL
Standard error of cross-validation	4.7429 CFU/mL
Standard error of validation	5.0916 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 merit	Value
R²	0.9165
Standard error of calibration	0.6938%
Standard error of cross-validation	0.7896%
Standard errror of validation	0.8628%

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 merit	Value
R²	0.9863
Standard error of calibration	0.4767%
Standard error of cross-validation	0.6821%
Standard error of validation	1.2429%

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 merit	Value
R²	0.9083
Standard error of calibration	2295 u/mL
Standard error of cross-validation	2968 u/mL
Standard error of validation	2089 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 merit	Value
R²	0.9156
Standard error of calibration	1913 u/mL
Standard error of cross-validation	2172 u/mL
Standard error of validation	1168 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
Parameter	Method	Time to result
pH	pH Meter	∼ 3–5 minutes
Bacterial concentration	UV-Vis	∼ 8 hours (sample preparation) + ∼ 1 minute (UV-Vis)
Glucose and reducing sugars concentration	HPLC	∼ 30–45 minutes
Potency	UV-Vis	∼ 7minutes (sample preparation) + ∼ 1 minute (UV-Vis)
Potency	HPLC + PCR	∼ 1hour (sample preparation) + ∼ 20 minutes (HPLC + PCR)