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. 2024 May 28:12:1349473.
doi: 10.3389/fbioe.2024.1349473. eCollection 2024.

Bioprocess monitoring applications of an innovative ATR-FTIR spectroscopy platform

Loren Christie #  1   2 , Samantha Rutherford  2 , David S Palmer  1   2 , Matthew J Baker  1   3 , Holly J Butler #  1
Affiliations

Bioprocess monitoring applications of an innovative ATR-FTIR spectroscopy platform

Loren Christie et al. Front Bioeng Biotechnol. .

Abstract

Pharmaceutical manufacturing is reliant upon bioprocessing approaches to generate the range of therapeutic products that are available today. The high cost of production, susceptibility to process failure, and requirement to achieve consistent, high-quality product means that process monitoring is paramount during manufacturing. Process analytic technologies (PAT) are key to ensuring high quality product is produced at all stages of development. Spectroscopy-based technologies are well suited as PAT approaches as they are non-destructive and require minimum sample preparation. This study explored the use of a novel attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy platform, which utilises disposable internal reflection elements (IREs), as a method of upstream bioprocess monitoring. The platform was used to characterise organism health and to quantify cellular metabolites in growth media using quantification models to predict glucose and lactic acid levels both singularly and combined. Separation of the healthy and nutrient deficient cells within PC space was clearly apparent, indicating this technique could be used to characterise these classes. For the metabolite quantification, the binary models yielded R 2 values of 0.969 for glucose, 0.976 for lactic acid. When quantifying the metabolites in tandem using a multi-output partial least squares model, the corresponding R 2 value was 0.980. This initial study highlights the suitability of the platform for bioprocess monitoring and paves the way for future in-line developments.

Keywords: bioprocess monitoring; bioprocessing; fourier transform infrared spectroscopy (FTIR); metabolite quantification; process analytical technology (PAT).

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Conflict of interest statement

Authors LC, DP, MB, and HB were employed by the Dxcover Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Qualitative analysis of CHO cells and CHO cell media (A) Offset spectra from nutrient deficient and healthy CHO cells in pellet form, (B) principal component analysis (PCA) scatterplot of the nutrient deficient and healthy cell spectra, (C) Offset spectra from corresponding nutrient deficient and healthy the supernatant CHO cell media, and (D) PCA of the corresponding nutrient deficient and healthy CHO cell media data.
FIGURE 2
FIGURE 2
Average spectral plot of DMEM cell media with increasing concentrations of glucose. 8, 10, 20, 30, 40, 60, 80, and 100 mg/mL.
FIGURE 3
FIGURE 3
(A) PLS model of predicted vs. observed concentration of glucose in DMEM cell media generated using a partial least squares model, and (B) corresponding leave-one-out cross validation partial least squares model.
FIGURE 4
FIGURE 4
Average spectral plot of DMEM cell media with increasing concentrations of lactic acid. 8, 10, 20, 30, 40, 60, 80, and 100 mg/mL.
FIGURE 5
FIGURE 5
(A) Calibration plot of predicted vs. observed concentration of lactic acid in DMEM cell media generated using a partial least squares model, and corresponding (B) cross validation partial least squares calibration plot.
FIGURE 6
FIGURE 6
Average spectral plot of DMEM cell media with alternating concentrations of glucose and lactic acid.
FIGURE 7
FIGURE 7
(A) Cross validation multi-output partial least squares models for glucose, and (B) lactic acid in DMEM cell media.
FIGURE A1
FIGURE A1
See this image and copyright information in PMC

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