Raman Spectroscopy for Quantitative Analysis in the Pharmaceutical Industry

Jesus, José Izo Santana da Silva de; Löbenberg, Raimar; Bou‐Chacra, Nádia Araci

doi:10.18433/jpps30649

Cited by 24 publications

(12 citation statements)

References 93 publications

(147 reference statements)

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“…Raman spectroscopy has been one of the most important PAT tools for enabling efficient process monitoring and control in pharmaceutical and biopharmaceutical industry. There are numerous reports on successful application of Raman spectroscopy for various online, inline, or at‐line analysis (Esmonde‐White et al, 2017; Jesus et al, 2020). In the biologics space, Raman spectroscopy is particularly attractive for in‐process analysis as it is highly compatible with aqueous environments and offers rich spectral information on biologics samples.…”

Section: Introductionmentioning

confidence: 99%

Robust platform for inline Raman monitoring and control of perfusion cell culture

Wan,

Patel,

Zhou

et al. 2024

Biotech & Bioengineering

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Perfusion cell culture has been gaining increasing popularity for biologics manufacturing due to benefits such as smaller footprint, increased productivity, consistent product quality and manufacturing flexibility, cost savings, and so forth. Process Analytics Technologies tools are highly desirable for effective monitoring and control of long‐running perfusion processes. Raman has been widely investigated for monitoring and control of traditional fed batch cell culture process. However, implementation of Raman for perfusion cell culture has been very limited mainly due to challenges with high‐cell density and long running times during perfusion which cause extremely high fluorescence interference to Raman spectra and consequently it is exceedingly difficult to develop robust chemometrics models. In this work, a platform based on Raman measurement of permeate has been proposed for effective analysis of perfusion process. It has been demonstrated that this platform can effectively circumvent the fluorescence interference issue while providing rich and timely information about perfusion dynamics to enable efficient process monitoring and robust bioreactor feed control. With the highly consistent spectral data from cell‐free sample matrix, development of chemometrics models can be greatly facilitated. Based on this platform, Raman models have been developed for good measurement of several analytes including glucose, lactate, glutamine, glutamate, and permeate titer. Performance of Raman models developed this way has been systematically evaluated and the models have shown good robustness against changes in perfusion scale and variations in permeate flowrate; thus models developed from small lab scale can be directly transferred for implementation in much larger scale of perfusion. With demonstrated robustness, this platform provides a reliable approach for automated glucose feed control in perfusion bioreactors. Glucose model developed from small lab scale has been successfully implemented for automated continuous glucose feed control of perfusion cell culture at much larger scale.

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Section: Introductionmentioning

confidence: 99%

Robust platform for inline Raman monitoring and control of perfusion cell culture

Wan,

Patel,

Zhou

et al. 2024

Biotech & Bioengineering

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“…Biological methods, as well as a majority of physicochemical techniques (chromatographic, electrophoretic) applied in quality control of these medicinal products are destructive, time-consuming, and require sample preparation. Vibrational spectroscopic techniques, including Raman spectroscopy and Fourier transform infrared spectroscopy (FTIR), are fast, powerful, and non-destructive techniques which, when combined with multivariate chemometric modelling, can provide specific identification, quantitative determination, and insight into the secondary structure of proteins and peptides (7)(8)(9)(10)(11).…”

Section: Introductionmentioning

confidence: 99%

PLS based quantitative determination of insulin aspart in solution using Raman spectroscopy

Godzo,

Gigopulu,

Geskovski

et al. 2024

Arhiv za farmaciju

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The complex structure of medicines containing polypeptide active substances requires the implementation of challenging analytical approaches, based on physicochemical methods, and, where necessary, biological assays for quality control, as well as for the detection of substandard and falsified products. Vibrational spectroscopic techniques, including Raman spectroscopy, are fast, powerful, and non-destructive techniques which, when combined with multivariate chemometric modelling, can provide specific identification, quantitative determination, and insight into the secondary structure of proteins and peptides. The aim of this study was to investigate the possibility of using Raman spectroscopy as a screening method for quantification of pharmaceutical products containing active substances with polypeptide structures. For that purpose, a model based on partial least square (PLS) analysis for quantitative determination of insulin aspart in solution was developed using Raman spectroscopy. The proposed model enables the establishment of a rapid approach for screening of the quality of formulations containing active substances with polypeptide structure, providing the selection of suspected samples that should be further analysed using routine techniques, which are time-consuming and costly.

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“…Furthermore, bioprocesses are highly sensitive to changes in the cultivation conditions, leading to a wide variety of possible process states (Hirsch et al, 2019). Therefore, developing and calibrating a robust statistical model usually requires several off‐line monitored calibration batches (André et al, 2017; Jesus et al, 2020; Webster et al, 2018). In this study, robustness is defined as the capability of an evaluation model to maintain accurate prediction quality for a wide variety of possible process states.…”

Section: Introductionmentioning

confidence: 99%

Bioprocess in‐line monitoring using Raman spectroscopy and Indirect Hard Modeling (IHM): A simple calibration yields a robust model

Müller

Flake

Brands

et al. 2023

Biotech & Bioengineering

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To increase the process productivity and product quality of bioprocesses, the in‐line monitoring of critical process parameters is highly important. For monitoring substrate, metabolite, and product concentrations, Raman spectroscopy is a commonly used Process Analytical Technology (PAT) tool that can be applied in‐situ and non‐invasively. However, evaluating bioprocess Raman spectra with a robust state‐of‐the‐art statistical model requires effortful model calibration. In the present study, we in‐line monitored a glucose to ethanol fermentation by Saccharomyces cerevisiae (S. cerevisiae) using Raman spectroscopy in combination with the physics‐based Indirect Hard Modeling (IHM) and showed successfully that IHM is an alternative to statistical models with significantly lower calibration effort. The IHM prediction model was developed and calibrated with only 16 Raman spectra in total, which did not include any process spectra. Nevertheless, IHM's root mean square errors of prediction (RMSEPs) for glucose (3.68 g/L) and ethanol (1.69 g/L) were comparable to the prediction quality of similar studies that used statistical models calibrated with several calibration batches. Despite our simple calibration, we succeeded in developing a robust model for evaluating bioprocess Raman spectra.

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Raman Spectroscopy for Quantitative Analysis in the Pharmaceutical Industry

Cited by 24 publications

References 93 publications

Robust platform for inline Raman monitoring and control of perfusion cell culture

Robust platform for inline Raman monitoring and control of perfusion cell culture

PLS based quantitative determination of insulin aspart in solution using Raman spectroscopy

Bioprocess in‐line monitoring using Raman spectroscopy and Indirect Hard Modeling (IHM): A simple calibration yields a robust model

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