In‐line monitoring of amino acids in mammalian cell cultures using raman spectroscopy and multivariate chemometrics models

Abstract

In-line monitoring of amino acids in mammalian cell cultures using raman spectroscopy and multivariate chemometrics modelsThe application of PAT for in-line monitoring of biopharmaceutical manufacturing operations has a central role in developing more robust and consistent processes. Various spectroscopic techniques have been applied for collecting real-time data from cell culture processes. Among these, Raman spectroscopy has been shown to have advantages over other spectroscopic techniques, especially in aqueous culture solutions. Measurements of several process parameters such as glucose, lactate, glutamine, glutamate, ammonium, osmolality and VCD using Ramanbased chemometrics models have been reported in literature. The application of Raman spectroscopy, coupled with calibration models for amino acid measurement in cell cultures, has been assessed. The developed models cover four amino acids important for cell growth and production: tyrosine, tryptophan, phenylalanine and methionine. The chemometrics models based on Raman spectroscopy data demonstrate the significant potential for the quantification of tyrosine, tryptophan and phenylalanine. The model for methionine would have to be further refined to improve quantification.

Development of generic raman models for a GS‐KOTM CHO platform process

“…Several inline spectroscopic methods including Near Infrared (NIR), 2D‐Fluorescence, and Raman have been proposed for continuous cell culture monitoring . NIR measures the region between 800 and 2500 nm and collects information about the overtones of fundamental absorption bands observed in more traditional mid‐IR applications .…”

“…However, the Raman signal is generally lower compared to elastically scattered light (≈1,000 times less) and is sensitive to interference from fluorescent molecules which can lead to baseline offsets . Even with these limitations Raman spectroscopy, has seen increased use in applications for monitoring bioreactor process parameters in recent years . Furthermore, a recent evaluation by Rowland‐Jones et al comparing NIR, 2D‐fluorescence, and Raman identified Raman as more suitable for analysis of the contents of a miniature bioreactor …”

Decision Tree‐PLS (DT‐PLS) algorithm for the development of process: Specific local prediction models

“…In spectroscopy‐based bioprocess monitoring, it has been shown that numerous variables such as metabolites, cell density, and titer can be predicted based on the spectra . Recent examples illustrate the application of PLSR‐based calibration models to monitor several amino acids in cell culture processes …”

“…[24][25][26] Recent examples illustrate the application of PLSR-based calibration models to monitor several amino acids in cell culture processes. 27,28 However, linearity is one of the major limitations of the PLSR approach for bioprocessing analysis due to the high level of nonlinear dynamic effects. 18 Several studies attempted to overcome these by utilizing nonlinear data analysis approaches such as artificial neural networks (ANN).…”

Development of an on-line Raman spectral analytical method for monitoring and endpoint determination of the Cornu Caprae Hircus hydrolysis process

“…As a noninvasive and nondestructive process analytical technology (PAT) tool, Raman spectroscopy has attracted attention because it produces detailed molecular fingerprints with high chemical specificity, does not require sample preparation and is suitable for aqueous system analysis with only weak signals from water when compared with NIR spectroscopy. In a recent study conducted by Bhatia et al ., the significant potential of Raman spectroscopy for quantification of Tyr, Trp and Phe was demonstrated. Additionally, quantification and monitoring of Glu and other analytes by Raman spectroscopy in cell cultures have been reported in several studies .…”