Automated Data Generation for Raman Spectroscopy Calibrations in Multi-Parallel Mini Bioreactors

Autor: Alexander Graf, Angus Woodhams, Michael Nelson, Douglas D. Richardson, Steven M. Short, Mark Brower, Marek Hoehse
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Sensors, Vol 22, Iss 9, p 3397 (2022)
Druh dokumentu: article
ISSN: 22093397
1424-8220
DOI: 10.3390/s22093397
Popis: Raman spectroscopy is an analytical technology for the simultaneous measurement of important process parameters, such as concentrations of nutrients, metabolites, and product titer in mammalian cell culture. The majority of published Raman studies have concentrated on using the technique for the monitoring and control of bioreactors at pilot and manufacturing scales. This research presents a novel approach to generating Raman models using a high-throughput 250 mL mini bioreactor system with the following two integrated analysis modules: a prototype flow cell enabling on-line Raman measurements and a bioanalyzer to generate reference measurements without a significant time-shift, compared to the corresponding Raman measurement. Therefore, spectral variations could directly be correlated with the actual analyte concentrations to build reliable models. Using a design of experiments (DoE) approach and additional spiked samples, the optimized workflow resulted in robust Raman models for glucose, lactate, glutamine, glutamate and titer in Chinese hamster ovary (CHO) cell cultures producing monoclonal antibodies (mAb). The setup presented in this paper enables the generation of reliable Raman models that can be deployed to predict analyte concentrations, thereby facilitating real-time monitoring and control of biologics manufacturing.
Databáze: Directory of Open Access Journals
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