Article ID Journal Published Year Pages File Type
14647 Biotechnology Advances 2009 7 Pages PDF
Abstract

In recent years, much attention has been directed towards the development of global methods for on-line process monitoring, especially since the Food and Drug Administration (FDA) launched the Process Analytical Technology (PAT) guidance, stimulating biopharmaceutical companies to update their monitoring tools to ensure a pre-defined final product quality. The ideal technologies for biopharmaceutical processes should operate in situ, be non-invasive and generate on-line information about multiple key bioprocess and/or metabolic variables. A wide range of spectroscopic techniques based on in situ probes have already been tested in mammalian cell cultures, such as near infrared (NIR), mid infrared (MIR), 2D fluorescence and dielectric capacitance spectroscopy; similarly, the electronic nose technique based on chemical array sensors has been tested for in situ off-gas analysis of mammalian cell cultures. All these methods provide series of spectra, from which meaningful information must be extracted. In this sense, data mining techniques such as principal components regression (PCR), partial least squares (PLS) or artificial neural networks (ANN) have been applied to handle the dense flow of data generated from the real-time process analyzers. Furthermore, the implementation of feedback control methods would help to improve process performance and ultimately ensure reproducibility. This review discusses the suitability of several spectroscopic techniques coupled with chemometric methods for improved monitoring and control of mammalian cell processes.

Related Topics
Physical Sciences and Engineering Chemical Engineering Bioengineering
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