APR Nov/Dec 2022 - 35

« SPECTROSCOPY
predictive 'global' glucose model that could be used at any location
using that specific set-up.
This powerful
tool can offer real-time tracking of the glucose
concentration throughout the bioprocess by analyzing the output.
Application of this model to a fourth site is illustrated in Figure 2,
showing how the glucose level steadily declines over time until a
specified minimum value is reached, rising again after the addition
of glucose. Using Raman spectroscopy this way ensured optimal
process control.
Summary
Raman spectroscopy has proven to be useful in various applications
in both research and manufacturing, including process control for
biopharmaceuticals,
where
it
offers
enhanced,
non-destructive
compositional measurements for a variety of sample types. This
technology has several advantages over other spectroscopic methods,
such as infrared and near-infrared spectroscopy, providing specificity,
compatibility with aqueous solutions, and sampling flexibility. In
addition, modern analyzers based on this technology are easier to use
compared to old models that required expert knowledge to operate.
These new systems are also smaller, which makes them perfect for
real-time monitoring of bioprocesses both in-line and on-line, as well
as for at-line and off-line measurements, opening up the technology
to more applications and facilities. When combined with data science
tools, Raman analysis can help manufacturers gain precise control over
their processes by monitoring relevant parameters such as glucose,
lactate, glutamine and glutamate, amino acids, pH, cell viability, and
cell volume. Ultimately, this will enable higher yield and quality of the
end product, while minimizing waste and reducing costs.
References
1.
Figure 2. Application of the glucose model to bioprocessing.
2.
Application note. In-line, on-line, at-line, or off-line: how solid-state Raman analyzers can
be adapted for any point of need. WP-RAMINALINE-0322 v01. Thermo Fisher Scientific.
Application note. Using process Raman and data science to gain actionable information for
glucose monitoring. AN-RAMINA-0522 v01. Thermo Fisher Scientific.
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APR Nov/Dec 2022

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