An Advanced Monitoring Platform for Rational Design of Recombinant Processes - Measurement, Monitoring, Modelling, and Control of Bioprocesses - page 68

important process variables as well as automatic process control techniques are
well established [ 2 ]. The main reasons for this difference are that cell-based
processes are far more complex than pure chemical processes, that real-time access
to physiologically relevant variables is not available, and that proteins as products
are large molecules that are extremely sensitive to the manufacturing process.
In spite of significant progress in sensor and analyzer technologies, only a few
systems have been qualified for bioprocess monitoring [ 3 - 5 ]. The main challenge
in this context is to perform measurements under common bioprocess conditions in
a sterile environment with living cells as a solid phase in a gas-liquid mixture.
Currently, routine online data acquisition is focused on classical variables such as
pH, pO 2 , pCO 2 , rpm, air flow, stirrer speed, temperature, flow rates, and analysis of
O 2 /CO 2 in exhaust gas (cf. the chapter by Sonnleitner). Exhaust gas analysis can
be used to calculate the oxygen uptake rate (OUR), the carbon dioxide evolution
rate (CER), and the respiration quotient (RQ), but none of the state variables
provide metabolism-related information [ 6 ]. State-of-the-art online monitoring
tools, such as infrared spectroscopy [ 7 - 9 ], fluorescence spectroscopy [ 10 - 13 ], and
dielectric spectroscopy [ 14 , 15 ], reflect changes in the process, but signals cannot
be directly assigned to biological process variables and host cell physiology [ 16 ].
More advanced methods include the application of analyzer technologies
connected to the bioreactor via accurate interfaces, such as high-performance
liquid chromatography [ 17 , 18 ], gas chromatography [ 19 ], mass spectrometry [ 20 ],
or flow cytometry [ 21 , 22 ]. By following such strategies, timely information on
metabolites, intermediate compounds, or end-products of metabolism excreted to
the medium can be obtained. Each of these at-line technologies requires a sam-
pling procedure, sample preparation steps, and a certain time to run the analysis.
In this sense, such applications represent the link to offline analysis.
Quantitative and qualitative data on intracellular components definitely yield
the highest level of physiology-related information, but are not accessible via
direct online measurements [ 23 ]. To gain this essential process information,
sample preparation steps and biochemical analysis are required.
Setting up an offline measurement platform is a nontrivial task as the set of
selected techniques (i) must cover the wide diversity of all molecules of interest
and (ii) should allow high sampling frequencies combined with low sample vol-
umes, and (iii) cost-time demands must not exceed justifiable quantities. For more
or less all molecule classes in a cellular system, various analytical methods are
available but only a limited number meet the above-mentioned criteria. Hence,
careful selection and combination of methods is imperative. Directly related to the
analytical method and the analyte is the sampling strategy. Accurate sampling
and quenching procedures are of highest priority to guarantee representative
samples, and the sampling frequency must allow for adaptation to the expected
kinetics of molecules of interest. Progress in this field has been strongly sup-
ported by systems-biology-based approaches and the development of -omics
techniques [ 24 , 25 ].
The shortcomings in real-time access to physiology-relevant variables can be
circumvented by application of chemometric-based approaches. As mentioned,