Thesis final - after defense-7 - Jacobs University

Chapter 1
followed by its introduction into the market. It has been reported that in silico approaches can
help to make decisions and simulate about certain pharmaceutical processes which can further
reduce the space between pharmaceutical and engineering based disciplines (84). To develop
the computational models, it is necessary to have enough experimental data in the databases.
These computational models can be exploited to predict about any biological process. The in
silico approach has been reported to play its role as a complement to in vitro and in vivo
experimentation (83). The upstream and downstream processes need to be improved utilizing
the in silico approaches. The advances in the upstream processes such as fermentation have
been already achieved and a product can be produced in several grams instead of milligrams
due to the introduction of genetic engineering technologies (85). However, the major
bottleneck still exists in the downstream processing of bioproducts. The current lack of the
accurate data about the bioseparation of the products and the structural implications of the
bioproducts are the main hurdles to design the purification models. A downstream approach
has been proposed to collect the experimental data to design models for the improvement of
the in silico approach (Figure 5). To collect the experimental data using modern mass
spectrometry based proteomics tools after crude fractionation are highly required to design
efficient bioprocesses (86). However, the in silico approach has been rarely reported in the
downstream processing of proteins and the reason could be the lack of information with the
real expression systems. Mostly model proteins were used to produce data and that data was
then used to predict about the retention behavior of the other model proteins using
mathematical models. The next step was then to compare the experimental retention time with
that of predicted ones. In case of deviations from the predicted one, certain parameters have to
be changed accordingly to calibrate the computer model. Once the model has been calibrated,
no further investigations are required and the researcher can simulate the separation behavior
of proteins on computer.
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