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to decide upon the optimal technique/method to be used for analysis.
Sometimes the simplest method is enough, so it is not necessary for more
complex tools to be introduced. Especially when chemometrics
application is in the fi eld of pharmaceuticals manufacturing and/or
control, care has to be taken that each step of development and
implementation of chemometrics tools is analyzed and discussed (Doherty
and Lange, 2006). Also, it is often highlighted that a reference model is
needed to confi rm results obtained by chemometrics analysis, which can
signifi cantly increase the need for resources.
One of the most often encountered pitfalls in application of
chemometrics (and any other modeling technique) is overfi tting of the
model. This means that a model with the apparent highest correlation
obtained during its development is chosen with no independent testing of
previously unseen data. Many of the traditional statistical tests assume
that the data obey normal distribution, which is not always the case in
real-life applications (Rajalahti and Kvalheim, 2011). With a greater
number of variables in comparison to sample numbers, overfi tting can
occur (Brereton, 2006).
Also an issue that is often neglected, but that can be the source of
serious misunderstanding, is discrepancy in terminology that is used for
algorithms and methods in different software packages. We have to
carefully analyze all the details of methods prior to comparison of results
obtained, using the same methodology but with different software tools.
4.3 Examples
Review of pharmaceutical applications, where advanced characterization
techniques are used in combination with multivariate data analysis
methods, is provided in relevant references (Gendrin et al., 2008;
De Beer et al., 2011; Gordon and McGoverin, 2011; Rajalahti and
Kvalheim, 2011).
4.3.1 Classifi cation methods
(qualitative applications)
Tablets of identical formulation, but produced on different sites, were
analyzed before and after storage, using NIR spectroscopy (NIRS). PCA
of NIR spectra was computed and the score plot confi rmed statistical
differences between the production sites, and the loadings identifi ed the
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