Chemometric methods application in pharmaceutical products and processes analysis and control - Computer-Aided Applications in Pharmaceutical Technology - page 77

laboratory-scale samples as calibration samples and pilot-scale samples
(powders and tablets) as model test samples. It was concluded that the
use of laboratory-scale samples to construct the calibration set is an
effective way to ensure the concentration variability in the development
of calibration models for industrial applications. Furthermore, the
optimal validation approach and the number of samples needed for
successful validation was studied.
Univariate and multivariate methods for processing Raman chemical
images were compared and used for analysis of pharmaceutical tablets
(Šašic´ et al., 2004; Šašic´, 2007). The study showed that quality of
compositional images was improved by the use of multivariate techniques.
Furthermore, it was demonstrated that some of the LVs of less importance
(e.g. 8th or 12th LV/PC) can carry information about excipients present
in low concentration in a pharmaceutical formulation (e.g. magnesium
stearate).
Possible sources of variation in a pharmaceutical granulation process
were investigated using the PCA method (Sochon et al., 2010).
A dissolution testing system for extended release tablets was validated
using multivariate analysis (Gottfries et al., 1994).
An interesting area of chemometrics application is in the biotechnology
industry. Review of chemometrics in bioprocess engineering and PAT
applications has been provided (Lopes et al., 2004). Chemometrics were
used for analysis of pyrolysis mass spectrometry data in α2-interferon
production (McGovern et al., 1999). Use of chemometrics in development
of an in-line monitoring system for bioprocessing was described
(Roychoudhury et al., 2006). Multivariate analysis tools for on-line
monitoring of bioprocesses were also reported (Amigo et al., 2008;
Schenk et al., 2007). Possibilities to avoid pitfalls with chemometrics in
the pharmaceutical and biotech industries are elaborated upon (Doherty
and Lange, 2006).

￿

￿ ￿

Example 1

A combination of experimental design, optimization, and
multivariate techniques was integrated into the process
development of a drug product (Huang et al., 2009). DoE effect
analysis was used to evaluate the interactions and effects of three
design factors (water amount, wet massing time, and lubrication