Multiple response optimization applied to the development of a capillary electrophoretic method for pharmaceutical analysis.

Multiple response simultaneous optimization by using the desirability function was used for the development of a capillary electrophoresis method for the simultaneous determination of four active ingredients in pharmaceutical preparations: vitamins B(6) and B(12), dexamethasone and lidocaine hydrochloride. Five responses were simultaneously optimized: the three resolutions, the analysis time and the capillary current. This latter response was taken into account in order to improve the quality of the separations.

Monitoring substrate and products in a bioprocess with FTIR spectroscopy coupled to artificial neural networks enhanced with a genetic-algorithm-based method for wavelength selection.

An experiment was developed as a simple alternative to existing analytical methods for the simultaneous quantitation of glucose (substrate) and glucuronic acid (main product) in the bioprocesses Kombucha by using FTIR spectroscopy coupled to multivariate calibration (partial least-squares, PLS-1 and artificial neural networks, ANNs). Wavelength selection through a novel ranked regions genetic algorithm (RRGA) was used to enhance the predictive ability of the chemometric models. Acceptable results were obtained by using the ANNs models considering the complexity of the sample and the speediness and simplicity of the method.

Chemometrics-assisted UV-spectroscopic strategies for the determination of theophylline in syrups.

Two spectrophotometric methods, assisted by chemometric tools, were developed for the determination of theophylline in syrups: derivative spectroscopy (DS) and partial least-squares regression (PLS), the latter using both artificial and natural calibration sets. HPLC technique was employed to apply a reference method in order to achieve a complete assessment of performance. Calibrations presented excellent analytical figures of merits (i.