Multicomponent spectrometric analysis of drugs and their preparations.

Abstract

Pharmaceutical preparations may contain a single ingredient or multi-ingredients as well as excipients. In multicomponent systems, specific analytical methods are required to determine the concentrations of individual components in the presence of interfering substances. Ultraviolet and visible spectrometric methods have widely been developed for the analysis of drugs in mixtures and pharmaceutical preparations. These methods are based on ultraviolet and visible multicomponent analysis and chemometrics (multivariate data analysis). The commonly used chemometric methods include principal component analysis (PCA); regression involving classical least squares (CLS), partial least squares (PLS), inverse least squares (ILS), principal component regression (PCR), multiple linear regression (MLR), artificial neural networks (ANNs); soft independent modeling of class anthology (SIMCA), PLS-discriminant analysis (DA); and functional data analysis (FDA). In this chapter, the applications of multicomponent ultraviolet and visible, derivative, infrared and mass spectrometric and spectrofluorimetric methods to the analysis of multi-ingredient pharmaceutical preparations, biological samples and the kinetics of drug degradation have been reviewed. Chemometric methods provide an efficient solution to calibration problems in the analysis of spectral data for the simultaneous determination of drugs in multicomponent systems. These methods facilitate the assessment of product quality and enhance the efficiency of quality control systems.