Rapid identification of oral solid dosage forms of counterfeit pharmaceuticals by discrimination using near-infrared spectroscopy.

Abstract

Since it can take an enormous amount of time and cost to discriminate counterfeit medicines by using conventional methods, counterfeit medicines has been spread in the world markets. The purpose of this study was to develop a rapid and simple analytical method to discriminate counterfeit drugs using near infrared (NIR) spectroscopy. Seven types of brand name tablet and generic tablets containing atorvastatin calcium sesquihydrate (AT) preparations were used as simulated counterfeit medicines. NIR spectra of 35 AT tablet products were measured using a diffuse reflection method. The NIR spectral data were analyzed by principal component analysis (PCA). The PCA results suggested that the model had sufficient accuracy to discriminate the 7 types for AT tablets. The NIR spectral data were also analyzed using a soft independent modeling of class analogy (SIMCA) method. Predicting the classification of the AT tablet samples was performed based on all the validated AT tablet data using the SIMCA model, and the probability of classification of 7 types was 100%. The discrimination power spectrum of the SIMCA model indicated significant patterns based on diluents. The PCA and SIMCA classification of the AT tablets were depended on the major excipient combinations.