Fingerprinting of morphine using chromatographic purity profiling and multivariate data analysis

Abstract

Chromatographic purity profiling (CPP) is the common name of a group of analytical and chemometric applications for detection, identification and quantitative determination of related substances and other impurities in active pharmaceutical ingredients (APIs) and finished dosage forms (FDFs). CPP is used for fingerprinting and discriminating between samples, thus representing a core activity in modern drug analysis. The worldwide demand for morphine and its congeners is tremendous and depends entirely on the supply of natural opiates. The aim of this research was to develop a methodology that enables identification of a source of morphine, thus revealing falsification of the substance. The characteristic and reproducible features of impurity profiles for 28 samples of morphine (6 morphine sulfate, 9 morphine hydrochloride and 13 morphine base) were captured by a new LC/MS method for impurity profiling of morphine. The impurity profile encompasses the related substances specified in relevant Ph.Eur. monographs, as well as the other morphinane like impurities, including the naturally occurring co-extracted alkaloids. Different pattern recognition techniques (unsupervised and supervised) were used to reveal the differentiation features of the morphine fingerprints for classification and authentication purposes. The results described in this research open the possibility of using the chromatographic purity profile combined with multivariate data analysis for fingerprinting of morphine samples.

Keywords: Active pharmaceutical ingredient fingerprinting; Chemometrics; Liquid chromatography/diode-array detection/mass spectrometry detection; Morphine; Pattern recognition techniques.