Non-target impurity profiling of marketplace Cetirizine using high-resolution mass spectrometry and multivariate data analysis.

Abstract

As always, drug impurity is the first concern of medication safety. The quality of pre- and post-marketed drugs is estimated through systematic analysis of potential hazardous substances by impurity profiling. Impurity profile is the general name of all unwanted materials which may affect the purity of an active pharmaceutical ingredient (API). The safety of original drugs is guaranteed by an enormous amount of animal experiments and clinical research while the safety of generic drugs should also be ensured by comparative analysis for consistency evaluation. The significantly differential impurities between them should be focused on and the toxicity should be further estimated if necessary. Herein, we take a marketplace drug named Cetirizine as an example to investigate if there was a method which could effectively discover the potential markers among Cetirizine tablets with different brands and describe specific impurity profiling which makes the unknown brand of Cetirizine tablets predictable. Liquid chromatography coupled with high-resolution mass spectrometry (LC/HRMS) was applied to capture the characteristic features of the impurity profile for three brands of marketplace Cetirizine tablets using full scan data-dependent MS/MS scan mode (FS-ddMS(2) ). Unsupervised learning: principal component analysis (PCA) and supervised learning: consensus orthogonal partial least squares discriminant analysis (OPLS-DA) were utilized to reveal the essential character of Cetirizine impurity profile; 16 differential impurities were finally found, their structures were speculated by HRMS(2) data. The cause of formation was further elucidated which gave a suggestion for production process optimization. Copyright © 2016 John Wiley & Sons, Ltd.