Table of Contents
Chromatography Research International
Volume 2013 (2013), Article ID 315145, 12 pages
Research Article

Development and Validation of a Stability-Indicating RP-HPLC Method for the Simultaneous Estimation of Guaifenesin and Dextromethorphan Impurities in Pharmaceutical Formulations

1Analytical Research and Development, Integrated Product Development, Dr. Reddy’s Laboratories Limited, Bachupally, Hyderabad-500072, India
2School of Chemistry, Andhra University, Visakhapatnam, Andhra Pradesh 530003, India

Received 8 June 2013; Revised 9 August 2013; Accepted 9 August 2013

Academic Editor: Osama Y. Aldirbashi

Copyright © 2013 Thummala V. Raghava Raju et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A sensitive, stability-indicating gradient RP-HPLC method has been developed for the simultaneous estimation of impurities of Guaifenesin and Dextromethorphan in pharmaceutical formulations. Efficient chromatographic separation was achieved on a Sunfire C18, 250 × 4.6 mm, 5 µm column with mobile phase containing a gradient mixture of solvents A and B. The flow rate of the mobile phase was 0.8 mL min−1 with column temperature of 50°C and detection wavelength at 224 nm. Regression analysis showed an r value (correlation coefficient) greater than 0.999 for Guaifenesin, Dextromethorphan, and their impurities. Guaifenesin and Dextromethorphan formulation sample was subjected to the stress conditions of oxidative, acid, base, hydrolytic, thermal, and photolytic degradation. Guaifenesin was found stable and Dextromethorphan was found to degrade significantly in peroxide stress condition. The degradation products were well resolved from Guaifenesin, Dextromethorphan, and their impurities. The peak purity test results confirmed that the Guaifenesin and Dextromethorphan peak was homogenous and pure in all stress samples and the mass balance was found to be more than 98%, thus proving the stability-indicating power of the method. The developed method was validated according to ICH guidelines with respect to specificity, linearity, limits of detection and quantification, accuracy, precision, and robustness.