American Journal of Applied Sciences

Determination of Ibuprofen and Paracetamol in Binary Mixture Using Chemometric-Assisted Spectrophotometric Methods

Wafaa S. Hassan

DOI : 10.3844/ajassp.2008.1005.1012

American Journal of Applied Sciences

Volume 5, Issue 8

Pages 1005-1012

Abstract

Three methods are presented for simultaneous determination of ibuprofen and paracetamol without previous separation. The first method depends on first derivative UV spectrophotometry, with zero-crossing measurement. The first derivative amplitudes at 230 and 290 nm were selected for the assay of ibuprofen and paracetamol, respectively. The second method depends on first derivative of the ratio-spectra by measurements of the amplitudes at 280 and 290 nm for ibuprofen and paracetamol, respectively. Calibration graphs were established in the range of 5-100 and 10-100 µg mL-1 for ibuprofen and paracetamol, respectively. The third method is the use of multivariate spectrophotometric calibration for the simultaneous determination of the analyzed mixture. The resolution of the studied binary mixture has been accomplished by using partial least squares (PLS) regression analysis. Although the components show an important degree of spectral overlap, they have been simultaneously determined with high accuracy, with no interference from pharmaceutical dosage form excipients. A comparison is presented with the related multivariate method of classical least squares (CLS) analysis, which is shown to yield less reliable results due to severe spectra overlap presented by the studied compounds. All of the proposed methods have been extensively validated. These methods allow a number of cost and time saving benefits. The described methods can be readily utilized for analysis of pharmaceutical formulations. There was no significant difference between the performance of all of the proposed methods regarding the mean values and standard deviations.

Copyright

© 2008 Wafaa S. Hassan. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.