Title of article :
Simultaneous spectrophotometric determination of paracetamol, phenylephrine and chlropheniramine in pharmaceuticals using chemometric approaches
Author/Authors :
Khoshayand, M.R. tehran university of medical sciences tums - Faculty of Pharmacy, and Pharmaceutical Sciences Research Center - Department of Food and Drug Control, تهران, ايران , Abdollahi, H. institute for advanced studies in basic sciences (iasbs) - Department of Chemistry, زنجان, ايران , Ghaffari, A. Chemidarou Pharmaceutical Company, ايران , Shariatpanahi, M. tehran university of medical sciences tums - Faculty of Pharmacy and Pharmaceutical Sciences Research Center - Department of Drug and Food Control, تهران, ايران , Farzanegan, H. tehran university of medical sciences tums - Faculty of Pharmacy and Pharmaceutical Sciences Research Center - Department of Drug and Food Control, تهران, ايران
Abstract :
Background and the purpose of the study: The linear multivariate calibration models such as principal components regression (PCR) and partial least squares regressions (PLS1 and PLS2) due to the mathematical simplicity and physical or chemical interpretability are sufficient and generally preferred method for analysis of multicomponent drugs. In this study, simultaneous determination of paracetamol, phenylephrine and chlorpheniramine in pharmaceuticals using chemometric methods and UV spectrophotometry is reported as a simple alternative technique. Material and methods: Principal components regression (PCR) and partial least squares regressions (PLS1 and PLS2) were used for chemometric analyses of data obtained from the spectra of paracetamol, phenylephrine and chlorpheniramine between wavelengths of 200 to 400 nm at several concentrations within their linear ranges. The analytical performance of these chemometric methods were characterized by relative prediction errors and recoveries (%) and compared with each other. Results: PCR, PLS1 and PLS2 were successfully applied to a tablet formulation, with no interference from excipients as indicated by the recovery. However, the PLS1 shows better results due to its flexibility and mathematical principals. Conclusion: The proposed methods are simple and rapid requiring no separation step, and can be easily used as an alternative in the quality control of drugs.
Keywords :
Principal components regression (PCR) , Partial least squares regressions (PLS1 , PLS2)
Journal title :
Daru:Journal of Pharmaceutical Sciences
Journal title :
Daru:Journal of Pharmaceutical Sciences