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Simultaneous Quantitative Analysis of a Three-Drug Combination Using Synchronous Fluorescence Spectroscopy and Chemometrics


Affiliations
1 Department of Chemistry, Savitribai Phule Pune University, Ganeshkhind Road, Pune 411 007, India
 

Establishing precise and accurate analytical methods for multicomponent analysis using time- and cost-effective ways are highly advantageous. Here, syn-chronous fluorescence spectroscopic method is coupled with chemometric tools in order to achieve simultaneous quantitative analysis of a three-component system consisting of metoprolol, propranolol and amiloride. Chemometric methods such as principal component regression and partial least squares re-gression were applied to the fluorescence data. Root mean square error values, correlation coefficient and limit of detection were used to judge the potential of the model for prediction. The proposed method worked well for simultaneous analysis of the three-drug system in the presence of strong serum albumin signals.

Keywords

Three-Drug System, Partial least Squares Regression, Principal Component Regression, Synchronous Fluorescence Spectroscopy.
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  • Simultaneous Quantitative Analysis of a Three-Drug Combination Using Synchronous Fluorescence Spectroscopy and Chemometrics

Abstract Views: 333  |  PDF Views: 119

Authors

Mandakini A. Shinde
Department of Chemistry, Savitribai Phule Pune University, Ganeshkhind Road, Pune 411 007, India
Ottoor Divya
Department of Chemistry, Savitribai Phule Pune University, Ganeshkhind Road, Pune 411 007, India

Abstract


Establishing precise and accurate analytical methods for multicomponent analysis using time- and cost-effective ways are highly advantageous. Here, syn-chronous fluorescence spectroscopic method is coupled with chemometric tools in order to achieve simultaneous quantitative analysis of a three-component system consisting of metoprolol, propranolol and amiloride. Chemometric methods such as principal component regression and partial least squares re-gression were applied to the fluorescence data. Root mean square error values, correlation coefficient and limit of detection were used to judge the potential of the model for prediction. The proposed method worked well for simultaneous analysis of the three-drug system in the presence of strong serum albumin signals.

Keywords


Three-Drug System, Partial least Squares Regression, Principal Component Regression, Synchronous Fluorescence Spectroscopy.



DOI: https://doi.org/10.18520/cs%2Fv108%2Fi7%2F1348-1354