Herein, UV spectrophotometry assisted by multivariate chemometric analysis have been presented for quantitative determination of complex quinary therapy containing atenolol, ramipril, hydrochlorothiazide, simvastatin and aspirin without any prior separation. Such combination is very useful for treating various cardiovascular diseases (CVD) including high blood pressure, hypercholesterolemia in addition to its antiplatelet aggregating activity. Calibration (15 samples) and validation (10 samples) sets were prepared of different concentrations for these drugs via implementing partial factorial experimental design. The zero order UV spectra of these sets were recorded and then subjected for further chemometric analysis. Partial least square (PLS) with/without variable selection procedure i.e. genetic algorithm (GA) were employed to untangle the UV spectral overlapping of these mixtures. The performance of these chemometric techniques were compared in terms of accuracy and predictive abilities using cross-validation and external validation methods. It was found that PLS provides good recoveries with prompt predictive ability albeit GA-PLS exhibited better analytical performance owing to its capability to remove redundant variables i.e. the number of absorbance variables had been reduced to about 19-28%. The developed methods allowed reliable determination of such complex therapy in its laboratory prepared mixtures and pharmaceutical preparation within comparable results to those reported by HPLC method, posing these chemometric methods as valuable and indispensable analytical tools in in-process testing and quality control analysis of many pharmaceutical compounds targeting CVD.
Keywords: Cardiovascular diseases; Chemometrics; Genetic algorithm; Partial least square; Spectrophotometry.
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