A novel eco-friendly methods for simultaneous determination of aspirin, clopidogrel, and atorvastatin or rosuvastatin in their fixed-dose combination using chemometric techniques and artificial neural networks

Abstract

In this study, the simultaneous determination of aspirin, clopidogrel, and either atorvastatin or rosuvastatin in their fixed-dose combination (FDC) formulations has been reported. As a straightforward substitute for employing distinct models for each component, UV spectrophotometry was applied with chemometric approaches and artificial neural networks to achieve this. Three chemometric techniques, including principal component regression (PCR), partial least-squares (PLS), and classical least-squares (CLS), were applied in addition to the radial basis function-artificial neural network (RBF-ANN). The validation of a set of laboratory-prepared combinations of aspirin, clopidogrel, and atorvastatin in one ternary mixture and aspirin, clopidogrel, and rosuvastatin in a second ternary mixture was assessed, and the results from the use of these approaches were recorded and compared. The absorbance data matrix matching the concentration data matrix in CLS, PCR, and PLS was created using measurements of absorbances in the range of 250–280 nm at intervals of 0.2 nm in their zero-order spectra. Then, in order to forecast the unknown concentrations, calibration or regression was created utilizing the concentration and absorbance data matrices. Using RBF-ANN for the simultaneous determination of aspirin, clopidogrel, and atorvastatin or rosuvastatin in their formulations was achieved by providing the input layer with 151 neurons; there are 2 hidden layers and 3 output neurons were obtained. The green profile of the developed methods has been assessed and compared with previously reported spectrophotometric methods. The suggested techniques were effectively applied to FDC dosage forms that contained the cited medications.