Volume 26 , Issue 1 , June 2024 , Pages 5-16
1 Chemistry Department, College of Science, University of Sulaimani
The current study aims to utilize two different chemometrics approaches as data
assessment tools to analyze a quaternary combination in pure and pharmaceutical
dosage forms including four antidiabetic medications, Metformin (MET),
Empagliflozin (EMG), Vildagliptin (VGP), and Linagliptin (LGP). Both strategies were
utilized to decide on the variables to extract crucial information and improve the
accuracy of the procedures. The objective of this study is to determine the quantities of
four components at the same time, both the Principle Component regression (PCR) and
Partial Least Square (PLS-2) multivariate calibration techniques were effective. These
methods eliminated the need for a prior separation step, making them ideal for
pharmaceutical formulation analysis. The identification of the most advantageous
spectral ranges and combinations was accomplished through careful consideration of
various factors, including the minimization of the Root Mean Square Error of
Calibration (RMSEC) values with the range of 0.0392 to 0.3366, the Root Mean Square
Error of Prediction (RMSEP) values were within the range of 0.0419 to 0.3914, and the
Relative Error of Prediction (REP) values were ranging from 0.2756 to 0.9591. These
parameters were used to determine the optimal spectral regions that yielded the most
accurate and precise results. No statistically significant variations in results were
discovered between the suggested chemometric methodologies and the current official
procedures. The provided methodologies offer a powerful tool for rapid and precise
pharmaceutical formulation analysis, indicating their potential to improve quality
control operations in the industry.