Chemometric Assessment for Simultaneous Determination of the Quaternary Mixture - Abdullah, Ahmed Muhammed (Sulaimani Journal for Pure and Applied Sciences, 2024)
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.
Keywords: Chemometric Empagliflozin Linagliptin Metformin Partial Least Square