Determination of benazepril HCl and hydrochlorothiazide in pharmaceutical preparations using UV-visible spectrophotometry and genetic multivariate calibration method

Abstract

Simultaneous determination of binary mixtures of benazepril and hydrochlorothiazide in pharmaceutical tablets using uV-visible spectrophotometry, classical least squares (cLS) and three genetic algorithms (GA) based multivariate calibration methods was demonstrated. The three genetic multivariate calibration methods are Genetic classical Least Squares (GcLS), Genetic Inverse Least Squares (GILS) and Genetic Regression (GR). The sample data set contains the uV-spectra of 28 synthetic mixtures of benazepril (12~36 µg/mL) and hydrochlorothiazide (10~22 µg/mL) and 16 tablets containing both compounds. The spectra cover the range from 210 to 360 nm in 0.1 nm intervals. Several calibration models were built with the four methods. The root mean square error of calibration (RMSEc) and validation (RMSEV) for the synthetic data were in the range of 0.19 and 0.34 µg/mL for all the genetic algorithm based methods. The root mean square error of Prediction (RMSEP) values for the tablets were in the range of 0.04~0.20 mg/tablets. A comparison of genetic algorithm selected wavelengths for each component was also included.

Stability Indicating Uplc Method for Estimation of Benazepril and Hydrochlorothiazide in Bulk and Combined Dosage Form

“…By lowering certain molecules that harden blood vessels, it increases blood flow. Few UV [5][6][7][8][9], HPTLC [10][11][12], and HPLC [13][14][15][16][17][18][19][20][21][22][23][24][25] procedures for BZP and HTZ in bulk and formulations with other medications have been described, according to a study of the literature. In order to estimate BZP and HTZ in bulk and formulations, a stability-indicating chromatographic approach has been developed.…”

Near infrared spectroscopic determination of olive oil adulteration with sunflower and corn oil

“…GILS follows the same basic initialize/ breed/mutate/evaluate algorithm as other GA's to select a subset of wavelengths which is unique in the way it encodes genes. Detailed working principles of GILS were described elsewhere (19)(20)(21) but for completeness, a brief outline was given here. Following is a flow chart for the GILS algorithm used in this study.…”

“…Genetic Inverse Least Squares (GILS) is a modified version of original ILS method in which a small set of wavelengths are selected from a full spectral data matrix. It has evolved to an optimum solution using a genetic algorithm (GA) and has been applied to a number of wavelength selection problems (19)(20)(21)(22)(23) . GA's are non-local search and optimization methods that are based upon the principles of natural selection (24)(25)(26) .…”