Comparison of two augmented classical least squares algorithms and PLS for determining nifuroxazide and its genotoxic impurities using UV spectroscopy

Abstract

Concentration residual augmented classical least squares (CRACLS) and spectral residual augmented classical least squares (SRACLS) are reflecting the resolving power of spectrophotometric augmented mathematical techniques. The applied multivariate calibration methods were able to determine simultaneously the quinary mixture of nifuroxazide (NIF) and its four carcinogenic impurities, and a comparative study between the proposed models and the conventional partial least squares (PLS) algorithm was also done. Regression models were built covering the range of 10.00 to 50.00 μg mL−1 for NIF, 0.05 to 0.45 μg mL−1 (for each of impurities A and B), and 0.10 to 0.90 μg mL−1 (for impurities C and D). NIF and its four genotoxic impurities were successfully determined in the prepared mixtures and dosage forms. The efficiency of the applied algorithm for resolution and quantitation of the overlapped UV signals were compared, and the advantages over PLS mode were emphasized. The obtained results were statistically compared with each other along with those of the reported method.

Chemometrics-Assisted UV-Vis Spectrophotometry for Quality Control of Pharmaceuticals: A Review

“…Meanwhile, the concentration range of impurities A and B was 0.05 to 0.45 μg/mL and for impurities, C and D was 0.10 to 0.90 μg/mL. Result revealed that chemometrics of CRACLS, SRACLS, and PLSR was successfully used to determine NIF and its four impurities either in the pharmaceutical formulation or in the prepared mixtures [27].…”

Image of the distribution profile of targets in skin by Raman spectroscopy‐based multivariate analysis

“…Multivariable linear regression is a commonly used model for analysis of different components in complex system. Least squares (LS) analysis is commonly employed to resolve the problem 15–18 . As the concentration of each substance in the mixing system is positive, there will be negative numbers when solving the multivariate linear regression with LS.…”

“…Least squares (LS) analysis is commonly employed to resolve the problem. 15 , 16 , 17 , 18 As the concentration of each substance in the mixing system is positive, there will be negative numbers when solving the multivariate linear regression with LS. Therefore, LS with a nonnegative constraint was used to solve the problem for concentration analysis.…”