Abstract

Drug impurities are now seen as a major threat to the production of pharmaceuticals around the world and a major part of the global contamination problem, especially when it comes to carcinogenic impurities. We present the first spectrophotometric strategy based on a combination of univariate and multivariate methods as impurity profiling methods for the estimation of lignocaine (LIG) and fluorescein (FLS) with their carcinogenic impurities: 2,6-xylidine (XYL) and benzene-1,3-diol (BZD). The data processing strategy depends on overcoming unresolved bands by employing five affordable, accurate, selective, and sensitive methods. The methods applied were a direct UV univariate spectrophotometric analysis (D0) and four multivariate chemometric methods, including classical least squares (CLS), principal component regression (PCR), partial least squares (PLS), and genetic algorithm (GA-PLS). FLS analysis (1-16 μg/mL) was performed using the D0 method at 478 nm; then, the application of the ratio subtraction method (RSM) allowed the removal of interference caused by the FLS spectrum. From the resulting ratio spectra, LIG, XYL, and BZD can be efficiently determined by chemometrics. The calibration set was carefully selected at five concentration levels using a partial factorial training design, resulting in 25 mixtures with central levels of 160, 40, and 3 μg/mL for LIG, XYL, and BZD, respectively. Another 13 samples were applied to validate the predictive ability. The statistical parameters demonstrated exceptional recoveries and smaller prediction errors, confirming the experimental model's predictive power. The proposed approach was effectively tested using newly FDA-approved LIG and FLS pharmaceutical preparation and aqueous humor. Additionally, it was effectively assessed for whiteness, greenness, and sustainability using five assessment tools. With its remarkable analytical performance, sustainability, affordability, simplicity, and cost-efficiency, the proposed strategy is an indispensable tool for quality control and in situ analysis in little-equipped laboratories, increasing the proposed approach's surveillance ability.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.