Abstract

Spectrophotometric data analysis using multivariate approaches has many useful applications. One of these applications is the analysis of active ingredients in presence of impurities. Four chemometric-assisted spectrophotometric methods, namely, principal component regression (PCR), partial least-squares (PLS), artificial neural networks (ANN) and multivariate curve resolution-alternating least squares (MCR-ALS) were proposed and validated. The developed chemometric methods were compared to resolve the severely overlapped spectrum of Paracetamol (PAR) and Phenylephrine HCl (PHE) along with PAR impurities namely, P-Aminophenol (PAP), P-Nitrophenol (PNP), Acetanilide (ACT) and P-Chloroacetanilide (CAC). The four multivariate calibration methods succeeded in simultaneous determination of PAR and PHE with further quantification of PAR impurities. So, the proposed methods could be used with no need of any separation step and successfully applied for pharmaceutical formulation analysis. Furthermore, statistical comparison between the results obtained by the proposed chemometric methods and the official ones showed no significant differences.

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.