| Literature DB >> 26254602 |
Ali M Yehia1, Heba M Mohamed2.
Abstract
Three advanced chemmometric-assisted spectrophotometric methods namely; Concentration Residuals Augmented Classical Least Squares (CRACLS), Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) and Principal Component Analysis-Artificial Neural Networks (PCA-ANN) were developed, validated and benchmarked to PLS calibration; to resolve the severely overlapped spectra and simultaneously determine; Paracetamol (PAR), Guaifenesin (GUA) and Phenylephrine (PHE) in their ternary mixture and in presence of p-aminophenol (AP) the main degradation product and synthesis impurity of Paracetamol. The analytical performance of the proposed methods was described by percentage recoveries, root mean square error of calibration and standard error of prediction. The four multivariate calibration methods could be directly used without any preliminary separation step and successfully applied for pharmaceutical formulation analysis, showing no excipients' interference.Entities:
Keywords: Artificial Neural Networks; Chemometric methods; Guaifenesin; Paracetamol; Phenylephrine
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Year: 2015 PMID: 26254602 DOI: 10.1016/j.saa.2015.07.101
Source DB: PubMed Journal: Spectrochim Acta A Mol Biomol Spectrosc ISSN: 1386-1425 Impact factor: 4.098