Izvorni znanstveni članak

https://doi.org/10.5562/cca2214

Spectrophotometric Simultaneous Determination of Caffeine and Paracetamol in Commercial Pharmaceutical by Principal Component Regression, Partial Least Squares and Artificial Neural Networks Chemometric Methods

A. Hakan Aktaş orcid.org/0000-0003-2327-4031 ; Süleyman Demirel University, Science and Art Faculty, Department of Chemistry, 32260 Isparta – Turkey
Filiz Kitiş ; Süleyman Demirel University, Science and Art Faculty, Department of Chemistry, 32260 Isparta – Turkey

Sažetak

Three multivariate calibration-prediction techniques, principal component regression (PCR), partial least squares (PLS) and artificial neural networks (ANN) were applied to the spectrometric multicomponent analysis of the drug containing paracetamol (PCT) and caffeine (CAF) without any separation step. The selection of variables was studied. A series of synthetic solution containing different concentrations of PCT and CAF were used to check the prediction ability of the PCR, PLS and ANN. The results obtained in this investigation strongly encourage us to apply these techniques for a routine analysis and quality con-trol of the drug.(doi: 10.5562/cca2214)

Ključne riječi

paracetamol; caffeine; spectrometry; multivariate calibration

Hrčak ID:

122281

URI

https://hrcak.srce.hr/122281

Datum izdavanja:

30.4.2014.

Posjeta: 6.043 *