Author/Authors :
Bahrami, Gholamreza Medical Biology Research Center - Kermanshah University of Medical Sciences, Kermanshah, Iran , Nabiyar, Hamid Student Research Committee - Kermanshah University of Medical Sciences, Kermanshah, Iran , Sadrjavadi, Komail Pharmaceutical Sciences Research Center - School of Pharmacy - Kermanshah University of Medical Sciences, Kermanshah, Iran , Shahlaei, Mohsen Nano Drug Delivery Research Center - School of Pharmacy - Kermanshah University of Medical Sciences, Kermanshah, Iran
Abstract :
This study describes a simple and rapid approach of monitoring ibuprofen (IBP). Unfolded
principal component analysis-artificial neural network (UPCA-ANN) and excitation-emission
spectra resulted from spectrofluorimetry method were combined to develop new model in
the determination of IBF in human serum samples. Fluorescence landscapes with excitation
wavelengths from 235 to 265 nm and emission wavelengths in the range 300–500 nm were
obtained. The figures of merit for the developed model were evaluated. High performance
liquid chromatography (HPLC) technique was also used as a standard method. Accuracy of the
method was investigated by analysis of the serum samples spiked with various concentration
of IBF and an average relative error of prediction of 0.18% was obtained. The results indicated
that the proposed method is an interesting alternative to the traditional techniques normally
used for determination of IBF such as HPLC.
Keywords :
Data Reduction , Artificial neural network , Principal component analysis , Excitation-emission fluorescence matrices , Ibuprofen
