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Mohammad Reza Hadjmohammadi

Mohammad Reza Hadjmohammadi

Academic rank: Professor
ORCID:
Education: PhD.
ScopusId:
HIndex:
Faculty: Faculty of Chemistry
Address: Babolsar
Phone: 01135302350

Research

Title
Extraction of azathioprine drug from plasma samples by modified magnetic iron oxide nanoparticles and it’s determination by HPLC
Type
Presentation
Keywords
Azathioprine, magnetic nanoparticles, HPLC
Year
2018
Researchers Tahereh Harsij ، Mohammad Reza Hadjmohammadi ، Mohammad Hossein Fatemi

Abstract

In recent years modified iron oxide magnetic nanoparticles (MNPs) were used as new sorbents in analytical chemistry. They can interact with different analytes by π–π, dipole-dipole, Van der Waals, hydrogen bonding and ion-dipole interactions and thus MNPs is suitable for extraction of analytes with a wide range of polarity [1]. In the present work, application of MNPs, has been investigated for development of a ultrasound-assisted dispersive magnetic solid phase extraction (UADM-SPE) coupled with high performace liquid chromatography (HPLC) was developed for preconcentration and determination of azathioprine in plasma samples. In UADM-SPE the sorbent is dispersed under sonication in the sample solution, providing a high surface contact with the analyte. Then, due to its magnetic properties, the sorbent is easily isolated from the solution using a magnet. Subsequently, a suitable solvent is used for analytes’ desorption and the sample is then subjected to instrumental analysis [2]. The method provides important advantages such as fast, simple, inexpensive and environmentally friendly condition procedure [3]. MNPs were prepared through the co-precipitation method. Then, the synthesized nanoparticles were characterized by Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM) and X-ray diffraction (XRD) [4]. The variables affected the extraction efficiency of Azathioprine (i.e. amount of MNPs, pH, sample volume, temperature and sonication time) were screened by fractional factorial design to find significant variables and optimized by response surface methodology using the central composite design (CCD). Finally, under optimal conditions the method was applied for analysis of the Azathioprine in plasma samples and good results were obtained.