Design and Characterization of Acyclovir Loaded Nanoparticles for Controlled Delivery System

ISSN: 1875-6786 (Online)
ISSN: 1573-4137 (Print)


Volume 10, 6 Issues, 2014


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Design and Characterization of Acyclovir Loaded Nanoparticles for Controlled Delivery System

Author(s): Shadab Shahsavari, Ebrahim Vasheghani-Farahani, Mehdi Ardjmand and Farid Abedin Dorkoosh

Affiliation: Faculty of Pharmacy, Tehran University of Medical Sciences, Postal code: 1439956131, Tehran, Iran.

Abstract

The aim of this research was the preparation, optimization, and in-vitro characterization of acyclovir loaded chitosan nanoparticles. Experimental design D-optimal response surface methodology was used for the optimization of the nanoparticles. Therefore, the polymeric nano-drug controlled release system has been designed for varied variables such as the concentration of Acyclovir, concentration ratio of chitosan/ TPP and pH using the ionic gelation method. The optimized nanoparticles were characterized morphologically by Scanning Electron Microscopy (SEM), particle size analyzer (DLS) for determining size, zeta and PdI, Fourier Transform Infra-Red (FTIR) Spectroscopy for determination of chemical structure of nanoparticles molecules and Thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) for studying thermal behavior. The size of the optimized particles was detected to be 132 ± 24.3 nm; zeta potential was 32 ± 2.87 mV; PdI of particles was 0.159 ± 0.05; and calculated EE% was 85 ± 4.38%. SEM image shows segregated and non-aggregated nanoparticles with sub-spherical smooth morphology. An in-vitro release study of the prepared nanoparticles illustrated that the percentage of acyclovir released from the nanoparticles was 80.17 ± 2.45% within 48 hrs. Kinetic release profiles of acyclovir from nanoparticles appeared to fit best with Korsmeyer-Peppas and First-order models, the Fickian diffusion being premier phenomenon.




Keywords: Acyclovir, chitosan nanoparticles, d-optimal response surface experimental design methodology, drug delivery systems, in-vitro models, ionic gelation, oral drug delivery.

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Article Details

Volume: 10
Issue Number: 4
First Page: 521
Last Page: 531
Page Count: 11
DOI: 10.2174/15734137113096660128
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