Cover image of the article: Formulation Optimization of Low Bioavailable Drug Loaded Alginate Microparticles Using Artificial Neural Networks

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Formulation Optimization of Low Bioavailable Drug Loaded Alginate Microparticles Using Artificial Neural Networks

Authors

Katayoun Derakhashandeh1, 2,*, Zahra Hamedi1, Moin Karimi1, Mahmood Amiri3, Farahnaz Ahmadi4
1Department of Pharmaceutics, Faculty of Pharmacy, Kermanshah University of Medical Sciences, Kermanshah, Iran
2Nano Drug Delivery Research Center, Faculty of Pharmacy, Kermanshah University of Medical Sciences, Kermanshah, Iran
3Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
4Department of Pharmacology and Toxicology, Faculty of Pharmacy, Kermanshah University of Medical Sciences, Kermanshah, Iran
*Corresponding Author: Corresponding author: Nano Drug Delivery Research Center, Faculty of Pharmacy, Kermanshah University of Medical Sciences, Kermanshah, Iran. Email:kderakhshandeh@kums.ac.ir

Journal of Reports in Pharmaceutical Sciences:Vol. 1, issue 1; 49-59
Published online:Apr 25, 2012
Article type:Research Article
Received:Mar 26, 2012
Accepted:Apr 19, 2012
How to Cite:Derakhashandeh K, Hamedi Z, Karimi M, Amiri M, Ahmadi F. Formulation Optimization of Low Bioavailable Drug Loaded Alginate Microparticles Using Artificial Neural Networks. J Rep Pharm Sci. 2012;1(1):e147805. doi:

Abstract

The adsorptive behavior of the immunosuppressive agent tacrolimus was studied by cyclic and differential-pulse voltammetry on a hanging mercury drop electrode (HMDE). The drug was accumulated at HMDE and two well-defined peak currents were obtained at -1353 and -1417 mV vs. SCE (saturated KCl) in borate buffer (pH 10.0) + 0.1 KCl solution. A voltammetric procedure was developed for the determination of tacrolimus using differential-pulse adsorptive stripping voltammetry (DPAdSV). The optimum working conditions for determination of the drug were established. The analysis of tacrolimus in pharmaceutical dosage forms was carried out satisfactorily. In the present study, sodium alginate microparticle for oral delivery of furosemide was designed whether the encapsulation into microparticles might improve the oral absorption of this potent loop diuretic. We described preparation of microspheres based on ionotropic gelation method and characterized its physicochemical properties.To acquire an optimum formulation, a Generalized Regression Neural Networks (GRNN) and a Multi-Layer Perceptron (MLP) were employed. The drug loaded formulation parameters were the input vectors of the GRNN and included the amount of polymer, cross linked agent, volume of external and internal phases. The microparticles drug loading, size and in vitro drug release constitute the output vector of each network. In this way, GRNN and MLP were trained to investigate the functional influence of input variables on the output responses. The results demonstrated that GRNN is promising in providing better solutions for optimization of drug delivery system formulation.The obtained optimum formulation showed a narrow size distribution on an average diameter of 700 ± 50 m and drug loading of more than 75%. The drug release profile illustrates a sustained released pattern and released percent of about 36% in 2 hour. In vitro drug release rate for microspheres was found to be sustained over 24 hours, obeying Higuchi order kinetic. Furthermore, the results of this paper confirmed that alginate microparticles could be a hopeful carrier for orally administration of furosemide and provides a sustained release property for this potent anti hypertension drug. In addition, the novel formulation design facilitates the optimization and successful development of microsphere formulations for enhanced safe and effective oral drug delivery. 

Highlights

Copyright

© 2012, Author(s). This open-access article is available under the Creative Commons Attribution 4.0 (CC BY 4.0) International License (https://creativecommons.org/licenses/by/4.0/), which allows for unrestricted use, distribution, and reproduction in any medium, provided that the original work is properly cited.

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