Determination of factors controlling the particle size and entrapment efficiency of noscapine in PEG/PLA nanoparticles using artificial neural networks

Karim S Shalaby,1 Mahmoud E Soliman,1 Luca Casettari,2 Giulia Bonacucina,3 Marco Cespi,3 Giovanni F Palmieri,3 Omaima A Sammour,1 Abdelhameed A El Shamy1,&dagger; 1Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmacy, Ain Shams University, Cairo, Egypt; 2Department of Biomo...

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Autores principales:	Shalaby KS, Soliman ME, Casettari L, Bonacucina G, Cespi M, Palmieri GF, Sammour OA, El Shamy AA
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2014
Materias:	Medicine (General) R5-920
Acceso en línea:	https://doaj.org/article/8b3268946fb54feabb850ec097b48dc2
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spelling	oai:doaj.org-article:8b3268946fb54feabb850ec097b48dc22021-12-02T00:37:09ZDetermination of factors controlling the particle size and entrapment efficiency of noscapine in PEG/PLA nanoparticles using artificial neural networks1178-2013https://doaj.org/article/8b3268946fb54feabb850ec097b48dc22014-10-01T00:00:00Zhttp://www.dovepress.com/determination-of-factors-controlling-the-particle-size-and-entrapment--peer-reviewed-article-IJNhttps://doaj.org/toc/1178-2013 Karim S Shalaby,1 Mahmoud E Soliman,1 Luca Casettari,2 Giulia Bonacucina,3 Marco Cespi,3 Giovanni F Palmieri,3 Omaima A Sammour,1 Abdelhameed A El Shamy1,&dagger; 1Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmacy, Ain Shams University, Cairo, Egypt; 2Department of Biomolecular Sciences, School of Pharmacy, University of Urbino, Urbino, Italy; 3School of Pharmacy, University of Camerino, Camerino, Italy &dagger;Abdel Hameed El-Shamy passed away on August 25, 2013 Abstract: In this study, di- and triblock copolymers based on polyethylene glycol and polylactide were synthesized by ring-opening polymerization and characterized by proton nuclear magnetic resonance and gel permeation chromatography. Nanoparticles containing noscapine were prepared from these biodegradable and biocompatible copolymers using the nanoprecipitation method. The prepared nanoparticles were characterized for size and drug entrapment efficiency, and their morphology and size were checked by transmission electron microscopy imaging. Artificial neural networks were constructed and tested for their ability to predict particle size and entrapment efficiency of noscapine within the formed nanoparticles using different factors utilized in the preparation step, namely polymer molecular weight, ratio of polymer to drug, and number of blocks that make up the polymer. Using these networks, it was found that the polymer molecular weight has the greatest effect on particle size. On the other hand, polymer to drug ratio was found to be the most influential factor on drug entrapment efficiency. This study demonstrated the ability of artificial neural networks to predict not only the particle size of the formed nanoparticles but also the drug entrapment efficiency. This may have a great impact on the design of polyethylene glycol and polylactide-based copolymers, and can be used to customize the required target formulations. Keywords: noscapine, polyethylene glycol (PEG), polylactide (PLA), biodegradable nanoparticles, artificial neural networks (ANNs)Shalaby KSSoliman MECasettari LBonacucina GCespi MPalmieri GFSammour OAEl Shamy AADove Medical PressarticleMedicine (General)R5-920ENInternational Journal of Nanomedicine, Vol 2014, Iss Issue 1, Pp 4953-4964 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine (General) R5-920
spellingShingle	Medicine (General) R5-920 Shalaby KS Soliman ME Casettari L Bonacucina G Cespi M Palmieri GF Sammour OA El Shamy AA Determination of factors controlling the particle size and entrapment efficiency of noscapine in PEG/PLA nanoparticles using artificial neural networks
description	Karim S Shalaby,1 Mahmoud E Soliman,1 Luca Casettari,2 Giulia Bonacucina,3 Marco Cespi,3 Giovanni F Palmieri,3 Omaima A Sammour,1 Abdelhameed A El Shamy1,&dagger; 1Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmacy, Ain Shams University, Cairo, Egypt; 2Department of Biomolecular Sciences, School of Pharmacy, University of Urbino, Urbino, Italy; 3School of Pharmacy, University of Camerino, Camerino, Italy &dagger;Abdel Hameed El-Shamy passed away on August 25, 2013 Abstract: In this study, di- and triblock copolymers based on polyethylene glycol and polylactide were synthesized by ring-opening polymerization and characterized by proton nuclear magnetic resonance and gel permeation chromatography. Nanoparticles containing noscapine were prepared from these biodegradable and biocompatible copolymers using the nanoprecipitation method. The prepared nanoparticles were characterized for size and drug entrapment efficiency, and their morphology and size were checked by transmission electron microscopy imaging. Artificial neural networks were constructed and tested for their ability to predict particle size and entrapment efficiency of noscapine within the formed nanoparticles using different factors utilized in the preparation step, namely polymer molecular weight, ratio of polymer to drug, and number of blocks that make up the polymer. Using these networks, it was found that the polymer molecular weight has the greatest effect on particle size. On the other hand, polymer to drug ratio was found to be the most influential factor on drug entrapment efficiency. This study demonstrated the ability of artificial neural networks to predict not only the particle size of the formed nanoparticles but also the drug entrapment efficiency. This may have a great impact on the design of polyethylene glycol and polylactide-based copolymers, and can be used to customize the required target formulations. Keywords: noscapine, polyethylene glycol (PEG), polylactide (PLA), biodegradable nanoparticles, artificial neural networks (ANNs)
format	article
author	Shalaby KS Soliman ME Casettari L Bonacucina G Cespi M Palmieri GF Sammour OA El Shamy AA
author_facet	Shalaby KS Soliman ME Casettari L Bonacucina G Cespi M Palmieri GF Sammour OA El Shamy AA
author_sort	Shalaby KS
title	Determination of factors controlling the particle size and entrapment efficiency of noscapine in PEG/PLA nanoparticles using artificial neural networks
title_short	Determination of factors controlling the particle size and entrapment efficiency of noscapine in PEG/PLA nanoparticles using artificial neural networks
title_full	Determination of factors controlling the particle size and entrapment efficiency of noscapine in PEG/PLA nanoparticles using artificial neural networks
title_fullStr	Determination of factors controlling the particle size and entrapment efficiency of noscapine in PEG/PLA nanoparticles using artificial neural networks
title_full_unstemmed	Determination of factors controlling the particle size and entrapment efficiency of noscapine in PEG/PLA nanoparticles using artificial neural networks
title_sort	determination of factors controlling the particle size and entrapment efficiency of noscapine in peg/pla nanoparticles using artificial neural networks
publisher	Dove Medical Press
publishDate	2014
url	https://doaj.org/article/8b3268946fb54feabb850ec097b48dc2
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Determination of factors controlling the particle size and entrapment efficiency of noscapine in PEG/PLA nanoparticles using artificial neural networks

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