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Determination of factors controlling the particle size in nanoemulsions using Artificial Neural Networks

Amani, Amir, York, Peter, Chrystyn, Henry, Clark, Brian J. and Do, Duong Q. (2008) Determination of factors controlling the particle size in nanoemulsions using Artificial Neural Networks. European Journal of Pharmaceutical Sciences, 35 (1-2). pp. 42-51. ISSN 09280987

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Abstract

The purpose of this study was to use Artificial Neural Networks (ANNs) in identifying factors, in addition to surfactant and internal phase content, that influence the particle size of nanoemulsions. The phase diagram and rheometric characteristics of a nanoemulsion system containing polysorbate 80, ethanol, medium chain triglycerides and normal saline loaded with budesonide were investigated. The particle size of samples of various compositions prepared using different rates and amounts of applied energy was measured. Data, divided into training, test and validation sets, were modelled by ANNs. The developed model was assessed and found to be of high quality. The model was then used to explore the effect of composition and processing factors on particle size of the nanoemulsion preparation. The study demonstrates the potential of ANNs in identifying critical parameters controlling preparation for this system, with the total amount of applied energy during preparation found to be the dominant factor in controlling the final particle size

Item Type: Article
Subjects: Q Science > Q Science (General)
Q Science > QD Chemistry
Schools: School of Applied Sciences
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Depositing User: Sara Taylor
Date Deposited: 19 Feb 2009 12:29
Last Modified: 12 Mar 2010 08:52
URI: http://eprints.hud.ac.uk/id/eprint/3429

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