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Factors Affecting the Stability of Nanoemulsions—Use of Artificial Neural Networks

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Abstract

Purpose

The aim of this study was to identify the dominant factors affecting the stability of nanoemulsions, using artificial neural networks (ANNs).

Methods

A nanoemulsion preparation of budesonide containing polysorbate 80, ethanol, medium chain triglycerides and saline solution was designed, and the particle size of samples with various compositions, prepared using different rates and amounts of applied ultrasonic energy, was measured 30 min and 30 days after preparation. Using ANNs, data were modelled and assessed. The derived predictive model was validated statistically and then used to determine the effect of different formulation and processing input variables on particle size growth of the nanoemulsion preparation as an indicator of the preparation stability.

Results

The results indicated that the data can be satisfactorily modelled using ANNs, while showing a high degree of complexity between the dominant factors affecting the stability of the preparation.

Conclusion

The total amount of applied energy and concentration of ethanol were found to be the dominant factors controlling the particle size growth.

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Authors and Affiliations

  1. Institute of Pharmaceutical Innovation, School of Pharmacy, University of Bradford, BD7 1DP, Bradford, UK

    Amir Amani, Peter York & Brian J. Clark

  2. Department of Medical Nanotechnology, School of Advanced Medical Technologies, Tehran University of Medical Sciences, Tehran, 1417614411, Iran

    Amir Amani

  3. School of Applied Sciences, University of Huddersfield, HD1 3DH, Huddersfield, UK

    Henry Chrystyn

Authors
  1. Amir Amani
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  2. Peter York
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  3. Henry Chrystyn
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  4. Brian J. Clark
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Correspondence to Amir Amani.

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Amani, A., York, P., Chrystyn, H. et al. Factors Affecting the Stability of Nanoemulsions—Use of Artificial Neural Networks. Pharm Res 27, 37–45 (2010). https://doi.org/10.1007/s11095-009-0004-2

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  • DOI: https://doi.org/10.1007/s11095-009-0004-2

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