An artificial neural network based analysis of factors controlling particle size in a virgin coconut oil-based nanoemulsion system containing copper peptide
A predictive model of a virgin coconut oil (VCO) nanoemulsion system for the topical delivery of copper peptide (an anti-aging compound) was developed using an artificial neural network (ANN) to investigate the factors that influence particle size. Four independent variables including the amount of...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science
2016
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| Online Access: | http://psasir.upm.edu.my/id/eprint/55017/1/An%20Artificial%20Neural%20Network%20Based%20Analysis.pdf |
| _version_ | 1796976189181526016 |
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| author | Samson, Shazwani Basri, Mahiran Fard Masoumi, Hamid Reza Abdul Malek, Emilia Karjiban, Roghayeh Abedi |
| author_facet | Samson, Shazwani Basri, Mahiran Fard Masoumi, Hamid Reza Abdul Malek, Emilia Karjiban, Roghayeh Abedi |
| author_sort | Samson, Shazwani |
| collection | UPM |
| description | A predictive model of a virgin coconut oil (VCO) nanoemulsion system for the topical delivery of copper peptide (an anti-aging compound) was developed using an artificial neural network (ANN) to investigate the factors that influence particle size. Four independent variables including the amount of VCO, Tween 80: Pluronic F68 (T80:PF68), xanthan gum and water were the inputs whereas particle size was taken as the response for the trained network. Genetic algorithms (GA) were used to model the data which were divided into training sets, testing sets and validation sets. The model obtained indicated the high quality performance of the neural network and its capability to identify the critical composition factors for the VCO nanoemulsion. The main factor controlling the particle size was found out to be xanthan gum (28.56%) followed by T80:PF68 (26.9%), VCO (22.8%) and water (21.74%). The formulation containing copper peptide was then successfully prepared using optimum conditions and particle sizes of 120.7 nm were obtained. The final formulation exhibited a zeta potential lower than -25 mV and showed good physical stability towards centrifugation test, freeze-thaw cycle test and storage at temperature 25°C and 45°C. |
| first_indexed | 2024-03-06T09:22:14Z |
| format | Article |
| id | upm.eprints-55017 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T09:22:14Z |
| publishDate | 2016 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | upm.eprints-550172018-07-12T10:40:42Z http://psasir.upm.edu.my/id/eprint/55017/ An artificial neural network based analysis of factors controlling particle size in a virgin coconut oil-based nanoemulsion system containing copper peptide Samson, Shazwani Basri, Mahiran Fard Masoumi, Hamid Reza Abdul Malek, Emilia Karjiban, Roghayeh Abedi A predictive model of a virgin coconut oil (VCO) nanoemulsion system for the topical delivery of copper peptide (an anti-aging compound) was developed using an artificial neural network (ANN) to investigate the factors that influence particle size. Four independent variables including the amount of VCO, Tween 80: Pluronic F68 (T80:PF68), xanthan gum and water were the inputs whereas particle size was taken as the response for the trained network. Genetic algorithms (GA) were used to model the data which were divided into training sets, testing sets and validation sets. The model obtained indicated the high quality performance of the neural network and its capability to identify the critical composition factors for the VCO nanoemulsion. The main factor controlling the particle size was found out to be xanthan gum (28.56%) followed by T80:PF68 (26.9%), VCO (22.8%) and water (21.74%). The formulation containing copper peptide was then successfully prepared using optimum conditions and particle sizes of 120.7 nm were obtained. The final formulation exhibited a zeta potential lower than -25 mV and showed good physical stability towards centrifugation test, freeze-thaw cycle test and storage at temperature 25°C and 45°C. Public Library of Science 2016 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/55017/1/An%20Artificial%20Neural%20Network%20Based%20Analysis.pdf Samson, Shazwani and Basri, Mahiran and Fard Masoumi, Hamid Reza and Abdul Malek, Emilia and Karjiban, Roghayeh Abedi (2016) An artificial neural network based analysis of factors controlling particle size in a virgin coconut oil-based nanoemulsion system containing copper peptide. PLOS ONE, 11 (7). pp. 1-15. ISSN 1932-6203 10.1371/journal.pone.0157737 |
| spellingShingle | Samson, Shazwani Basri, Mahiran Fard Masoumi, Hamid Reza Abdul Malek, Emilia Karjiban, Roghayeh Abedi An artificial neural network based analysis of factors controlling particle size in a virgin coconut oil-based nanoemulsion system containing copper peptide |
| title | An artificial neural network based analysis of factors controlling particle size in a virgin coconut oil-based nanoemulsion system containing copper peptide |
| title_full | An artificial neural network based analysis of factors controlling particle size in a virgin coconut oil-based nanoemulsion system containing copper peptide |
| title_fullStr | An artificial neural network based analysis of factors controlling particle size in a virgin coconut oil-based nanoemulsion system containing copper peptide |
| title_full_unstemmed | An artificial neural network based analysis of factors controlling particle size in a virgin coconut oil-based nanoemulsion system containing copper peptide |
| title_short | An artificial neural network based analysis of factors controlling particle size in a virgin coconut oil-based nanoemulsion system containing copper peptide |
| title_sort | artificial neural network based analysis of factors controlling particle size in a virgin coconut oil based nanoemulsion system containing copper peptide |
| url | http://psasir.upm.edu.my/id/eprint/55017/1/An%20Artificial%20Neural%20Network%20Based%20Analysis.pdf |
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