ME_expert - a neural decision support system as a tool in the formulation of microemulsions

• Autorzy: Mendyk, A. , Jachowicz, R.
• Języki publikacji: EN

Abstrakty

EN

The aim of this project was to create a tool for improvement of microemulsions formulation process. Microemulsions are promising drug forms allowing for improvement of solubility and enabling controlled release of drugs. As a modeling tool, artificial neural networks (ANNs) were chosen. ME _expert system was created basing on the neural expert committee constructed of 11 neural models. ANN were designed to predict occurrence of microemulsion basing on its particular quantitative and quantitative compostion. Generalization abilities of ME _expert were tested in laboratory trials, where 77% of accuracy was found for unknown composition of microemulsion.

Słowa kluczowe

PL

sztuczna sieć neuronowa; mikroemulsja; system wspomagania decyzji; technologia farmaceutyczna

EN

artificial neural networks; microemulsions; decision support systems; expert committees; pharmaceutical technology

• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2006
• Tom: Vol. 26, no. 4
• Strony: 25-32
• Opis fizyczny: Bibliogr. 10 poz., rys., tab.

Twórcy

autor

Mendyk, A.

autor

Jachowicz, R.

• Department of Pharmaceutical Technology and Biopharmaceutics, Faculty of Pharmacy, Collegium Medicum, Jagiellonian University, ul. Medyczna 9, 30-688 Kraków, Poland,

Bibliografia

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• 3. Alany R.G., Agatonovic-Kustrin S., Rades T., Tucker I.G.: Use of artificial neural networks to predict quaternery phase systems from limited experimental data. J. Pharm. Biomed. Anal. 1999, 19, 443-452.
• 4. Agatonovic-Kustrin S., Alany R.G.: Role of genetic algorithms and artificial neural networks in predicting the phase behavior of colloidal delivery systems. Pharm. Res. 2001, 18, 1049-1055.
• 5. Mendyk A., Jachowicz R., Chłosta S., Dziekan A.: Neural Expert System for Optimization of Microemulsions Quantitative and Qualitative Composition. 4th World Meeting ADRITELF/AVP/APGI, Florence, 8/11 April 2002, 1519-1520.
• 6. Agatonovic-Kustrin S., Glass B.D., Wisch M.H., Alany R.G.: Prediction of a stable microemulsion formulation for the oral delivery of a combination of antitubercular drugs using ANN methodology. Pharm. Res. 2003, 20, 1760-1765.
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• 8. Bilski J.: The backpropagation learning with logarithmic transfer function. Proceedings of the Fifth Conference Neural Networks and Soft Computing, Zakopane 2000, 71-77.
• 9. Mendyk A.: Artificial neural networks as universal modeling tools in the pharmaceutical technology and biopharmaceutics, PhD thesis, Department of Pharmaceutical Technology and Biopharmaceutics, Faculty of Pharmacy, Collegium Medicum, Jagiellonian University, Kraków 2004, (in Polish).
• 10. http://www.borland.com