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

European Journal of Pharmaceutical Sciences

Volumn 35, Issue 1-2, 2008, Pages 42-51

  Amani, Amir ^a,b   York, Peter ^a   Chrystyn, Henry ^c   Clark, Brian J ^a   Do, Duong Q ^d  

^a UNIVERSITY OF BRADFORD   (United Kingdom)

^b TEHRAN UNIVERSITY OF MEDICAL SCIENCES   (Iran)

^c UNIVERSITY OF HUDDERSFIELD   (United Kingdom)

^d UNIVERSITY OF MEDICINE AND PHARMACY AT HO CHI MINH CITY   (Viet Nam)

Author keywords

Artificial Neural Networks; Nanoemulsion; Particle size

Indexed keywords

ALCOHOL; BUDESONIDE; DRUG VEHICLE; MEDIUM CHAIN TRIACYLGLYCEROL; POLYSORBATE; SODIUM CHLORIDE; SURFACTANT;

ARTICLE; ARTIFICIAL NEURAL NETWORK; DATA ANALYSIS; EMULSION; ENERGY; FLOW MEASUREMENT; INTERNAL PHASE; NANOEMULSION; NANOTECHNOLOGY; PARAMETER; PARTICLE SIZE; PREDICTIVE VALIDITY; PRIORITY JOURNAL;

ALGORITHMS; ANTI-INFLAMMATORY AGENTS; BUDESONIDE; DATA INTERPRETATION, STATISTICAL; EMULSIONS; ETHANOL; EXCIPIENTS; INDICATORS AND REAGENTS; NANOPARTICLES; NEURAL NETWORKS (COMPUTER); PARTICLE SIZE; POLYSORBATES; REPRODUCIBILITY OF RESULTS; SOFTWARE; SOLVENTS; TRIGLYCERIDES;

EID: 48849091581     PISSN: 09280987     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ejps.2008.06.002     Document Type: Article

References (27)

1. Aboofazeli R., Barlow D.J., and Lawrence M.J. Particle size analysis of concentrated phospholipid microemulsions: II. Photon Correlation Spectroscopy. AAPS Pharmsci. 2 (2000) Article 19
2. Agatonovic-Kustrin S., and Alany R.G. Role of genetic algorithms and artificial neural networks in predicting the phase behavior of colloidal delivery systems. Pharm. Res. 18 (2001) 1049-1055
3. Agatonovic-Kustrin S., and Beresford R. Basic concept of artificial neural network (ANN) modeling and its application in pharmaceutical research. J. Pharm. Biomed. Anal. 22 (2000) 717-727
4. Agatonovic-Kustrin S., Glass B.D., Wisch M.H., and Alany R.G. Prediction of a stable microemulsion formulation for the oral delivery of a combination of antitubercular drugs using ANN methodology. Pharm. Res. 20 (2003) 1760-1765 (2003)
5. Alany R.G., Agatonovic-Kustrin S., Rades T., and Tucker I.G. Use of artificial neural networks to predict quaternary phase systems from limited experimental data. J. Pharm. Biomed. Anal. 19 (1999) 443-452
6. Attwood D., Mallon C., Ktistis G., and Taylor C.J. A study on factors influencing the droplet size in non-ionic oil-in-water microemulsions. Int. J. Pharm. 88 (1992) 417-422
7. Bourquin J., Schimidli H., Hoogevest P.V., and Leunberger H. Comparison of artificial neural networks (ANN) with classical modelling techniques using different experimental design and data from a galenical study on a solid dosage form. Eur. J. Pharm. Sci. 6 (1998) 187-300
8. Bourquin J., Schimidli H., Hoogevest P.V., and Leunberger H. Advantages of artificial neural networks (ANN) as alternative modelling technique for data sets showing non-linear relationships using data from a galenical study on a solid dosage form. Eur. J. Pharm. Sci. 7 (1998) 5-16
9. Chen H., Chang X., Weng T., Zhao X., Gao Z., Yang Y., Xu H., and Yang X. A study of microemulsion system for transdermal delivery of triptolide. J. Control Release 98 (2004) 427-436
10. Debuigne F., Cuisenaire J., Jeunieau L., Masereel B., and Nagy J.B. Synthesis of nimesulide nanoparticles in the microemulsion Epikuron/Isopropyl Myristate/Water/n-Butanol (or Isopropanol). J. Colloid Interf. Sci. 243 (2001) 90-101
11. Glass B.D., Agatonovic-Kustrin S., and Wisch M.H. Artificial neural networks to optimize formulation components of a fixed-dose combination of rifampicin, isoniazid and pyrazinamide in a microemulsion. Curr. Drug Discov. Technol. 2 (2005) 195-201
12. Hou M.J., Kim M., and Shah D.O. A light scattering study on the particle size and interparticle interaction in microemulsions of AOT-oil-water systems. J. Colloid Interf. Sci. 123 (1988) 398-412
13. Hussain A.S., Shivanand P., and Johnson R.D. Application of neural computing in pharmaceutical product development: computer aided formulation design. Drug Dev. Ind. Pharm. 20 (1994) 1739-1752
14. Intelligensys Ltd., 2007. INForm Manual, http://www.intelligensys.co.uk/Products/Downloads/downeval.htm (accessed 09.07.07), part of Intelligensys Formulating Knowledge, http://www.intelligensys.co.uk (accessed 09.07.07).
15. Klampfl C.W., Leitner T., and Hilder E.F. Development and optimization of an analytical method for the determination of UV filters in suntan lotions based on microemulsion electrokinetic chromatography. Electrophoresis 23 (2002) 2424-2429
16. 10/water oil-in-water microemulsions. J. Pharm. Sci. 91 (2002) 2317-2331
17. Massart D.L. Biological calculation methods and their application in pharmaceutical science. Verh. K. Acad. Geneeskd. Belg. 60 (1998) 535-564
18. Moreno M.A., Ballesteros M.P., and Frutos P. Lecithin-based oil-in-water microemulsions for parenteral use: pseudoternary phase diagrams, characterization and toxicity studies. J. Pharm. Sci. 92 (2003) 1428-1437
19. Murtoniemi E., Yliruusi J., Kinnunen P., and Merkku P. The advantages by the use of neural networks in modelling the fluidised bed granulation process. Int. J. Pharm. 108 (1994) 155-164
20. Park K.M., and Kim C.K. Preparation and evaluation of flurbiprofen-loaded microemulsion for parenteral delivery. Int. J. Pharm. 181 (1999) 173-179
21. Richardson C.J., Mbanefo A., Aboofazeli R., Lawrence M.J., and Barlow D.J. Neural network prediction of microemulsion phase behaviour. Eur. J. Pharm. Sci. 4 Suppl. 1 (1996) 139
22. Rowe R.C., and Roberts R.J. Intelligent Software for Product Formulation (1998), Taylor & Francis, London pp. 55-60
23. Sarker D.K. Engineering of nanoemulsions for drug delivery. Curr. Drug Deliv. 2 (2005) 297-310
24. Sathe P.M., and Venitz J. Comparison of neural network and multiple linear regression as dissolution predictors. Drug Dev. Ind. Pharm. 29 (2003) 349-355
25. Shao Q., Rowe R.C., and York P. Comparison of experimental data of neurofuzzy logic and neural networks in modelling experimental data of an immediate release tablet formulation. Eur. J. Pharm. Sci. 28 (2006) 394-404
26. Sun Y., Peng Y., Chen Y., and Shukla A.J. Application of artificial neural networks in the design of controlled release drug delivery systems. Adv. Drug Deliv. Rev. 55 (2003) 1201-1215
27. Tenjarla S. Microemulsions: an overview and pharmaceutical applications. Crit. Rev. Ther. Drug Carrier Syst. 16 (1999) 461-521