Validation of fluid bed granulation utilizing artificial neural network

International Journal of Pharmaceutics

Volumn 291, Issue 1-2, 2005, Pages 139-148

  Behzadi, Sharareh Salar ^a   Klocker, Johanna ^a   Hüttlin, Herbert ^b   Wolschann, Peter ^a   Viernstein, Helmut ^a  

^a UNIVERSITY OF VIENNA   (Austria)

^b Innojet Technologies   (Germany)

Author keywords

Fluid bed granulation; Generalized regression neural network; Innovative components; Non linear calculation methods

Indexed keywords

SUCROSE;

AIR TEMPERATURE; AIRFLOW; ARTIFICIAL NEURAL NETWORK; ATMOSPHERIC PRESSURE; CONCENTRATION RESPONSE; CONFERENCE PAPER; DRUG GRANULATION; FILTER; FLOW RATE; FLUID BED GRANULATION; FLUIDIZED BED; INSTRUMENTATION; PRIORITY JOURNAL; SPRAY DRYING; VALIDATION PROCESS;

EID: 13544264594     PISSN: 03785173     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijpharm.2004.07.051     Document Type: Conference Paper

References (29)

1. T. Abberger The effect of powder type, free moisture and deformation behaviour of granules on the kinetics of fluid bed granulation Eur. J. Pharm. Biopharm. 52 2001 327 336
2. A.S. Achanta, P.S. Adusumilli, K.W. James, and C.T. Rhodes Development of hot melt coating methods Drug Dev. Ind. Pharm. 23 1997 441 449
3. K.H. Bauer, K. Lehmann, H.P. Osterwald, and G. Rothgang Coated Pharmaceutical Dosage Forms 1998 Medpharm Scientific Publishers Stuttgart p. 172 (Chapter 7.5)
4. P. Bruneau Search for predictive generic model of aqueous solubility using Bayesian neural nets J. Chem. Inf. Comput. Sci. 41 2001 1605 1616
5. H. Egermann, and S. Flögel Wirbelschichtgranulierung von Laktose im Gleichstrom- und im Gegenstromverfahren Sci. Pharm. 63 1995 4
6. P. Frake, D. Greenhalgh, S.M. Grierson, J.M. Hempenstall, and D.R. Rudd Process control and end-point determination of a fluid bed granulation by application of near infra-red spectroscopy Int. J. Pharm. 151 1997 75 80
7. Y. Funakoshi, M. Yamamoto, Y. Matsumura, and H. Komeda A novel agglomeration granulating system utilizing a centrifugal-fluidizing drive Powder Technol. 27 1980 13 21
8. K.F. Jäger, and K.H. Bauer Auswirkungen der Gutbewegung im Rotor-Wirbelschicht-Granulator auf die Aufbauagglomeration Pharm. Ind. 44 1982 193 197
9. D.V. Jones Air suspension coating Encyclopedia of Pharmaceutical Technology vol. 1 1988 Marcel Dekker New York p. 189
10. M.J. Jozwiakowski, D.M. Jones, and R.M. Franz Characterization of a hot-melt fluid bed coating process for fine granules Pharm. Res. 7 1990 1119 1126
11. J. Klocker, B. Wailzer, G. Buchbauer, and P. Wolschann Bayesian neural networks for aroma classification J. Chem. Inf. Comput. Sci. 42 2002 1443 1449
12. H. Kristensen, and T. Schaefer Granulation, a review of pharmaceutical wet granulation Drug Dev. Ind. Pharm 13 1987 803 872
13. W. Külling Maßnahmen und Einrichtungen zur Sicherung von Wirbelschicht-Trocknern und -Sprühgranulatoren gegen Sraub- und Lösungsmittelexplosionen 1. Teil Pharm. Ind. 39 1977 631 636
14. W. Külling Maßnahmen und Einrichtungen zur Sicherung von Wirbelschicht Trocknern und -Sprühgranulatoren gegen Sraub- und Lösungsmittelexplosionen 2. Teil Pharm. Ind. 39 1977 831 834
15. E. Murtoniemi, J. Yliruusi, P. Kinnunen, P. Merkku, and K. Leiviska The advantages by the use of neural networks in modelling the fluidized bed granulation process Int. J. Pharm. 108 1994 155 164
16. R. Pisek, O. Planinsek, M. Tus, and S. Srcic Influence of rotational speed and surface of rotating disc on pellets produced by direct rotor pelletization Pharm. Ind. 62 2000 312 319
17. J. Rantanen, S. Lehtola, P. Rämet, J.P. Mannermaa, and J. Yliruusi On-line monitoring of moisture content in an instrumented fluidized bed granulator with a multi-channel NIR moisture sensor Powder Technol. 99 1998 163 170
18. L. Simon, and K.M. Nazmul Probabilistic neural networks using Bayesian decision strategies and a modified Gompertz model for growth phase classification in the batch culture of Bacillus subtilis Biochem. Eng. J. 7 2001 41 48
19. D.F. Specht Probabilistic Neural Netw. 3 1990 109 118
20. D.F. Specht A general regression neural network IEEE Trans. Neural Netw. 2 1991 568 576
21. Trajan Neural Networks 5.0, 1999. Trajan Software Ltd.
22. P. Veng-Pedersen, and N.B. Modi Application of neural networks to pharmacodynamics J. Pharm. Sci. 82 1993 918 926
23. J. Vertommen, and R. Kinget The influence of five selected processing and formulation variables on the particle size, particle size distribution, and friability of pellets produced in a rotary processor Drug Dev. Ind. Pharm. 23 1997 39 46
24. S. Watano, K. Therashita, and K. Miyanami Determination of end-point with a complex granulation applying infrared moisture sensor Chem. Pharm. Bull. 39 1991 1013 1017
25. S. Watano, T. Fukushima, K. Miyanami, T. Murakami, and T. Sato Automation of the manufacturing process of cold remedy granules by a tumbling fluidized bed applying the fuzzy control method Chem. Pharm. Bull. 42 1994 1302 1307
26. S. Watano, H. Takashima, and K. Miyanami Scale-up of agitation fluidised bed granulation V. Effect of moisture content on scale-up characteristics Chem. Pharm. Bull. 45 1997 710 714
27. S. Watano, H. Takashima, and K. Miyanami Scale-up of agitation fluidized bed granulation by neural network Chem. Pharm. Bull. 45 1997 1193 1197
28. Z.R. Young, M.B. Platt, and H.D. Platt Probabilistic neural networks in bankruptcy prediction J. Business Res. 44 1999 67 74
29. J. Zupan, and J. Gasteiger Neural Networks in Chemistry and Drug Design 1999 Wiley-VCH Weinheim/New York