On the Use of Artificial Neural Networks to Monitor a Pharmaceutical Freeze-Drying Process

Drying Technology

Volumn 31, Issue 1, 2013, Pages 72-81

  Drǎgoi, Elena Niculina ^a   Curteanu, Silvia ^a   Fissore, Davide ^b  

^a GHEORGHE ASACHI TECHNICAL UNIVERSITY OF IASI   (Romania)

^b POLITECNICO DI TORINO   (Italy)

Author keywords

Artificial neural network; Differential evolution; Freeze drying; Mathematical model; Monitoring; Soft sensor

Indexed keywords

ACCURATE ESTIMATION; DATA SETS; DIFFERENTIAL EVOLUTION; DRYING CHAMBERS; FREEZE-DRYING; FREEZE-DRYING PROCESS; HEAT AND MASS TRANSFER COEFFICIENTS; LEARNING PHASE; LIMIT VALUES; LOCAL SEARCH METHOD; MASS TRANSFER RESISTANCES; NETWORK DEVELOPMENT; OPERATING CONDITION; PARAMETRIC OPTIMIZATION; PHENOMENOLOGICAL MODELS; PRIMARY DRYING; SELF-ADAPTIVE; SOFT SENSORS; SPECIFIC VALUES; VAPOR FLOWS;

BACKPROPAGATION ALGORITHMS; ELECTRIC NETWORK PARAMETERS; EVOLUTIONARY ALGORITHMS; LOW TEMPERATURE DRYING; MASS TRANSFER; MATHEMATICAL MODELS; MONITORING; NEURAL NETWORKS; SENSORS; VAPORS;

DRYING;

EID: 84872380691     PISSN: 07373937     EISSN: 15322300     Source Type: Journal    
DOI: 10.1080/07373937.2012.718308     Document Type: Article

References (46)

1. Liapis, A.I.; Pikal, M.J.; Bruttini, R. Research and development needs and opportunities in freeze drying. Drying Technology 1996, 14, 1265-1300.
2. Sadikoglu, H.; Ozdemir, M.; Seker, M. Freeze-drying of pharmaceutical products: Research and development needs. Drying Technology 2006, 24, 849-861.
3. Barresi, A.A.; Fissore, D.; Product quality control in freeze drying of pharmaceuticals. In Modern Drying Technology: Product Quality and Formulation; Tsotsas, E., Mujumdar, A.S., Eds.; Wiley-VCH: Weinheim, Germany, 2011; 91-154.
4. US Food and Drug Administration. PAT Guidance for Industry-A Framework for Innovative Pharmaceutical Development, Manufacturing and Quality Assurance; US Department of Health and Human Services, Food and Drug Administration, Center for Drug Evaluation and Research, Center for Veterinary Medicine, Office of Regulatory Affairs: Rockville, MD, 2004.
5. Milton, N.; Pikal, M.J.; Roy, M.L.; Nail, S.L. Evaluation of manometric temperature measurement as a method of monitoring product temperature during lyophilisation. PDA Journal of Pharmaceutical Science and Technology 1997, 5, 7-16.
6. Liapis, A.I.; Sadikoglu, H. Dynamic pressure rise in the drying chamber as a remote sensing method for monitoring the temperature of the product during the primary drying stage of freeze-drying. Drying Technology 1998, 16, 1153-1171.
7. Chouvenc, P.; Vessot, S.; Andrieu, J.; Vacus, P. Optimization of the freeze-drying cycle: A new model for pressure rise analysis. Drying Technology 2004, 22, 1577-1601.
8. Velardi, S.A.; Rasetto, V.; Barresi, A.A. Dynamic Parameters Estimation Method: Advanced manometric temperature measurement approach for freeze-drying monitoring of pharmaceutical. Industrial Engineering Chemistry Research 2008, 47, 8445-8457.
9. Fissore, D.; Pisano, R.; Barresi, A.A. On the methods based on the Pressure Rise Test for monitoring a freeze-drying process. Drying Technology 2011, 29, 73-90.
10. Pisano, R.; Fissore, D.; Barresi, A.A. Innovation in monitoring food freeze-drying. Drying Technology 2011, 29, 1920-1931.
11. Velardi, S.A.; Hammouri, H.; Barresi, A.A. In-line monitoring of the primary drying phase of the freeze-drying process in vial by means of a Kalman filter based observer. Chemical Engineering Research & Design 2009, 87, 1409-1419.
12. Velardi, S.A.; Hammouri, H.; Barresi, A.A.Development of a high gain observer for in-line monitoring of sublimation in vial freeze-drying. Drying Technology2010, 28, 256-268.
13. Bosca, S.; Fissore, D. Design and validation of an innovative soft-sensor for pharmaceuticals freeze-drying monitoring. Chemical Engineering Science 2011, 66, 5127-5136.
14. Rasetto, V.; Marchisio, D.L.; Fissore, D.; Barresi, A.A. On the use of a dual-scale model to improve understanding of a pharmaceutical freeze-drying process. Journal of Pharmaceutical Sciences 2010, 99, 4337-4350.
15. Barresi, A.A.; Pisano, R.; Rasetto, V.; Fissore, D.; Marchisio, D.L. Model-based monitoring and control of industrial freeze-drying processes: Effect of batch non-uniformity. Drying Technology 2010, 28, 577-590.
16. Fissore, D.; Velardi, S.A.; Barresi, A.A. In-line control of a freeze-drying process in vials. Drying Technology 2008, 26, 685-694.
17. Drǎgoi, E.N.; Curteanu, S.; Fissore, D. Freeze-drying modeling and monitoring using a new neuro-evolutive technique. Chemical Engineering Science 2011, 72, 195-204.
18. Ochoa-Martinez, C.I.; Ramaswamy, H.S.; Ayala-Aponte, A.A. Artificial neural network modeling of osmotic dehydration mass transfer kinetics of fruits. Drying Technology 2007, 25, 85-95.
19. Mujumdar, A.S.; Zhonghua, W. Thermal drying technologies - Cost-effective innovation aided by mathematical modeling approach. Drying Technology 2008, 26, 145-153.
20. Mihajlovic, T.; Ibric, S.; Mladenovic, A. Application of design of experiments and multilayer perceptron neural network in optimization of the spray-drying process. Drying Technology 2011, 29, 1638-1647.
21. Polat, K.; Kirmaci, V. A novel data preprocessing method for the modeling and prediction of freeze-drying behavior of apples: Multiple output-dependent data scaling (MODDS). Drying Technology 2012, 30, 185-196.
22. Keshani, S.; Daud, W.R.W.; Woo, M.W.; Talib, M.Z.M.; Chuah, A.L.; Russly, A.R. Artificial neural network modeling of the deposition rate of lactose powder in spray dryers. Drying Technology 2012, 30, 386-397.
23. Valentina, N.; Denoeux, T. A neural network-based software sensor for coagulation control in a water treatment plant. Intelligent Data Analysis 2001, 5, 23-39.
24. Jimenez, A.; Beltran, G.; Aguilera, M.P.; Uceda, M. A sensor-software based on artificial neural network for the optimization of olive oil elaboration process. Sensors and Actuators B 2008, 129, 985-990.
25. Erenturk, S.; Erenturk, K. Comparison of genetic algorithm and neural network approaches for the drying process of carrot. Journal of Food Engineering 2007, 78, 905-912.
26. Menlik, T.; Kirmaci, V.; Usta, H. Modeling of freeze drying behaviors of strawberries by using artificial neural network. Journal of Thermal Science and Technology 2009, 29, 11-21.
27. Menlik, T.; Ozdemir, M.B.; Kirmaci, V. Determination of freeze-drying behaviors of apples by artificial neural network. Expert Systems with Applications 2010, 37, 7669-7677.
28. Todorov, Y.V.; Terziyska, M.; Petrov, M. Nonlinear model predictive controller using a Fuzzy-Neural Wiener-Hammerstein model. In Proceedings of 16th International Conference on Process Control 2007, 216, 1-7.
29. Todorov, Y.V.; Tsvetkov, T.D. Volterra Model predictive control of a lyophilization plant. In Proceedings of 4th International IEEE Conference-Intelligent Systems 2008, 3, 2013-2018.
30. Rojas, R. Neural Networks: A Systematic Introduction; Springer: Berlin, 1996.
31. Xin, Y. Evolving artificial neural networks. In Proceedings of the IEEE 1999, 87, 1423-1447.
32. Abbass, H.A. A memetic Pareto evolutionary approach to artificial neural networks. In Proceedings of the 14th Australian Joint Conference on Artificial Intelligence 2001, 2256, 1-12.
33. Olafsson, S. Metaheuristics. In Simulation: Handbooks in Operations Research and Management Science; Henderson, S.G.; Nelson, B.L., Eds.; Elsevier: Amsterdam, 2006; 633-654.
34. Feoktistov, V. Differential Evolution: In Search of Solutions; Springer-Verlag: Berlin, 2006.
35. Floreano, D.; Durr, P.; Mattiussi, C. Neuroevolution: From architecture to learning. Evolutionary Intelligence 2008, 1, 47-62.
36. Bedri Ozer, A. CIDE: Chaotically Initialized Differential Evolution. Expert System with Applications 2010, 37, 4632-4641.
37. Curteanu, S.; Cartwright, H. Neural networks applied in chemistry.I. Determination of the optimal topology of multilayer perceptron neural networks. Journal of Chemometrics 2011, 25, 527-574.
38. Lombraña, J.I.; De Elvira, C.; Villaran, M.C.; Izcara, J. Simulation and design of heating profiles in heat controlled freeze-drying of pharmaceuticals in vials by the application of a sublimation semispherical model. Drying Technology 1993, 11, 471-487.
39. Lombraña, J.I.; De Elvira, C.; Villaran, M.C.; Izcara, J. Simulation and design of heating profiles in heat controlled freeze-drying of pharmaceuticals in vials by the application of a sublimation cylindrical model. Drying Technology 1993, 11, 85-102.
40. Sadikoglu, H.; Liapis, A.I. Mathematical modelling of the primary and secondary drying stages of bulk solution freeze-drying in trays: Parameter estimation and model discrimination by comparison of theoretical results with experimental data. Drying Technology 1997, 15, 791-810.
41. Gan, K.H.; Crosser, O.K.; Liapis, A.I.; Bruttini, R. Lyophilisation in vials on trays: Effects of tray side. Drying Technology 2005, 23, 341-363.
42. Hottot, A.; Peczalski, R.; Vessot, S.; Andrieu, J. Freeze-drying of pharmaceutical proteins in vials: Modeling of freezing and sublimation steps. Drying Technology 2006, 24, 561-570.
43. Velardi, S.A.; Barresi, A.A. Development of simplified models for the freeze-drying process and investigation of the optimal operating conditions. Chemical Engineering Research and Design 2008, 87, 9-22.
44. Himmelblau, D. Applications of artificial neural networks in chemical engineering. Korean Journal of Chemical Engineering 2000, 17, 373-392.
45. Kisi, O. River suspended sediment concentration modeling using a neural differential evolution approach. Journal of Hydrology 2010, 389, 227-235.
46. Giordano, A.; Barresi, A.A.; Fissore, D. On the use of mathematical models to build the design space for the primary drying phase of a pharmaceutical lyophilization process. Journal of Pharmaceutical Sciences 2011, 100, 311-324.