Generalization of a prototype intelligent hybrid system for hard gelatin capsule formulation development

AAPS PharmSciTech

Volumn 6, Issue 3, 2005, Pages

  Wilson, Wendy I ^a   Peng, Yun ^b   Augsburger, Larry L ^a  

^a UNIVERSITY OF MARYLAND   (United States)

^b Baltimore County   (United States)

Author keywords

Artificial neural networks; Capsule formulation; Expert systems; In silico modeling; Low solubility drugs

Indexed keywords

CARBAMAZEPINE; CHLORPROPAMIDE; DIAZEPAM; GELATIN; IBUPROFEN; KETOPROFEN; NAPROXEN; PIROXICAM;

ANALYTICAL ERROR; ARTICLE; ARTIFICIAL NEURAL NETWORK; CONTROLLED STUDY; DATA ANALYSIS; DRUG CAPSULE; DRUG CLASSIFICATION; DRUG FORMULATION; DRUG MANUFACTURE; DRUG SOLUBILITY; HARDNESS; HYBRID; PERFORMANCE; PHYSICAL PARAMETERS; PREDICTION; VALIDATION PROCESS;

EID: 27744597040     PISSN: 15309932     EISSN: 15309932     Source Type: Journal    
DOI: 10.1208/pt060356     Document Type: Article

References (24)

1. Bourquin J, Schmidli H, van Hoogevest P, Leuenberger H. Application of artificial neural networks (ANN) in the development of solid dosage forms. Pharm Dev Tech. 1997:2:111-121.
2. Achanta AS, Kowalski JG, Rhodes CT. Artificial neural networks: implications for pharmaceutical sciences. Drug Dev Ind Pharm. 1995;21:119-155.
3. Rowe RC. Expert systems in solid dosage development. Pharm Ind. 1993;55:1040-1045.
4. Ebube NK, McCall T, Chen Y, Meyer MC. Relating formulation variables to in vitro dissolution using artificial neural network. Pharm Dev Tech. 1997;2:225-232.
5. Peh KK, Lim CP, Quek SS, Khoh KH. Use of artificial neural networks to predict drug dissolution profiles and evaluation of network performance using similarity factor. Pharm Res. 2000; 17:1384-1388.
6. Kandimalla KK, Kanikkannan N, Singh M. Optimization of a vehicle mixture for the transdermal delivery of melatonin using artificial neural networks and response surface method. J Control Release. 1999;61:71-82.
7. Takayama K, Fujikawa M, Nagai T. Artificial neural networks as a novel method to optimize pharmaceutical formulations. Pharm Res. 1999; 16:1-6.
8. Takayama K, Takahara J, Fujikawa M, Ichikawa H, Nagai T. Formula optimization based on artificial neural networks in transdermal drug delivery. J Control Release. 1999;62:161-170.
9. Leane MM, Cumming I, Corrigan OI. The use of artificial neural networks for the selection of the most appropriate formulation and processing variables in order to predict the in vitro dissolution of sustained release minitablets. Pharm Sci Tech. 2003;4:218-229.
10. Takayama K, Morva A, Fujikawa M, Hattori Y, Obata Y, Nagai T. Formula optimization of theophylline controlled release tablet based on artificial neural networks. J Control Release. 2000;68:175-186.
11. Kesavan JG, Peck GE. Pharmaceutical granulation and tablet formulation using neural networks. Pharm Dev Tech. 1996;1:391-404,
12. Huuskonen J, Salo M, Taskinen J. Neural network modeling for estimation of the aqueous solubility of structurally related drugs. J Pharm Sci. 1996;86:450-454.
13. Dowell JA, Hussain A, Devane J, Young D. Artificial neural networks applied to the in vitro-in vivo correlation of an extended release formulation: initial trials and experience. J Pharm Sci. 1998;88:154-160.
14. Rocksloh K, Rapp FR, Abu Abed S, et al. Optimization of crushing strength and disintegration time of a high-dose plant extract tablet by neural networks. Drug Dev Ind Pharm. 1999;25:1015-1025.
15. Ebube NK, Owusu-Ababio G, Moji Adeyeye C. Preformulation studies and characterization of the physiochemical properties of amorphous polymers using artificial neural networks. Int J Pharm. 2000; 196:27-35.
16. Hussain AS, Yu X, Johnson RD. Application of neural computing in pharmaceutical product development. Pharm Res. 1991;8:1248-1252.
17. Murray FJ. The application of expert systems to pharmaceutical processing equipment. Pharm Technol. 1989;13:100-110.
18. Greer ML. RXPERT: A prototype expert system for formulary decision making. Ann Pharmacother. 1992;26:244-250.
19. Guo M, Kalra G, Wilson W, Peng Y, Augsburger LL. A prototype intelligent hybrid system for hard gelatin capsule formulation development. Pharm Technol N Am. 2002;26:44-60.
20. Lai FKY. A prototype expert system for selecting pharmaceutical powder mixers. Pharm. Technol. 1998;12:22-31.
21. Expert System for Formulation Support. 1996.
22. Amidon GL, Lennernas H, Shah VP, Crison JR. A theoretical basis for a biopharmaceutic drug classification: the correlation of in vitro drug product dissolution and in vivo bioavailability. Pharm Res. 1995;12:413-420.
23. FDA. In Vivo Bioavailability and Bioequivalence Studies for Immediate Release Solid Oral Dosage Forms Based on a Biopharmaceutical Classification System. Guidance for Industry. Rockville, MD: Food and Drug Administration; 2001.
24. FDA. Dissolution Testing of Immediate Release Oral Solid Dosage Forms. Guidance for Industry. Rockville, MD: Food and Drug Administration; 1997.