Artificial neural networks applied to the in vitro-in vivo correlation of an extended-release formulation: Initial trials and experience

Journal of Pharmaceutical Sciences

Volumn 88, Issue 1, 1999, Pages 154-160

  Dowell, James A ^a   Hussain, Ajaz ^b   Devane, John ^a,c   Young, David ^a,d  

^a UNIVERSITY OF MARYLAND   (United States)

^b CENTER FOR DRUG EVALUATION AND RESEARCH   (United States)

^c ELAN PHARMACEUTICALS   (United States)

^d ICON Development Solutions   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DRUG;

ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; CORRELATION FUNCTION; DRUG FORMULATION; DRUG SOLUBILITY; FORECASTING; MATHEMATICAL ANALYSIS; MODEL; STRUCTURE ANALYSIS; SUSTAINED RELEASE PREPARATION;

EID: 0032960016     PISSN: 00223549     EISSN: None     Source Type: Journal    
DOI: 10.1021/js970148p     Document Type: Article

References (21)

1. Sullivan, T. J.; Sakmar, E.; Wagner, J. G. Comparative bioavailability: a new type of in vitro-in vivo correlation exemplified by prednisone. J. Pharmacokinet. Biopharm. 1976, 4(2), 173-181.
2. Graffner, C.; Nicklasson, M.; J.-E. Lindgren, Correlations between in vitro dissolution rate and bioavailability of alaproclate tablets. J. Pharmacokinet. Biopharm. 1984, 12(4), 367-380.
3. Caramella, C.; Ferrari, F.; Bonferoni, M. C.; Sangalli, M. E.; De Bernardi Di Valserra, M.; Feletti, F.; F., Galmozzi, M. R. In vitro/in vivo correlation of prolonged release dosage forms containing diltiazem HCl. Biopharm. Drug Dispos. 1993, 14(2), 143-160.
4. Wood, R. W.; Martis, L.; Gillum, A. W.; Roseman, T. J.; Lin, L.; L.; Bernardo, P. In vitro dissolution and in vivo bioavailability of commercial levothyroxine sodium tablets in the hypothyroid dog model. J. Pharm. Sci. 1990, 79(2), 124-127.
5. Barr, W. H.; Zola, E. M.; Candler, E. L.; S-M. Hwang, Tendolkar, A. V.; Shamburek, R.; Parker, B.; Hilty, M. D. Differential absorption of amoxicillin from the human small and large intestine. Clin. Pharmacol. Ther. 1994, 56(3), 279-285.
6. Levy, G.; Hollister, L. E. Inter-and intra subject variations in drug absorption kinetics. J. Pharm. Sci. 1964, 53(12), 1446-1452.
7. Anderson, J. A. An introduction to neural networks; The MIT Press: Cambridge, MA, 1995.
8. Gallant, S. I. Neural Network Learning and Expert Systems; The MIT Press, Cambridge, MA, 1993.
9. Hagan, M. T.; Demuth, H. B.; Beale, M. Neural Network Design; PWS Publishing: Boston, 1996.
10. Specht, D. F. A general regression neural network. IEEE Trans. Neural Networks 1991, 2(6), 568-576.
11. Erb, R. Introduction to back-propagation neural network computation. Pharm. Res. 1993, 10(1), 165-170.
12. Erb, R. The back-propagation neural network - A bayesian classifier. Introduction and applicability to pharmacokinetics. Clin. Pharmacokinet. 1995, 29(2), 69-79.
13. Hussain, A. S.; Johnson, R. D.; Vachharajani, N. N.; Ritschel, W. A. Feasibility of developing a neural network for prediction of human pharmacokinetic parameters from animal data. Pharm. Res. 1993, 10(3), 466-469.
14. Brier, M. E.; Zurada, J. M.; Aronoff, G. R. Neural network predicted peak and trough gentamicin concentrations. Pharm. Res., 1995, 12(3), 406-412.
15. Veng-Pedersen, P.; Modi, N. B. Application of neural networks to pharmacodynamics. J. Pharm. Sci., 1993, 82(9), 918-926.
16. Hussain, A. S.; Yu, X. Q.; Johnson, R. D. Application of neural computing in pharmaceutical product development. Pharm. Res. 1991, 8(10), 1248-1252.
17. Gobburu, J. V. S.; Shelver, W. H. Quantitative structure-pharmacokinetic relationships (QPSR) of beta blockers derived using neural networks. J. Pharm. Sci. 1995, 84(7), 862-865.
18. NeuroShell 2 Manual Third Edition; Ward Systems Group, Inc., Executive Park West, 5 Hillcrest Drive, Frederick, MD 21702, 1995.
19. Elman, J. L. Finding structure in time. Cognitive Science 1990, 14(1), 179-211.
20. Haykin, S. Neural networks: a comprehensive foundation; Macmillan: New York, 1994.
21. De Villiers, J.; Barnard, E. Back-propagation neural nets with one and two hidden layers. IEEE Trans. Neural Networks 1992, 4(1), 136-141.