Development of in Vitro-in Vivo Correlations Using Various Artificial Neural Network Configurations
It is desirable to have a predictive tool to determine the in vivo pharmacokinetics based on the in vitro dissolution and other important variables. We can see the in vitro — in vivo correlation (IVIVC) as an input-output relationship, and often are not interested in the internal structure of this model as long as we have a good, validated, predictive tool. This may be important, for example, in product development or to establish dissolution specifications. Many of the previous examples in this book use parametric models to define an IVIVC. For example, simple linear models are often used to relate a parameter or a time point descriptive of the dissolution to a parameter or a time point descriptive of the pharmacokinetic absorption1–3. These models, however, can be unsuccessful in completely describing the IVIVC, and sometimes no correlation can be determined. The number of possible variables, the model unable to account for some physiological rate determining process, and the possible amount of variability intrinsic to the parameters of these modeled relationships are some examples of these difficulties 4–6.
KeywordsArtificial Neural Network Dissolution Profile Network Configuration Logistic Linear General Regression Neural Network
Unable to display preview. Download preview PDF.
- 7.J. A. Anderson. An introduction to neural networks, MIT Press, Cambridge, 1995.Google Scholar
- 8.S. I. Gallant. Neural Network Learning and Expert Systems, MIT press, Cambridge, 1993.Google Scholar
- 9.M. T. Hagan, H. B. Demuth, and M. Beale. Neural Network Design, PWS Publishing Company, Boston, 1996.Google Scholar
- 11.R. Erb. The backpropagation neural network — A bayesian classifier. Introduction and applicability to pharmacokinetics. Clin. Pharmacokinet. 29: 69–79 (1995).Google Scholar
- 13.S. Haykin. Neural networks: a comprehensive foundation, Macmillan, New York, 1994.Google Scholar
- 14.NeuroShell® 2 Manual Third Edition, Ward Systems Group, Inc. Executive Park West, 5 Hillcrest Drive, Frederick, MD 21702. (1995).Google Scholar