期刊
EUROPEAN JOURNAL OF PHARMACEUTICAL SCIENCES
卷 31, 期 2, 页码 137-144出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ejps.2007.03.004
关键词
model trees; artificial neural networks; modelling; multivariate linear equations; tablet formulation
This study has investigated an artificial intelligence technology - model trees - as a modelling tool applied to an immediate release tablet formulation database. The modelling performance was compared with artificial neural networks that have been well established and widely applied in the pharmaceutical product formulation fields. The predictability of generated models was validated on unseen data and judged by correlation coefficient R-2. Output from the model tree analyses produced multivariate linear equations which predicted tablet tensile strength, disintegration time, and drug dissolution profiles of similar quality to neural network models. However, additional and valuable knowledge hidden in the formulation database was extracted from these equations. It is concluded that, as a transparent technology, model trees are useful tools to formulators. (c) 2007 Elsevier B.V. All rights reserved.
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