Explorations into modeling human oral bioavailability.
Explorations into modeling human oral bioavailability started with a whole dataset of 772 drug compounds. First, training set and test set were chosen based on Kohonen's self-organizing Neural Network (KohNN). Then, a quantitative model of the whole dataset was built using multiple linear regression (MLR) analysis. This model had limited predictability emphasizing that a variety of pharmacokinetic factors influence human oral bioavailability. In order to explore whether better models can be built when the compounds share some ADME properties, four subsets were chosen from the whole dataset to build quantitative models and better models were obtained by MLR analysis. These studies show that, indeed, good models for predicting human oral bioavailability can be obtained from datasets sharing certain pharmacokinetic properties.
Wang
Zhi
Z
State Key Laboratory of Chemical Resource Engineering, Department of Pharmaceutical Engineering, P.O. Box 53, Beijing University of Chemical Technology, 15 BeiSanHuan East Road, Beijing 100029, PR China.
Yan
Aixia
A
Yuan
Qipeng
Q
Gasteiger
Johann
J
D000284:Administration, Oral; D001682:Biological Availability; D020650:Combinatorial Chemistry Techniques; D006801:Humans; D008954:Models, Biological; D004364:Pharmaceutical Preparations
D004364:Pharmaceutical Preparations