title: Explorations into modeling human oral bioavailability.
abstract: 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.
authors.affiliation: 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.
authors.forename: Zhi
authors.initials: Z
authors.lastname: Wang
authors.forename: Aixia
authors.initials: A
authors.lastname: Yan
authors.forename: Qipeng
authors.initials: Q
authors.lastname: Yuan
authors.forename: Johann
authors.initials: J
authors.lastname: Gasteiger
mesh_terms: D000284:Administration, Oral; D001682:Biological Availability; D020650:Combinatorial Chemistry Techniques; D006801:Humans; D008954:Models, Biological; D004364:Pharmaceutical Preparations
chemical_list: D004364:Pharmaceutical Preparations