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.

journal_name

Eur J Med Chem

authors

Wang Z,Yan A,Yuan Q,Gasteiger J

doi

10.1016/j.ejmech.2008.05.017

subject

Has Abstract

pub_date

2008-11-01 00:00:00

pages

2442-52

issue

11

eissn

0223-5234

issn

1768-3254

pii

S0223-5234(08)00272-9

journal_volume

43

pub_type

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