Abstract

A neural model based on a numerical molecular representation using CODES (R) program to predict oral absorption of any structure is described. This model predicts both high and low-absorbed compounds with a global accuracy level of 74%. CODES/ANN methodology shows promising utilities not only as a conventional in silica, tool in high-throughput screening or improvement of absorption capabilities procedures but also the improvement of in vitro-in vivo correlation could be addressed. (C) 2009 Elsevier Masson SAS. All rights reserved.