Neural computational prediction of oral drug absorption based on CODES 2D descriptors

Abstract A neural model based on a numerical molecular representation using CODES ® 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 silico tool in high-throughput screening or improvement of absorption capabilities procedures but also the improvement of in vitro–in vivo correlation could be addressed.