Neural computational prediction of oral drug absorption based on CODES 2D descriptors.
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.
Guerra
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A
Instituto de Química Médica, CSIC, Juan de la Cierva, Madrid, Spain.
Campillo
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NE
Páez
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JA
D000284:Administration, Oral; D006801:Humans; D008956:Models, Chemical; D016571:Neural Networks, Computer; D010539:Permeability; D021281:Quantitative Structure-Activity Relationship; D013678:Technology, Pharmaceutical