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Neural computational prediction of oral drug absorption based on CODES 2D descriptors
A Guerra1, N E Campillo, J A Páez
1Instituto de Química Médica, CSIC, Juan de la Cierva, Madrid, Spain.
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.
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