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

  作者 Guerra, A; Campillo, NE; Paez, JA  
  选自 期刊  European Journal of Medicinal Chemistry;  卷期  2010年45-3;  页码  930-940  
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[摘要]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.

 
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