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

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

European journal of medicinal chemistry (2009-12-22)
A Guerra, N E Campillo, J A Páez
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.

MATERIALS
Product Number
Brand
Product Description

Sigma-Aldrich
Glycine, BioUltra, for molecular biology, ≥99.0% (NT)
Supelco
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Glycine, tested according to Ph. Eur.
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Salicylic acid, meets analytical specification of Ph. Eur., BP, USP, 99.5-100.5% (calc. to the dried substance)
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Chloroform solution, NMR reference standard, 1% in acetone-d6 (99.9 atom % D)
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D-Mannitol, BioUltra, ≥99.0% (sum of enantiomers, HPLC)
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Chloroform, anhydrous, contains amylenes as stabilizer, ≥99%
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