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Medchem & Toxicology 2018
Page 56
Journal of Organic & Inorganic Chemistry
ISSN: 2472-1123
A n n u a l C o n g r e s s o n
Medicinal Chemistry,
Pharmacology and toxicology
J u l y 3 0 - 3 1 , 2 0 1 8
Am s t e r d a m , N e t h e r l a n d s
U
tilization of a neural network model was used as computer algorithm to predict intestinal absorption of drugs based on
various molecular properties. In the search for new drugs, a major problem encountered is obtaining drug structures which, as
well as being potent in vitro, possess favourable pharmacokinetic profiles which enable them to pass easily through the relevant
body membranes, especially the gastrointestinal epithelia, to effect their action. Since most drugs are mostly absorbed passively,
this work aimed at simplifying and improving the prediction of intestinal drug absorption through a generated model. The model
was generated by neural network analysis of some molecular descriptors, obtained via molecular modelling, corresponding to the
empirically determined caco-2 cell permeability coefficient of the molecule. Utilization of a neural network model is good way to
find a nonlinear relationship between causal factors and their results. Most of the parameters were based on polar surface area
(PSA) for predicting Caco-2 cell permeability and human intestinal absorption
.
tellchris@gmail.comPredicting intestinal permeation of drugs
through neural network analysis based on some
molecular descriptors
Michael U Adikwu and I C Mbonu
1
University of Abuja, Abuja, Nigeria
2
Nnamdi Azikiwe, University, Awka, Nigeria
J Org Inorg Chem 2018, Volume 4
DOI: 10.21767/2472-1123-C3-009