Research article summary (published 29 Nov 2006):

[Prediction of drug bioavailability by genetic algorithm and artificial neural network]

Full Abstract

AIM:
To set up an artificial neural network system and optimize by genetic algorithm (GA) to predict drug bioavailability.

METHODS:
Genetic algorithm was used to optimize weights of the artificial neural network. The optimal solution of the artificial neural network model at a specific condition was obtained using the good search ability of genetic algorithm in order to predict drug bioavailability. Volume, refractivity, lgP(c), hydration, polarizability, E(HOMO) and E(LUMO) are inputs of the drug bioavailability prediction neural network, and its output is average drug bioavailability.

RESULTS:
The prediction precision of average drug bioavailability of the GA- neural network model is 95.9%.

CONCLUSION:
This model can be used in the forecasting of drug bioavailability.

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Author information

Author/s: Wang, Ze (Z); Li, Xin-Cheng (XC); Zhu, Wei-Xin (WX);

Affiliation: School of Mechanical Engineering, Jiangsu University, Zhenjiang 212013, China. wangze20041968(-atsign-)yahoo.com.cn

Journal and publication information

Publication Type: English Abstract; Journal Article; Research Support, Non-U.S. Gov't

Journal: Yao xue xue bao = Acta pharmaceutica Sinica (Yao Xue Xue Bao), published in China. (Language: chi)

Reference: 2006-Dec; vol 41 (issue 12) : pp 1180-3

Dates: Created 2007/02/12; Completed 2007/12/20;

PMID: 17290617, status: MEDLINE (last retrieval date: 12/26/2008)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Algorithms Biological Availability

Biological Availability Neural Networks (Computer)

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