Predictive QSAR modeling for the successful predictions of the ADMET properties of candidate drug molecules.
Curr Drug Discov Technol
; 4(3): 141-9, 2007 Oct.
Article
em En
| MEDLINE
| ID: mdl-17985997
ABSTRACT
Chemical breakthrough generates large numbers of prospective drug molecules; the use of ADMET (absorption, distribution, metabolism, excretion and toxicity) properties is flattering progressively more imperative in the drug discovery, assortment, development and promotion processes. Due to the inauspicious ADMET properties a huge amount of molecules in the development stage got failure. In the past years several authors reported that it possible to do some prediction of the ADMET properties using the structural features of the molecules, suing several approaches. One of the most important approaches is QSAR modeling of the data derived from their activity profiles and their different structural features (i.e., quantitative molecular descriptors). This review is critically assessing some of the most important issues for the effective prediction of ADMET properties of drug candidates based on QSAR modeling approaches.
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Base de dados:
MEDLINE
Assunto principal:
Farmacocinética
/
Preparações Farmacêuticas
/
Desenho de Fármacos
/
Relação Quantitativa Estrutura-Atividade
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Animals
/
Humans
Idioma:
En
Revista:
Curr Drug Discov Technol
Assunto da revista:
FARMACOLOGIA
Ano de publicação:
2007
Tipo de documento:
Article
País de afiliação:
Noruega