Linked Life Data

17827020

Source:http://linkedlifedata.com/resource/pubmed/id/17827020

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
22
pubmed:dateCreated
2007-10-1
pubmed:abstractText
A set of 116 structurally very diverse compounds, mainly drugs, was characterized by 1630 molecular descriptors. The biological property modelled in this study was the transdermal permeability coefficient logK(p). The main objective was to find a limited set of suitable model compounds for skin penetration studies. The classification and regression trees (CART) approach was applied and the resulting groups were discussed in terms of their role as possible model compounds and their determining descriptors. A second objective was to model transdermal penetration as a function of selected descriptors in quantitative structure-property relationships (QSPR) using a boosted CART (BRT) approach and multiple linear regression (MLR) analysis, where regression models were obtained by stepwise selection of the best descriptors. Evaluation of the standard statistical, as well as descriptor-number dependent, regression quality attributes yielded a maximal 10-dimensional MLR model. The CART and MLR models were subjected to an external validation with a test set of 12 compounds, not included in the original learning set of 104 compounds, to assess the predictive power of the models.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
0968-0896
pubmed:author
pubmed:issnType
Print
pubmed:day
15
pubmed:volume
15
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
6943-55
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Transdermal penetration behaviour of drugs: CART-clustering, QSPR and selection of model compounds.
pubmed:affiliation
Drug Quality and Registration (DruQuaR) Group, Department of Pharmaceutical Analysis, Faculty of Pharmaceutical Sciences, Ghent University, Harelbekestraat 72, B-9000 Ghent, Belgium.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't