Linked Life Data

11536204

Source:http://linkedlifedata.com/resource/pubmed/id/11536204

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
8
pubmed:dateCreated
2001-9-5
pubmed:abstractText
The influence of the amounts of additives including 1-O-ethyl-3-n-butylcyclohexanol (OEBC), diisopropyl adipate (DIA), and isopropanol (IPA) on the penetration rate (R(p)) of ketoprofen from hydrogels through rat skin in vivo was investigated. Skin irritation evoked by the application of hydrogels was evaluated based on a microscopic observation of skin cross-sections. Both optimization techniques incorporating an artificial neural network (ANN) and a second-order polynomial regression analysis were applied to the optimization of ketoprofen hydrogel formulations. Findings indicated that the R(p) and total irritation score (TIS) of the skin were predicted quantitatively as a function of quantities of OEBC, DIA, and IPA, employing ANN. In contrast, the prediction ability of the polynomial regression equation was somewhat poorer compared with that of ANN. The observed results of R(p) and TIS in the optimal formulation coincided well with the predictions in the simultaneous optimization technique incorporating ANN.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
0022-3549
pubmed:author
pubmed:copyrightInfo
Copyright 2001 Wiley-Liss, Inc.
pubmed:issnType
Print
pubmed:volume
90
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1004-14
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2001
pubmed:articleTitle
Simultaneous optimization based on artificial neural networks in ketoprofen hydrogel formula containing O-ethyl-3-butylcyclohexanol as percutaneous absorption enhancer.
pubmed:affiliation
Department of Pharmaceutics, Hoshi University, Ebara 2-4-41, Shinagawa, Tokyo 142-8501, Japan.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't