Linked Life Data

17947127

Source:http://linkedlifedata.com/resource/pubmed/id/17947127

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2007-10-23
pubmed:abstractText
To date, the application of physiologically based pharmacokinetic (PBPK) models in support of drug discovery remains limited, in part due to information deficit and uncertainty regarding model parameters. Fuzzy set theory provides a suitable way to objectively account for parameter uncertainty in models. Here, we present a fuzzy set-based PBPK modeling framework and demonstrate its utility in predicting diazepam pharmacokinetics in human plasma, following intravenous dosing, from available animal in vivo and literature data. For computationally expensive PBPK models, the sparse grid method is proposed as an efficient alternative to commonly used fuzzy arithmetic algorithms for function simulation.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1557-170X
pubmed:author
pubmed:issnType
Print
pubmed:volume
1
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
5037-40
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
A fuzzy physiologically based pharmacokinetic modeling framework to predict drug disposition in humans.
pubmed:affiliation
Department of Bioengineering, University of Washington, Seattle, WA 98105, USA. kyseng@u.washington.edu
pubmed:publicationType
Journal Article, Research Support, N.I.H., Extramural