Linked Life Data

2127288

Source:http://linkedlifedata.com/resource/pubmed/id/2127288

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
11
pubmed:dateCreated
1991-4-9
pubmed:abstractText
A variance-stabilizing transformation (VST) was applied to the linear regression of calibration standards of different drugs in plasma. This transformation involved the normalization of the dependent variable peak height or peak area ratio (Y), and the independent variable, plasma drug concentration (C). This transformation led to a constant variance in the regression error term across the measured concentration range and allowed the evaluation of the unbiased slope and y intercept with minimum variance. The utility of the VST procedure in comparison with the ordinary least squares (OLS) approach, routinely used in pharmaceutical studies for constructing calibration lines, is described. The principal advantage of the VST approach is allowing a lower minimum level of drug quantification while using a single calibration line over a wide range of drug concentrations. The VST method is especially useful to quantify drug plasma levels in pharmacokinetic evaluation of sustained-release dosage forms, where the precise quantification of low levels of drug is critical. The application of the VST method was explored and evaluated in comparison with the OLS method for pharmacokinetic assays of diltiazem, gallopamil, nitroglycerin, and nicotine.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
0022-3549
pubmed:author
pubmed:issnType
Print
pubmed:volume
79
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1005-8
pubmed:dateRevised
2000-12-18
pubmed:meshHeading
pubmed:year
1990
pubmed:articleTitle
Application of a variance-stabilizing transformation approach to linear regression of calibration lines.
pubmed:affiliation
Department of Biopharmaceutics and Pharmacokinetics, Schering-Plough Research, Miami, FL 33023.
pubmed:publicationType
Journal Article