Linked Life Data

1761728

Source:http://linkedlifedata.com/resource/pubmed/id/1761728

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
10
pubmed:dateCreated
1992-2-7
pubmed:abstractText
Newer mathematical techniques such as optimal sampling theory and NON-linear Mixed Effects Modelling (NONMEM) allow the determination of pharmacokinetics and pharmacodynamics in populations of individuals previously believed to be "too ill" or "too difficult to study." Optimal sampling determines the most information-rich times to sample the system, allowing robust parameter estimates to be determined from the minimal number of samples. NONMEM, by taking the population as the unit of analysis, allows even fragmentary patient data sets to contribute to population parameter estimates. Obviously, the microgravity environment presents extreme logistical difficulties to the performance of traditional pharmacokinetic and pharmacodynamic studies. Examples of the validation of these techniques are presented, which indicates their likely utility in the important task of determining the influence of the microgravity environment on drug distribution and elimination, even accounting for the limitations of support which will be faced in this circumstance.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
0091-2700
pubmed:author
pubmed:issnType
Print
pubmed:volume
31
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
962-7
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1991
pubmed:articleTitle
Optimal sampling theory and population modelling: application to determination of the influence of the microgravity environment on drug distribution and elimination.
pubmed:affiliation
Division of Infectious Diseases, University of Maryland School of Medicine, Baltimore 21201.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S.