Literature DB >> 11999293

Information tools for exploratory data analysis in population pharmacokinetics.

O Petricoul1, L Claret, D Barbolosi, A Iliadis, C Puozzo.   

Abstract

For a group of individuals, population pharmacokinetic studies describe the interindividual variability through a statistical distribution. These studies conducted during the drug development serve as a useful marker of the safety of the drug, provide information that might be decisive for future experiments and, in a clinical context, help establish guidelines for optimal use in each patient. As complementary tools to the existing statistical and graphical techniques for population pharmacokinetic data analysis, indexes derived from information theory were used to select the most appropriate modelfor the statistical distribution, to detect atypical individuals, and to screen influential covariates. The rationale for using these indexes is shown using simulated and real data.

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Year:  2001        PMID: 11999293     DOI: 10.1023/a:1014464505261

Source DB:  PubMed          Journal:  J Pharmacokinet Pharmacodyn        ISSN: 1567-567X            Impact factor:   2.745


  7 in total

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Journal:  Comput Methods Programs Biomed       Date:  1992-08       Impact factor: 5.428

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Authors:  L Claret; A Iliadis
Journal:  Math Biosci       Date:  1996-04-01       Impact factor: 2.144

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Authors:  E I Ette; T M Ludden
Journal:  Pharm Res       Date:  1995-12       Impact factor: 4.200

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5.  Psychopharmacology of midalcipran, 1-phenyl-1-diethyl-amino-carbonyl-2-aminomethylcyclopropane hydrochloride (F 2207), a new potential antidepressant.

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Journal:  Psychopharmacology (Berl)       Date:  1987       Impact factor: 4.530

6.  Double-blind placebo-controlled study of milnacipran in hospitalized patients with major depressive disorders.

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Journal:  Neuropsychobiology       Date:  1989       Impact factor: 2.328

7.  The population approach to pharmacokinetic data analysis: rationale and standard data analysis methods.

Authors:  L B Sheiner
Journal:  Drug Metab Rev       Date:  1984       Impact factor: 4.518

  7 in total
  2 in total

1.  PKreport: report generation for checking population pharmacokinetic model assumptions.

Authors:  Xiaoyong Sun; Jun Li
Journal:  BMC Med Inform Decis Mak       Date:  2011-05-16       Impact factor: 2.796

2.  Exploring population pharmacokinetic modeling with resampling visualization.

Authors:  Fenghua Zuo; Jun Li; Xiaoyong Sun
Journal:  Biomed Res Int       Date:  2014-05-04       Impact factor: 3.411

  2 in total

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