Literature DB >> 1783988

A population analysis of the pharmacokinetics and pharmacodynamics of midazolam in the rat.

L Aarons1, J W Mandema, M Danhof.   

Abstract

The concentration-EEG effect relationship of midazolam in the rat was studied from a population perspective. Plasma concentration and EEG effect data from 27 rats were available for analysis. Effect parameters derived from aperiodic EEG analysis were used as effect parameters. The population analysis gave results that were similar to the sample theory estimates (means s and SDs) obtained from the fits to individual data sets. Reanalysis of the EEG data using mean population pharmacokinetic parameters as input to the pharmacodynamic model led to poorer estimation of the pharmacodynamic parameters: particularly EC50. Inclusion of one observed plasma concentration per individual significantly improved the estimation of the pharmacodynamic parameters and led to results that were virtually indistinguishable from those obtained using complete pharmacokinetic data.

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Year:  1991        PMID: 1783988     DOI: 10.1007/bf01062959

Source DB:  PubMed          Journal:  J Pharmacokinet Biopharm        ISSN: 0090-466X


  9 in total

1.  Pharmacokinetic-pharmacodynamic modelling of the EEG effects of midazolam in individual rats: influence of rate and route of administration.

Authors:  J W Mandema; E Tukker; M Danhof
Journal:  Br J Pharmacol       Date:  1991-03       Impact factor: 8.739

2.  Pharmacokinetic-pharmacodynamic modeling of the central nervous system effects of heptabarbital using aperiodic EEG analysis.

Authors:  J W Mandema; M Danhof
Journal:  J Pharmacokinet Biopharm       Date:  1990-10

3.  Quantification of the EEG effect of midazolam by aperiodic analysis in volunteers. Pharmacokinetic/pharmacodynamic modelling.

Authors:  L T Breimer; P J Hennis; A G Burm; M Danhof; J G Bovill; J Spierdijk; A A Vletter
Journal:  Clin Pharmacokinet       Date:  1990-03       Impact factor: 6.447

4.  Pharmacokinetic and electroencephalographic study of intravenous diazepam, midazolam, and placebo.

Authors:  D J Greenblatt; B L Ehrenberg; J Gunderman; A Locniskar; J M Scavone; J S Harmatz; R I Shader
Journal:  Clin Pharmacol Ther       Date:  1989-04       Impact factor: 6.875

5.  An electroencephalographic processing algorithm specifically intended for analysis of cerebral electrical activity.

Authors:  T K Gregory; D C Pettus
Journal:  J Clin Monit       Date:  1986-07

6.  Pharmacokinetic-pharmacodynamic modeling of midazolam effects on the human central nervous system.

Authors:  R Koopmans; J Dingemanse; M Danhof; G P Horsten; C J van Boxtel
Journal:  Clin Pharmacol Ther       Date:  1988-07       Impact factor: 6.875

Review 7.  Kinetics of pharmacologic response.

Authors:  N H Holford; L B Sheiner
Journal:  Pharmacol Ther       Date:  1982       Impact factor: 12.310

8.  Bayesian individualization of pharmacokinetics: simple implementation and comparison with non-Bayesian methods.

Authors:  L B Sheiner; S L Beal
Journal:  J Pharm Sci       Date:  1982-12       Impact factor: 3.534

9.  Pharmacokinetic-pharmacodynamic modeling of the electroencephalographic effects of benzodiazepines. Correlation with receptor binding and anticonvulsant activity.

Authors:  J W Mandema; L N Sansom; M C Dios-Vièitez; M Hollander-Jansen; M Danhof
Journal:  J Pharmacol Exp Ther       Date:  1991-04       Impact factor: 4.030

  9 in total
  9 in total

1.  Nonlinearity detection: advantages of nonlinear mixed-effects modeling.

Authors:  E N Jonsson; J R Wade; M O Karlsson
Journal:  AAPS PharmSci       Date:  2000

2.  Development of a whole body physiologically based model to characterise the pharmacokinetics of benzodiazepines. 1: Estimation of rat tissue-plasma partition ratios.

Authors:  Ivelina Gueorguieva; Ivan A Nestorov; Susan Murby; Sophie Gisbert; Brent Collins; Kelly Dickens; Judith Duffy; Ziad Hussain; Malcolm Rowland
Journal:  J Pharmacokinet Pharmacodyn       Date:  2004-08       Impact factor: 2.745

3.  Propagation of population pharmacokinetic information using a Bayesian approach: comparison with meta-analysis.

Authors:  Aristides Dokoumetzidis; Leon Aarons
Journal:  J Pharmacokinet Pharmacodyn       Date:  2005-08       Impact factor: 2.745

4.  Combining MCMC with 'sequential' PKPD modelling.

Authors:  David Lunn; Nicky Best; David Spiegelhalter; Gordon Graham; Beat Neuenschwander
Journal:  J Pharmacokinet Pharmacodyn       Date:  2009-01-09       Impact factor: 2.745

Review 5.  Pharmacokinetic and pharmacodynamic data and models in clinical trials.

Authors:  J L Steimer; M E Ebelin; J Van Bree
Journal:  Eur J Drug Metab Pharmacokinet       Date:  1993 Jan-Mar       Impact factor: 2.441

Review 6.  Sparse data analysis.

Authors:  L Aarons
Journal:  Eur J Drug Metab Pharmacokinet       Date:  1993 Jan-Mar       Impact factor: 2.441

Review 7.  Role of population pharmacokinetics in drug development. A pharmaceutical industry perspective.

Authors:  E Samara; R Granneman
Journal:  Clin Pharmacokinet       Date:  1997-04       Impact factor: 6.447

8.  Population pharmacokinetic analysis of voriconazole plasma concentration data from pediatric studies.

Authors:  Mats O Karlsson; Irja Lutsar; Peter A Milligan
Journal:  Antimicrob Agents Chemother       Date:  2008-12-15       Impact factor: 5.191

Review 9.  Scaling basic toxicokinetic parameters from rat to man.

Authors:  K Bachmann; D Pardoe; D White
Journal:  Environ Health Perspect       Date:  1996-04       Impact factor: 9.031

  9 in total

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