Literature DB >> 2348381

Application of NONMEM to routine bioavailability data.

D A Graves1, I Chang.   

Abstract

Although NONMEM has been proposed as a modeling tool for sparse data sets, little work has described its application to pharmacokinetic data which is also amenable to typical evaluations. An analysis was performed with NONMEM using plasma concentration data obtained during the development of liquid and capsule extended-release (ER) pseudoephedrine products. A total of four studies (single dose and steady-state studies for both the liquid and capsule formulations) were evaluated, each with an immediate-release (IR) control, and consisting of 18 to 20 subjects. NONMEM analyses provided additional information which could not be obtained through traditional means. Specifically, NONMEM provided not only estimates of residual error from single dose and steady-state studies but also a stochastic measure of bioinequivalence and dose-dumping. It permitted hypothesis testing in the same process as pharmacokinetic parameter estimation, such as contrasting absorption rates from capsule and suspension ER products. A less biased estimate of absorption rate was obtainable for ER formulations by utilizing IR runs. Finally, these NONMEM runs confirmed that, even when data are plentiful and amenable to two-stage analyses, NONMEM provides estimates that may in fact be more meaningful and less susceptible to assay or residual variability. Fundamental differences between population and two-stage approaches are discussed.

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Year:  1990        PMID: 2348381     DOI: 10.1007/bf01063557

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


  8 in total

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  8 in total
  9 in total

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

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Journal:  AAPS PharmSci       Date:  2000

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Authors:  M Hossain; E Wright; R Baweja; T Ludden; R Miller
Journal:  Pharm Res       Date:  1997-03       Impact factor: 4.200

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

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Authors:  R Miller; T M Ludden
Journal:  Eur J Clin Pharmacol       Date:  1993       Impact factor: 2.953

9.  Smoking and body weight influence the clearance of chlorpromazine.

Authors:  M Chetty; R Miller; S V Moodley
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  9 in total

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