Literature DB >> 16463254

Optimum blood sampling time windows for parameter estimation in population pharmacokinetic experiments.

Gordon Graham1, Leon Aarons.   

Abstract

Clinical trials requiring the collection of pharmacokinetic information often specify blood samples to be taken at fixed times. This may be feasible when trial participants are in a controlled environment such as in early phase clinical trials, however it becomes problematic in trials where patients are in an out-patient clinic setting such as in late phase drug development. In such a situation it is common to take blood samples when it is convenient for all involved and may result in data that are uninformative. This paper proposes an approach to pharmacokinetic study design that allows greater flexibility as to when blood samples can be taken and still result in data that allows satisfactory parameter estimation. The sampling window approach proposed in this paper is based on determining time intervals around the D-optimum pharmacokinetic sampling times. These intervals are determined by allowing the sampling window design to result in a specified level of efficiency when compared to the fixed times D-optimum design. Several approaches are suggested for dealing with this design problem.

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Year:  2006        PMID: 16463254     DOI: 10.1002/sim.2512

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  4 in total

1.  Population Fisher information matrix and optimal design of discrete data responses in population pharmacodynamic experiments.

Authors:  Kayode Ogungbenro; Leon Aarons
Journal:  J Pharmacokinet Pharmacodyn       Date:  2011-06-10       Impact factor: 2.745

2.  A sequential Monte Carlo approach to derive sampling times and windows for population pharmacokinetic studies.

Authors:  J M McGree; C C Drovandi; A N Pettitt
Journal:  J Pharmacokinet Pharmacodyn       Date:  2012-07-31       Impact factor: 2.745

3.  Optimisation of sampling windows design for population pharmacokinetic experiments.

Authors:  Kayode Ogungbenro; Leon Aarons
Journal:  J Pharmacokinet Pharmacodyn       Date:  2008-09-09       Impact factor: 2.745

4.  Optimal design for multiresponse pharmacokinetic-pharmacodynamic models - dealing with unbalanced designs.

Authors:  Kayode Ogungbenro; Ivelina Gueorguieva; Oneeb Majid; Gordon Graham; Leon Aarons
Journal:  J Pharmacokinet Pharmacodyn       Date:  2007-02-07       Impact factor: 2.410

  4 in total

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