Literature DB >> 16341474

Optimal blood sampling time windows for parameter estimation using a population approach: design of a phase II clinical trial.

Marylore Chenel1, Kayode Ogungbenro, Vincent Duval, Christian Laveille, Roeline Jochemsen, Leon Aarons.   

Abstract

The objective of this paper is to determine optimal blood sampling time windows for the estimation of pharmacokinetic (PK) parameters by a population approach within the clinical constraints. A population PK model was developed to describe a reference phase II PK dataset. Using this model and the parameter estimates, D-optimal sampling times were determined by optimising the determinant of the population Fisher information matrix (PFIM) using PFIM_ _M 1.2 and the modified Fedorov exchange algorithm. Optimal sampling time windows were then determined by allowing the D-optimal windows design to result in a specified level of efficiency when compared to the fixed-times D-optimal design. The best results were obtained when K(a) and IIV on K(a) were fixed. Windows were determined using this approach assuming 90% level of efficiency and uniform sample distribution. Four optimal sampling time windows were determined as follow: at trough between 22 h and new drug administration; between 2 and 4 h after dose for all patients; and for 1/3 of the patients only 2 sampling time windows between 4 and 10 h after dose, equal to [4 h-5 h 05] and [9 h 10-10 h]. This work permitted the determination of an optimal design, with suitable sampling time windows which was then evaluated by simulations. The sampling time windows will be used to define the sampling schedule in a prospective phase II study.

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Year:  2005        PMID: 16341474     DOI: 10.1007/s10928-005-0014-6

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


  11 in total

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Authors:  S Retout; S Duffull; F Mentré
Journal:  Comput Methods Programs Biomed       Date:  2001-05       Impact factor: 5.428

2.  Optimal design of a population pharmacodynamic experiment for ivabradine.

Authors:  S B Duffull; F Mentré; L Aarons
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3.  Experimental design and efficient parameter estimation in population pharmacokinetics.

Authors:  M K al-Banna; A W Kelman; B Whiting
Journal:  J Pharmacokinet Biopharm       Date:  1990-08

4.  The use of a modified Fedorov exchange algorithm to optimise sampling times for population pharmacokinetic experiments.

Authors:  Kayode Ogungbenro; Gordon Graham; Ivelina Gueorguieva; Leon Aarons
Journal:  Comput Methods Programs Biomed       Date:  2005-08-31       Impact factor: 5.428

5.  Practical experience and issues in designing and performing population pharmacokinetic/pharmacodynamic studies.

Authors:  L Aarons; L P Balant; F Mentre; P L Morselli; M Rowland; J L Steimer; S Vozeh
Journal:  Eur J Clin Pharmacol       Date:  1996       Impact factor: 2.953

6.  Comparison of some practical sampling strategies for population pharmacokinetic studies.

Authors:  E N Jonsson; J R Wade; M O Karlsson
Journal:  J Pharmacokinet Biopharm       Date:  1996-04

7.  Population pharmacokinetic analysis and optimization of the experimental design for mizolastine solution in children.

Authors:  F Mentré; C Dubruc; J P Thénot
Journal:  J Pharmacokinet Pharmacodyn       Date:  2001-06       Impact factor: 2.745

8.  Interpretation of simulation studies for efficient estimation of population pharmacokinetic parameters.

Authors:  E I Ette; A W Kelman; C A Howie; B Whiting
Journal:  Ann Pharmacother       Date:  1993-09       Impact factor: 3.154

9.  Development of a dosing strategy for enoxaparin in obese patients.

Authors:  Bruce Green; Stephen B Duffull
Journal:  Br J Clin Pharmacol       Date:  2003-07       Impact factor: 4.335

10.  Fisher information matrix for non-linear mixed-effects models: evaluation and application for optimal design of enoxaparin population pharmacokinetics.

Authors:  Sylvie Retout; France Mentré; René Bruno
Journal:  Stat Med       Date:  2002-09-30       Impact factor: 2.373

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  3 in total

1.  Model-based approaches for ivabradine development in paediatric population, part I: study preparation assessment.

Authors:  Sophie Peigné; François Bouzom; Karl Brendel; Charlotte Gesson; Sylvain Fouliard; Marylore Chenel
Journal:  J Pharmacokinet Pharmacodyn       Date:  2015-11-12       Impact factor: 2.745

2.  A d-optimal designed population pharmacokinetic study of oral itraconazole in adult cystic fibrosis patients.

Authors:  Stefanie Hennig; Timothy H Waterhouse; Scott C Bell; Megan France; Claire E Wainwright; Hugh Miller; Bruce G Charles; Stephen B Duffull
Journal:  Br J Clin Pharmacol       Date:  2006-10-30       Impact factor: 4.335

3.  Drug-drug interaction predictions with PBPK models and optimal multiresponse sampling time designs: application to midazolam and a phase I compound. Part 1: comparison of uniresponse and multiresponse designs using PopDes.

Authors:  Marylore Chenel; François Bouzom; Leon Aarons; Kayode Ogungbenro
Journal:  J Pharmacokinet Pharmacodyn       Date:  2009-01-07       Impact factor: 2.745

  3 in total

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