PopED: an extended, parallelized, nonlinear mixed effects models optimal design tool

Nyberg, Joakim, Ueckert, Sebastian, Strömberg, Eric A., Hennig, Stefanie, Karlsson, Mats O. and Hooker, Andrew C. (2012) PopED: an extended, parallelized, nonlinear mixed effects models optimal design tool. Computer Methods and Programs in Biomedicine, 108 2: 789-805. doi:10.1016/j.cmpb.2012.05.005

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Author Nyberg, Joakim
Ueckert, Sebastian
Strömberg, Eric A.
Hennig, Stefanie
Karlsson, Mats O.
Hooker, Andrew C.
Total Author Count Override 7
Title PopED: an extended, parallelized, nonlinear mixed effects models optimal design tool
Journal name Computer Methods and Programs in Biomedicine   Check publisher's open access policy
ISSN 0169-2607
1872-7565
Publication date 2012-11
Year available 2012
Sub-type Article (original research)
DOI 10.1016/j.cmpb.2012.05.005
Volume 108
Issue 2
Start page 789
End page 805
Total pages 17
Place of publication Shannon, Co. Clare, Ireland
Publisher Elsevier
Collection year 2013
Language eng
Formatted abstract
Several developments have facilitated the practical application and increased the general use of optimal design for nonlinear mixed effects models. These developments include new methodology for utilizing advanced pharmacometric models, faster optimization algorithms and user friendly software tools. In this paper we present the extension of the optimal design software PopED, which incorporates many of these recent advances into an easily useable enhanced GUI. Furthermore, we present new solutions to problems related to the design of experiments such as: faster and more robust FIM calculations and optimizations, optimizing over cost/utility functions and diagnostic tools and plots to evaluate design performance. Examples for; (i) Group size optimization and efficiency translation, (ii) Cost/constraint optimization, (iii) Optimizations with different FIM approximations and (iv) optimization with parallel computing demonstrate the new features in PopED and underline the potential use of this tool when designing experiments.
Keyword Pharmacometrics
Optimal experimental design
Population PKPD
Parallelization
Cost optimization
Fisher information matrix linearization
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Available online 26 May 2012. Authors prepress title: "PopED: An improved optimal experimental design software".

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2013 Collection
School of Pharmacy Publications
 
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Citation counts: TR Web of Science Citation Count  Cited 22 times in Thomson Reuters Web of Science Article | Citations
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Created: Wed, 16 May 2012, 15:44:04 EST by Dr Stefanie Hennig on behalf of School of Pharmacy