PKreport: report generation for checking population pharmacokinetic model assumptions

<p>Abstract</p> <p>Background</p> <p>Graphics play an important and unique role in population pharmacokinetic (PopPK) model building by exploring hidden structure among data before modeling, evaluating model fit, and validating results after modeling.</p> <p>...

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Main Authors: Li Jun, Sun Xiaoyong
Format: Article
Language:English
Published: BMC 2011-05-01
Series:BMC Medical Informatics and Decision Making
Online Access:http://www.biomedcentral.com/1472-6947/11/31
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spelling doaj-96e6140a5d314b1b909ba2b008a37ce72020-11-25T01:32:31ZengBMCBMC Medical Informatics and Decision Making1472-69472011-05-011113110.1186/1472-6947-11-31PKreport: report generation for checking population pharmacokinetic model assumptionsLi JunSun Xiaoyong<p>Abstract</p> <p>Background</p> <p>Graphics play an important and unique role in population pharmacokinetic (PopPK) model building by exploring hidden structure among data before modeling, evaluating model fit, and validating results after modeling.</p> <p>Results</p> <p>The work described in this paper is about a new R package called PKreport, which is able to generate a collection of plots and statistics for testing model assumptions, visualizing data and diagnosing models. The metric system is utilized as the currency for communicating between data sets and the package to generate special-purpose plots. It provides ways to match output from diverse software such as NONMEM, Monolix, R nlme package, etc. The package is implemented with S4 class hierarchy, and offers an efficient way to access the output from NONMEM 7. The final reports take advantage of the web browser as user interface to manage and visualize plots.</p> <p>Conclusions</p> <p>PKreport provides 1) a flexible and efficient R class to store and retrieve NONMEM 7 output, 2) automate plots for users to visualize data and models, 3) automatically generated R scripts that are used to create the plots; 4) an archive-oriented management tool for users to store, retrieve and modify figures, 5) high-quality graphs based on the R packages, lattice and ggplot2. The general architecture, running environment and statistical methods can be readily extended with R class hierarchy. PKreport is free to download at <url>http://cran.r-project.org/web/packages/PKreport/index.html</url>.</p> http://www.biomedcentral.com/1472-6947/11/31
collection DOAJ
language English
format Article
sources DOAJ
author Li Jun
Sun Xiaoyong
spellingShingle Li Jun
Sun Xiaoyong
PKreport: report generation for checking population pharmacokinetic model assumptions
BMC Medical Informatics and Decision Making
author_facet Li Jun
Sun Xiaoyong
author_sort Li Jun
title PKreport: report generation for checking population pharmacokinetic model assumptions
title_short PKreport: report generation for checking population pharmacokinetic model assumptions
title_full PKreport: report generation for checking population pharmacokinetic model assumptions
title_fullStr PKreport: report generation for checking population pharmacokinetic model assumptions
title_full_unstemmed PKreport: report generation for checking population pharmacokinetic model assumptions
title_sort pkreport: report generation for checking population pharmacokinetic model assumptions
publisher BMC
series BMC Medical Informatics and Decision Making
issn 1472-6947
publishDate 2011-05-01
description <p>Abstract</p> <p>Background</p> <p>Graphics play an important and unique role in population pharmacokinetic (PopPK) model building by exploring hidden structure among data before modeling, evaluating model fit, and validating results after modeling.</p> <p>Results</p> <p>The work described in this paper is about a new R package called PKreport, which is able to generate a collection of plots and statistics for testing model assumptions, visualizing data and diagnosing models. The metric system is utilized as the currency for communicating between data sets and the package to generate special-purpose plots. It provides ways to match output from diverse software such as NONMEM, Monolix, R nlme package, etc. The package is implemented with S4 class hierarchy, and offers an efficient way to access the output from NONMEM 7. The final reports take advantage of the web browser as user interface to manage and visualize plots.</p> <p>Conclusions</p> <p>PKreport provides 1) a flexible and efficient R class to store and retrieve NONMEM 7 output, 2) automate plots for users to visualize data and models, 3) automatically generated R scripts that are used to create the plots; 4) an archive-oriented management tool for users to store, retrieve and modify figures, 5) high-quality graphs based on the R packages, lattice and ggplot2. The general architecture, running environment and statistical methods can be readily extended with R class hierarchy. PKreport is free to download at <url>http://cran.r-project.org/web/packages/PKreport/index.html</url>.</p>
url http://www.biomedcentral.com/1472-6947/11/31
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AT sunxiaoyong pkreportreportgenerationforcheckingpopulationpharmacokineticmodelassumptions
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