microsamplingDesign

Finding Optimal Microsampling Designs for Non-Compartmental Pharmacokinetic Analysis

Find optimal microsampling designs for non-compartmental pharacokinetic analysis using a general simulation methodology: Algorithm III of Barnett, Helen, Helena Geys, Tom Jacobs, and Thomas Jaki. (2017) "Optimal Designs for Non-Compartmental Analysis of Pharmacokinetic Studies. (currently unpublished)" This methodology consist of (1) specifying a pharmacokinetic model including variability among animals; (2) generating possible sampling times; (3) evaluating performance of each time point choice on simulated data; (4) generating possible schemes given a time point choice and additional constraints and finally (5) evaluating scheme performance on simulated data. The default settings differ from the article of Barnett and others, in the default pharmacokinetic model used and the parameterization of variability among animals. Details can be found in the package vignette. A 'shiny' web application is included, which guides users from model parametrization to optimal microsampling scheme.

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Package
microsamplingDesign
Title
Finding Optimal Microsampling Designs for Non-Compartmental Pharmacokinetic Analysis
Version
1.0.2
License
GPL-3
Maintainer
Adriaan Blommaert
Description
Find optimal microsampling designs for non-compartmental pharacokinetic analysis using a general simulation methodology: Algorithm III of Barnett, Helen, Helena Geys, Tom Jacobs, and Thomas Jaki. (2017) "Optimal Designs for Non-Compartmental Analysis of Pharmacokinetic Studies. (currently unpublished)" This methodology consist of (1) specifying a pharmacokinetic model including variability among animals; (2) generating possible sampling times; (3) evaluating performance of each time point choice on simulated data; (4) generating possible schemes given a time point choice and additional constraints and finally (5) evaluating scheme performance on simulated data. The default settings differ from the article of Barnett and others, in the default pharmacokinetic model used and the parameterization of variability among animals. Details can be found in the package vignette. A 'shiny' web application is included, which guides users from model parametrization to optimal microsampling scheme.
URL
Depends
R (>= 3.3.2), Rcpp
Imports
abind, deSolve, devtools, ggplot2, gridExtra, gtools, knitr, MASS, matrixStats, matrixcalc, methods, parallel, plyr, readr, reshape2, shiny, stats, stringr, utils
LinkingTo
Rcpp, RcppArmadillo
ByteCompile
true
LazyLoad
yes
RoxygenNote
6.0.1
Suggests
bookdown, data.table, plotly, shinyjs, shinyBS, rmarkdown, rhandsontable, shinycssloaders, testthat
Collate
'RcppExports.R' 'aaaGenerics.R' 'appFunctions.R' 'constraintFunctions.R' 'fastRankSchemes.R' 'internalHelpers.R' 'objectPkModelParent.R' 'objectSetOfSchemes.R' 'objectPkModel.R' 'objectPkModelRange.R' 'objectSetOfTimePoints.R' 'pkFunctions.R' 'schemeStatistics.R' 'rankScheme.R' 'rankTimePoints.R' 'schemeGenerator.R' 'timePointGeneration.R'
VignetteBuilder
knitr
NeedsCompilation
yes
Packaged
2018-05-03 11:57:26 UTC; ablommaert
Author
Adriaan Blommaert [aut, cre], Daan Seynaeve [ctb], Helen Barnett [ctb], Helena Geys [ctb], Tom Jacobs [ctb], Fetene Tekle [ctb], Thomas Jaki [ctb]
Repository
CRAN
Date/Publication
2018-05-14 13:32:21 UTC

install.packages('microsamplingDesign')

1.0.2

6 days ago

http://www.openanalytics.eu

Adriaan Blommaert

GPL-3

Depends on

R (>= 3.3.2), Rcpp

Imports

abind, deSolve, devtools, ggplot2, gridExtra, gtools, knitr, MASS, matrixStats, matrixcalc, methods, parallel, plyr, readr, reshape2, shiny, stats, stringr, utils

Suggests

bookdown, data.table, plotly, shinyjs, shinyBS, rmarkdown, rhandsontable, shinycssloaders, testthat

Discussions