CRAN/E | microsamplingDesign

microsamplingDesign

Finding Optimal Microsampling Designs for Non-Compartmental Pharmacokinetic Analysis

Installation

About

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 (currently unpublished)" This methodology consist of (1) specifying a pharmacokinetic model including variability among animals; (2) generating possible sampling times; (3)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.

www.openanalytics.eu/

Key Metrics

Version 1.0.8
R ≥ 3.4.0
Published 2021-10-13 897 days ago
Needs compilation? yes
License GPL-3
CRAN checks microsamplingDesign results

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Maintainer

Maintainer

Adriaan Blommaert

adriaan.blommaert@openanalytics.eu

Authors

Adriaan Blommaert

aut / cre

Daan Seynaeve

ctb

Helen Barnett

ctb

Helena Geys

ctb

Tom Jacobs

ctb

Fetene Tekle

ctb

Thomas Jaki

ctb

Material

NEWS
Reference manual
Package source

In Views

Pharmacokinetics

Vignettes

microsamplingDesign

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

microsamplingDesign archive

Depends

R ≥ 3.4.0
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

LinkingTo

Rcpp
RcppArmadillo