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 (currently unpublished)" This methodology consist of (1) specifying a pharmacokinetic model including variability among animals; (2) generating possible sampling times; (3)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


News

version 1.0.5

# change random number generation using cholesky decomposition instead of eigenvalue decomposition
# remove write down options, only useful for debugging

version 1.0.3

# debugging option in data generation, to test over platforms 
    * fix seed type
    * add option to write down intermediate output to debug data generation

version 1.0.0

# first version for CRAN with vignette

Reference manual

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install.packages("microsamplingDesign")

1.0.5 by Adriaan Blommaert, 5 months ago


http://www.openanalytics.eu


Browse source code at https://github.com/cran/microsamplingDesign


Authors: Adriaan Blommaert [aut, cre] , Daan Seynaeve [ctb] , Helen Barnett [ctb] , Helena Geys [ctb] , Tom Jacobs [ctb] , Fetene Tekle [ctb] , Thomas Jaki [ctb]


Documentation:   PDF Manual  


GPL-3 license


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

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

Linking to Rcpp, RcppArmadillo


See at CRAN