Personalize drug regimens using individual pharmacokinetic and pharmacokinetic-pharmacodynamic profiles. Using combining therapeutic drug monitoring (TDM) data and a population model, 'posologyr' provides accurate a posteriori estimates and allows you to compute the optimal individualized dosing regimen. The empirical Bayes estimates are computed as described in Kang et al. (2012) <doi:10.4196/kjpp.2012.16.2.97>.
Version: | 1.2.6 |
Depends: | R (≥ 3.5.0) |
Imports: | rxode2, stats, mvtnorm, data.table |
Suggests: | lotri, knitr, rmarkdown, testthat (≥ 3.0.0), ggplot2, magrittr, tidyr |
Published: | 2024-08-27 |
DOI: | 10.32614/CRAN.package.posologyr |
Author: | Cyril Leven |
Maintainer: | Cyril Leven <cyril.leven at chu-brest.fr> |
BugReports: | https://github.com/levenc/posologyr/issues |
License: | AGPL-3 |
URL: | https://levenc.github.io/posologyr/, https://github.com/levenc/posologyr |
NeedsCompilation: | no |
Citation: | posologyr citation info |
Materials: | README NEWS |
In views: | Pharmacokinetics |
CRAN checks: | posologyr results |
Reference manual: | posologyr.pdf |
Vignettes: |
A posteriori dose selection (source, R code) A priori dose selection (source, R code) AUC-based dose selection (source, R code) Classic posologyr models (source, R code) Multiple endpoints (source, R code) Patient data (source, R code) Population models (source, R code) Route of administration (source, R code) |
Package source: | posologyr_1.2.6.tar.gz |
Windows binaries: | r-devel: posologyr_1.2.6.zip, r-release: posologyr_1.2.6.zip, r-oldrel: posologyr_1.2.6.zip |
macOS binaries: | r-release (arm64): posologyr_1.2.6.tgz, r-oldrel (arm64): posologyr_1.2.6.tgz, r-release (x86_64): posologyr_1.2.6.tgz, r-oldrel (x86_64): posologyr_1.2.6.tgz |
Old sources: | posologyr archive |
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