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posologyr: Individual Dose Optimization using Population Pharmacokinetics
Personalize drug regimens using individual pharmacokinetic (PK) and
pharmacokinetic-pharmacodynamic (PK-PD) profiles. By combining therapeutic
drug monitoring (TDM) data with a population model, 'posologyr' offers
accurate posterior estimates and helps compute optimal individualized dosing
regimens. The empirical Bayes estimates are computed following the method
described by Kang et al. (2012) <doi:10.4196/kjpp.2012.16.2.97>.
| Version: |
1.2.8 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
rxode2, stats, mvtnorm, data.table |
| Suggests: |
lotri, rmarkdown, testthat (≥ 3.0.0), ggplot2, magrittr, tidyr |
| Published: |
2025-02-04 |
| DOI: |
10.32614/CRAN.package.posologyr |
| Author: |
Cyril Leven  [aut,
cre, cph],
Matthew Fidler
[ctb],
Emmanuelle Comets [ctb],
Audrey Lavenu [ctb],
Marc Lavielle [ctb] |
| 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 |
Documentation:
Downloads:
Linking:
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https://CRAN.R-project.org/package=posologyr
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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