Dose Titration Algorithm Tuning (DTAT) is a methodologic framework allowing dose individualization to be conceived as a continuous learning process that begins in early-phase clinical trials and continues throughout drug development, on into clinical practice. This package includes code that researchers may use to reproduce or extend key results of the DTAT research programme, plus tools for trialists to design and simulate a '3+3/PC' dose-finding study. Please see Norris (2017) <doi:10.12688/f1000research.10624.3> and Norris (2017) <doi:10.1101/240846>.
| Version: | 0.3-4 |
| Depends: | R (≥ 3.4.0), survival |
| Imports: | km.ci, pomp, Hmisc, data.table, dplyr, r2d3, shiny, jsonlite, methods |
| Suggests: | knitr, rmarkdown, lattice, latticeExtra, widgetframe, tidyr, RColorBrewer |
| Published: | 2020-06-14 |
| Author: | David C. Norris [aut, cre] |
| Maintainer: | David C. Norris <david at precisionmethods.guru> |
| License: | MIT + file LICENSE |
| URL: | https://precisionmethods.guru/ |
| NeedsCompilation: | no |
| Citation: | DTAT citation info |
| CRAN checks: | DTAT results |
| Reference manual: | DTAT.pdf |
| Vignettes: |
Exploring the '3+3/PC' dose-titration design |
| Package source: | DTAT_0.3-4.tar.gz |
| Windows binaries: | r-devel: DTAT_0.3-4.zip, r-release: DTAT_0.3-4.zip, r-oldrel: DTAT_0.3-4.zip |
| macOS binaries: | r-release: DTAT_0.3-4.tgz, r-oldrel: DTAT_0.3-4.tgz |
| Old sources: | DTAT archive |
Please use the canonical form https://CRAN.R-project.org/package=DTAT to link to this page.