Package: DTAT 0.3-8

DTAT: Dose Titration Algorithm Tuning

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 (2017a) <doi:10.12688/f1000research.10624.3> and Norris (2017c) <doi:10.1101/240846>.

Authors:David C. Norris [aut, cre]

DTAT_0.3-8.tar.gz
DTAT_0.3-8.zip(r-4.7-any)DTAT_0.3-8.zip(r-4.6-any)DTAT_0.3-8.zip(r-4.5-any)
DTAT_0.3-8.tgz(r-4.6-any)DTAT_0.3-8.tgz(r-4.5-any)
DTAT_0.3-8.tar.gz(r-4.7-any)DTAT_0.3-8.tar.gz(r-4.6-any)
DTAT_0.3-8.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
DTAT/json (API)

# Install 'DTAT' in R:
install.packages('DTAT', repos = c('https://dcnorris.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • de.bioRxiv.240846 - Simulated '3+3/PC' dose-titration study from bioRxiv paper no. 240846
  • dtat1000 - Precomputed neutrophil-guided chemotherapy dose titration for 1000 simulated subjects.

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.92 score 21 scripts 351 downloads 2 mentions 11 exports 80 dependencies

Last updated from:7f60dd902f. Checks:7 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develWARNING221
source / vignettesOK241
linux-releaseWARNING185
macos-releaseWARNING207
macos-oldrelWARNING213
windows-develWARNING128
windows-releaseWARNING142
windows-oldrelWARNING133
wasm-releaseOK161

Exports:as_d3_datadose.survfitdose.survivalds.curvenewton.raphsonOnoue.FribergplotrunDTATappsimtitratetitration

Dependencies:backportsbase64encbslibcachemcheckmatecliclustercodacolorspacecommonmarkcpp11data.tabledeSolvedigestdplyrevaluatefarverfastmapfontawesomeforeignFormulafsgenericsggplot2gluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetshttpuvisobandjquerylibjsonlitekm.ciknitrlabelinglaterlatticelifecyclemagrittrMatrixmemoisemimemvtnormnnetotelpillarpkgconfigpomppromisesr2d3R6rappdirsRColorBrewerRcpprlangrmarkdownrpartrstudioapiS7sassscalesshinysourcetoolsstringistringrsurvivaltibbletidyselecttinytexutf8vctrsviridisLitewithrxfunxtableyaml

Code and figures for 'DTAT should supersede MTD' v1
Pharmacokinetic model | Myelosuppression model | Simulated population (inter-individual heterogeneity) | PK/PD simulation model | Adaptive dosing based on a simple Newton-Raphson heuristic | Linearize dynamics | Would day-7 ANC suffice as a proxy for nadir? | Simulated dose titration in 25 study subjects | SessionInfo
Rendered fromdtat.Rmdusingknitr::rmarkdown

Last update: 2023-03-29
Started: 2023-03-29

Designing a 3+3/PC trial
Precautionary Coherence and the '3+3/PC' Design | Optimal-Dose Heterogeneity | Precautionary Coherence and Dose Ranging | Precautionary Coherence | Dose Ranging in General | 3+3/PC as a Dose Ranging Design | Dose Ranging in Our Example | Simulating your 3+3/PC Trial | Introduction to the Dose-Titration Diagram | 3+3/PC Rules | An Interactive 3+3/PC Design & Simulation App | References
Rendered fromDesigning-33PC.Rmdusingknitr::rmarkdown

Last update: 2020-06-14
Started: 2019-02-18