Package: iAdapt 2.0.1

Alyssa Vanderbeek

iAdapt: Two-Stage Adaptive Dose-Finding Clinical Trial Design

Simulate and implement early phase two-stage adaptive dose-finding design for binary and quasi-continuous toxicity endpoints. See Chiuzan et al. (2018) for further reading <doi:10.1080/19466315.2018.1462727>.

Authors:Alyssa Vanderbeek [aut, cre], Laura Cosgrove [ctb], Elizabeth Garrett-Mayer [ctb], Cody Chiuzan [ctb]

iAdapt_2.0.1.tar.gz
iAdapt_2.0.1.tar.gz(r-4.7-any)iAdapt_2.0.1.tar.gz(r-4.6-any)
iAdapt_2.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
iAdapt/json (API)

# Install 'iAdapt' in R:
install.packages('iAdapt', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • TOX - Sample array of toxicity probabilities for 6 doses. Taken from Du et al.

On CRAN:

Conda:

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

3.18 score 10 scripts 299 downloads 20 exports 33 dependencies

Last updated from:48db1d3f47. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK143
source / vignettesOK179
linux-release-x86_64OK145
wasm-releaseOK127

Exports:beta.abdlt.probeff.stg1eff.stg1.nTTPget.threshLRtoxLRtox.nTTPnTTP.indiv.simrand.probrand.stg2rand.stg2.nTTPrunExamplesafe.dosesafe.dose.nTTPsim.plotsim.summarysim.trialssim.trials.nTTPtox.profiletox.profile.nTTP

Dependencies:base64encbslibcachemclicommonmarkdigestfastmapfontawesomefsgluehtmltoolshttpuvjquerylibjsonlitelaterlatticelifecyclemagrittrMatrixmemoisemimeotelpromisesR6rappdirsRcpprlangsassshinyshinydashboardsourcetoolswithrxtable

Trial implementation
Stage 1: Establish the safety profile for all initial doses. | Using DLT as toxicity measure | Using quasi-continuous toxicity measure (nTTP) | Stage 2: Adaptive randomization based on efficacy outcomes.
Rendered fromImplementation_example.Rmdusingknitr::rmarkdown

Last update: 2021-08-06
Started: 2019-08-29

Trial simulation with binary toxicity measure
Overview | Scenario 1: Monotone dose-efficacy | One Trial Simulation | Stage 1: Establish the safety profile for all initial doses. | Stage 2: Adaptive randomization based on efficacy outcomes. | 100 Trials Simulations | Scenario 2: Non-monotone dose-efficacy | Stage 1: Establish the safety profile for all initial doses
Rendered fromDLT_simulation_example.Rmdusingknitr::rmarkdown

Last update: 2021-08-06
Started: 2020-09-02

Trial simulation with quasi-continuous toxicity measure
Overview | Statistical model for nTTP within the iAdapt framework | Simulation example | Specify design parameters | Calculate mean nTTP (mnTTP) and corresponding DLT rate per dose, and specify hypotheses | Simulate a single trial | Stage 1: Establish the safety profile for all initial doses. | Stage 2: Adaptive randomization based on efficacy outcomes. | Simulate 100 trials
Rendered fromnTTP_simulation_example.Rmdusingknitr::rmarkdown

Last update: 2021-08-06
Started: 2020-09-02