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DesignCTPB: Design Clinical Trials with Potential Biomarker Effect

Applying 'CUDA' 'GPUs' via 'Numba' for optimal clinical design. It allows the user to utilize a 'reticulate' 'Python' environment and run intensive Monte Carlo simulation to get the optimal cutoff for the clinical design with potential biomarker effect, which can guide the realistic clinical trials.

Version: 1.1.3
Depends: R (≥ 3.5.0)
Imports: reticulate, mnormt, fields, plotly, dplyr
Suggests: knitr, rmarkdown
Published: 2021-09-21
DOI: 10.32614/CRAN.package.DesignCTPB
Author: Yitao Lu ORCID iD [aut, cre], Belaid Moa [aut], Julie Zhou [aut], Li Xing ORCID iD [aut], Xuekui Zhang ORCID iD [aut]
Maintainer: Yitao Lu <yitaolu at uvic.ca>
BugReports: https://github.com/ubcxzhang/DesignCTPB/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/ubcxzhang/DesignCTPB, Y Lu (2020) <doi:10.1002/sim.8868>
NeedsCompilation: no
SystemRequirements: OpenSSL(>= 1.0.1), NVIDIA CUDA GPU with compute capability 3.0 or above and NVIDIA CUDA Toolkit 9.0 or above
Citation: DesignCTPB citation info
Materials: README
CRAN checks: DesignCTPB results

Documentation:

Reference manual: DesignCTPB.pdf
Vignettes: DesignCTPB

Downloads:

Package source: DesignCTPB_1.1.3.tar.gz
Windows binaries: r-devel: DesignCTPB_1.1.3.zip, r-release: DesignCTPB_1.1.3.zip, r-oldrel: DesignCTPB_1.1.3.zip
macOS binaries: r-release (arm64): DesignCTPB_1.1.3.tgz, r-oldrel (arm64): DesignCTPB_1.1.3.tgz, r-release (x86_64): DesignCTPB_1.1.3.tgz, r-oldrel (x86_64): DesignCTPB_1.1.3.tgz
Old sources: DesignCTPB archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=DesignCTPB to link to this page.

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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