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: 0.4.0
Depends: R (≥ 2.10)
Imports: reticulate, mnormt, fields, magrittr
Suggests: knitr, rmarkdown, dplyr, plotly
Published: 2021-01-21
Author: Yitao Lu ORCID iD [aut, cre], Belaid [aut], Julie Zhou [aut], Li Xing ORCID iD [aut], Xuekui Zhang ORCID iD [aut]
Maintainer: Yitao Lu <yitaolu at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL:, Y Lu (2020) <doi:10.1002/sim.8868>
NeedsCompilation: no
SystemRequirements: 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


Reference manual: DesignCTPB.pdf
Vignettes: DesignCTPB
Package source: DesignCTPB_0.4.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: DesignCTPB_0.4.0.tgz, r-oldrel: DesignCTPB_0.4.0.tgz


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