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crm12Comb (version 0.1.12)

Phase I/II CRM Based Drug Combination Design

Description

Implements the adaptive designs for integrated phase I/II trials of drug combinations via continual reassessment method (CRM) to evaluate toxicity and efficacy simultaneously for each enrolled patient cohort based on Bayesian inference. It supports patients assignment guidance in a single trial using current enrolled data, as well as conducting extensive simulation studies to evaluate operating characteristics before the trial starts. It includes various link functions such as empiric, one-parameter logistic, two-parameter logistic, and hyperbolic tangent, as well as considering multiple prior distributions of the parameters like normal distribution, gamma distribution and exponential distribution to accommodate diverse clinical scenarios. Method using Bayesian framework with empiric link function is described in: Wages and Conaway (2014) .

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Install

install.packages('crm12Comb')

Monthly Downloads

173

Version

0.1.12

License

GPL (>= 3)

Maintainer

Junying Wang

Last Published

February 3rd, 2026

Functions in crm12Comb (0.1.12)

empiric_GammaPriorLikelihood

empiric model with gamma prior
enroll_patient_plot

Plot patient enrollment for single trial
efficacy_est

Efficacy estimation
doseComb_to_mat

Title: Get 6 complete orderings for toxicity and efficacy for drug combinations
examples_results

Output dataset for examples given list of inputs
logisticOnePara_GammaPriorLikelihood

one-parameter logistic model with gamma prior
get_ordering

Complete orderings for combinations of two drugs
ODC_plot

Plot optimal combination dose selections
SIM_phase_I_II

Single simulation of phase I/II adaptive design for drug combinations based on CRM design
empiric_NormalPriorLikelihood

empiric model with normal prior
priorSkeletons

Generate the skeletons of toxicity and efficacy
patient_allocation_plot

Plot patient allocation for a single trial
rBin2Corr

Generate correlated binary variables
randomization_phase

Adaptive randomization
logisticTwoPara_NormalPriorLikelihood

two-parameter logistic model with normal prior
maximization_phase

Maximization phase
sample_plot

Sample plot for a given output results
tanh_ExpPriorLikelihood

Title: Bayesian likelihood inference
toxicity_est

Toxicity estimation
logisticOnePara_NormalPriorLikelihood

one-parameter logistic model with normal prior
logisticTwoPara_GammaPriorLikelihood

two-parameter logistic model with gamma prior