Package: OncoBayes2 0.9-4

Sebastian Weber

OncoBayes2: Bayesian Logistic Regression for Oncology Dose-Escalation Trials

Bayesian logistic regression model with optional EXchangeability-NonEXchangeability parameter modelling for flexible borrowing from historical or concurrent data-sources. The safety model can guide dose-escalation decisions for adaptive oncology Phase I dose-escalation trials which involve an arbitrary number of drugs. Please refer to Neuenschwander et al. (2008) <doi:10.1002/sim.3230> and Neuenschwander et al. (2016) <doi:10.1080/19466315.2016.1174149> for details on the methodology.

Authors:Novartis Pharma AG [cph], Sebastian Weber [aut, cre], Lukas A. Widmer [aut], Andrew Bean [aut], Trustees of Columbia University [cph]

OncoBayes2_0.9-4.tar.gz
OncoBayes2_0.9-4.zip(r-4.7)OncoBayes2_0.9-4.zip(r-4.6)OncoBayes2_0.9-4.zip(r-4.5)
OncoBayes2_0.9-4.tgz(r-4.6-x86_64)OncoBayes2_0.9-4.tgz(r-4.6-arm64)OncoBayes2_0.9-4.tgz(r-4.5-x86_64)OncoBayes2_0.9-4.tgz(r-4.5-arm64)
OncoBayes2_0.9-4.tar.gz(r-4.7-arm64)OncoBayes2_0.9-4.tar.gz(r-4.7-x86_64)OncoBayes2_0.9-4.tar.gz(r-4.6-arm64)OncoBayes2_0.9-4.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html
card.svg |card.png
OncoBayes2/json (API)
NEWS

# Install 'OncoBayes2' in R:
install.packages('OncoBayes2', repos = c('https://novartis.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/novartis/oncobayes2/issues

Pkgdown/docs site:https://opensource.nibr.com

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • codata_combo2 - Dataset: historical and concurrent data on a two-way combination
  • dose_info_combo2 - Dataset: trial dose information for a dual-agent combination study
  • drug_info_combo2 - Dataset: drug information for a dual-agent combination study
  • hist_combo2 - Dataset: historical data on two single-agents to inform a combination study
  • hist_combo3 - Dataset: historical and concurrent data on a three-way combination
  • hist_SA - Single-agent example

On CRAN:

Conda:

cpp

5.28 score 4 stars 24 scripts 320 downloads 28 exports 78 dependencies

Last updated from:0b8809c6aa. Checks:12 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK435
linux-devel-x86_64OK403
source / vignettesOK516
linux-release-arm64OK427
linux-release-x86_64OK456
macos-release-arm64OK292
macos-release-x86_64OK438
macos-oldrel-arm64OK311
macos-oldrel-x86_64OK590
windows-develOK352
windows-releaseOK385
windows-oldrelOK376
wasm-releaseFAIL309

Exports:as_drawsas_draws_arrayas_draws_dfas_draws_listas_draws_matrixas_draws_rvarsbind_rows_0blrm_exnexblrm_formula_linearblrm_formula_saturatingblrm_trialcritical_quantileexample_modelinv_logitlog_posteriorlogitneff_rationsamplesnuts_paramsplot_toxicity_curveplot_toxicity_intervalsplot_toxicity_intervals_stackedposterior_intervalposterior_linpredposterior_predictpredictive_intervalprior_summaryrhat

Dependencies:abindassertthatbackportsbayesplotBHbridgesamplingbrmsBrobdingnagcallrcheckmateclicodacodetoolscpp11descdigestdistributionaldplyrfarverFormulafuturefuture.applygenericsggplot2ggridgesglobalsgluegridExtragtableinlineisobandjsonlitelabelinglatticelifecyclelistenvloomagrittrMatrixmatrixStatsmgcvmvtnormnleqslvnlmenumDerivparallellypillarpkgbuildpkgconfigplyrposteriorprocessxpspurrrQuickJSRR6RBesTRColorBrewerRcppRcppEigenRcppParallelreshape2rlangrstanrstantoolsS7scalesStanHeadersstringistringrtensorAtibbletidyrtidyselectutf8vctrsviridisLitewithr

Guiding Oncology Dose-Escalation Trials

Rendered fromintroduction.Rmdusingknitr::rmarkdownon May 28 2026.

Last update: 2025-12-17
Started: 2025-10-17

Meta-Analytic-Predictive (MAP) approach for dose-toxicity modelling

Rendered frommap_approach.Rmdusingknitr::rmarkdownon May 28 2026.

Last update: 2025-10-17
Started: 2025-10-17

Readme and manuals

Help Manual

Help pageTopics
Bind rows of multiple data frames with zero fillbind_rows_0
Bayesian Logistic Regression Model for N-compounds with EXNEXblrm_exnex print.blrmfit
Build a BLRM formula with linear interaction term in logit-spaceblrm_formula_linear
Build a BLRM formula with saturating interaction term in logit-spaceblrm_formula_saturating
Dose-Escalation Trials guided by Bayesian Logistic Regression Modelblrm_trial print.blrm_trial
Dataset: historical and concurrent data on a two-way combinationcodata_combo2
Critical quantilecritical_quantile critical_quantile.blrmfit critical_quantile.blrm_trial
Extract Diagnostic Quantities of 'OncoBayes2' Modelsdiagnostic-quantities log_posterior log_posterior.blrmfit neff_ratio neff_ratio.blrmfit nuts_params nuts_params.blrmfit rhat rhat.blrmfit
Dataset: trial dose information for a dual-agent combination studydose_info_combo2
Transform 'blrmfit' or 'blrm_trial' to 'draws' objectsas_draws as_draws.blrmfit as_draws.blrm_trial as_draws_array as_draws_array.blrmfit as_draws_array.blrm_trial as_draws_df as_draws_df.blrmfit as_draws_df.blrm_trial as_draws_list as_draws_list.blrmfit as_draws_list.blrm_trial as_draws_matrix as_draws_matrix.blrmfit as_draws_matrix.blrm_trial as_draws_rvars as_draws_rvars.blrmfit as_draws_rvars.blrm_trial draws-OncoBayes2
Dataset: drug information for a dual-agent combination studydrug_info_combo2
Runs example modelsexample_model
Two-drug combination exampleexample-combo2
Two-drug combination example using BLRM Trialexample-combo2_trial
Three-drug combination exampleexample-combo3
Single Agent Exampleexample-single-agent
Dataset: historical data on two single-agents to inform a combination studyhist_combo2
Dataset: historical and concurrent data on a three-way combinationhist_combo3
Single-agent examplehist_SA
Logit (log-odds) and inverse-logit function.inv_logit lodds logit
Return the number of posterior samplesnsamples nsamples.blrmfit
OncoBayes2OncoBayes2-package OncoBayes2
Plot a fitted modelplot_blrm plot_toxicity_curve plot_toxicity_curve.blrmfit plot_toxicity_curve.blrm_trial plot_toxicity_intervals plot_toxicity_intervals.blrmfit plot_toxicity_intervals.blrm_trial plot_toxicity_intervals_stacked plot_toxicity_intervals_stacked.blrmfit plot_toxicity_intervals_stacked.blrm_trial
Posterior intervalsposterior_interval posterior_interval.blrmfit
Posterior of linear predictorposterior_linpred posterior_linpred.blrmfit
Posterior of predictiveposterior_predict posterior_predict.blrmfit
Posterior predictive intervalspredictive_interval predictive_interval.blrmfit
Summarise model priorprior_summary prior_summary.blrmfit
Summarise trialsummary.blrm_trial
Summarise model resultssummary.blrmfit
Update data and/or prior of a BLRM trialupdate.blrm_trial
Update data of a BLRM analysisupdate.blrmfit