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admiralonco

Oncology extension package for ADaM in R Asset Library {admiral}

Explore all the other packages in the {admiral} ecosystem to learn more about ADaM programming in R.

Purpose

To provide a complementary (to {admiral}) toolbox that enables users to develop oncology disease area specifics.

Installation

The package is available from CRAN and can be installed with:

install.packages("admiralonco")

To install the latest development version of the package directly from GitHub use the following code:

if (!requireNamespace("pak", quietly = TRUE)) {
  install.packages("pak")
}

pak::pkg_install("pharmaverse/admiralonco", dependencies = TRUE)

Dependencies

The latest version of the package works with the latest versions of the packages stated in DESCRIPTION.

If a previous version of the package should be used, it is recommended to use latest version of the dependencies at the point of time when the previous version of {admiralonco} was released. For example, admiralonco 0.3.0 was released on 2023-03-14. I.e., it will work with the latest version of packages available at that date, e.g., admiral 0.10.

Scope

  • Build a toolbox of re-usable functions and utilities to create oncology-specific ADaM datasets in R in a modular manner.
  • All functions are created based upon the ADaM Implementation Guide and aim to facilitate the programming of ADaM dataset standards.
  • Initially the package will focus on the most common efficacy endpoint needs for solid tumor (using RECIST v1.1 response criteria), but over time we will look to add extra areas such as: endpoints for targeted indications, baseline disease characteristics, common sensitivity analyses and questionnaires.

Expectations

{admiralonco} is expected to complement {admiral} and provide functions to help with the creation of the efficacy endpoints required for oncology ADaMs.

References and Documentation

R Versions

Here's a summary of our strategy for this package related to R versions:

  • R versions for developers and users will follow the same as {admiral} core package.
  • For development the main branch of {admiral} core is used as a dependency. For releasing a new {admiralonco} version it must run using the latest released {admiral} core version.

Contact

We use the following for support and communications between user and developer community:

  • Slack - for informal discussions, Q&A and building our user community. If you don't have access, use this link to join the pharmaverse Slack workspace
  • GitHub Issues - for direct feedback, enhancement requests or raising bugs

Acknowledgments

Along with the authors and contributors, thanks to the following people for their work on the package:

Teckla Akinyi, Uwe Bader, Stephen Gormley, Liming Jin, Samia Kabi, Zhang Kangjie, Karl Kennedy, Konstantina Koukourikou, Pavan Kumar, Edoardo Mancini, Matt Marino, Thomas Neitmann, Hinal Patel, Andrew Smith, Gopi Vegesna, Annie Yang

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Version

Install

install.packages('admiralonco')

Monthly Downloads

637

Version

1.4.0

License

Apache License (>= 2)

Issues

Pull Requests

Stars

Forks

Maintainer

Stefan Bundfuss

Last Published

January 29th, 2026

Functions in admiralonco (1.4.0)

admiralonco-package

admiralonco: Oncology Extension Package for ADaM in 'R' Asset Library
signal_crpr

Signal CR Records Followed by PR
death_event

Pre-Defined Time-to-Event Source Objects
filter_pd

Filter up to First PD (Progressive Disease) Date
get_crpr_dataset

Get CR Records Followed by PR That Lead to a Prior Error
aval_resp

Map Character Response Values to Numeric Values
derive_param_bor

Adds a Parameter for Best Overall Response (without confirmation)
derive_param_confirmed_bor

Adds a Parameter for Confirmed Best Overall Response
derive_param_response

Adds a Parameter Indicating If a Subject Had a Response before Progressive Disease
derive_param_confirmed_resp

Adds a Parameter for Confirmed Response
rsp_y

Pre-Defined Response Event Objects
derive_param_clinbenefit

Adds a Parameter for Clinical Benefit
date_source

Create a date_source object
admiral_adrs

Response Analysis Dataset