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sendigR: an R package to leverage the value of CDISC SEND datasets for cross-study analysis.

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Summary
This summary is machine-generated.

The new sendigR R package facilitates cross-study toxicology analyses using Standard for Exchange of Nonclinical Data (SEND) datasets. It enables database construction and terminology harmonization for open-source toxicology data exploration.

Keywords:
BioCelerateCDISC Standard for Exchange of Nonclinical DataUnited States FDAcross-study analysissendigRtoxicology data

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Area of Science:

  • * Pharmacology and Toxicology
  • * Data Science and Bioinformatics

Background:

  • * The CDISC Standard for Exchange of Nonclinical Data (SEND) enables data standardization in toxicology.
  • * Facilitating cross-study analyses of SEND datasets is crucial for drug development.
  • * Open-source software solutions are needed to leverage SEND data effectively.

Purpose of the Study:

  • * To develop and publicize novel methods for cross-study analysis of SEND datasets.
  • * To create an open-source R package, sendigR, for constructing relational databases from SEND datasets.
  • * To enable harmonization of terminology within SEND datasets using controlled terminologies.

Main Methods:

  • * Development of the R package `sendigR` in collaboration with the Pharmaceutical Users Software Exchange (PHUSE).
  • * Integration of the Python package `xptcleaner` for terminology harmonization.
  • * Inclusion of an R Shiny web application for historical control analyses without coding experience.

Main Results:

  • * The `sendigR` R package allows users to build a relational database from SEND datasets.
  • * Users can query the database to perform cross-study analyses.
  • * Terminology harmonization is achieved by mapping to CDISC controlled terminologies via `xptcleaner`.
  • * An R Shiny application is available for non-programmers to conduct historical control analyses.

Conclusions:

  • * `sendigR` provides a valuable open-source tool for researchers analyzing toxicology data.
  • * The package democratizes cross-study analysis of SEND data for both experienced programmers and toxicologists.
  • * `sendigR` is freely available on CRAN and GitHub, promoting collaborative development and accessibility.