Generate Synthetic SEND Data • SENDsanitizer

SENDsanitizer is an R package to generate synthetic data from real data.

Overview

The Standard for Exchange of Nonclinical Data (SEND), developed by the Clinical Data Interchange Standards Consortium (CDISC), offers a structured electronic format to organize and exchange nonclinical study data among sponsor companies, contract research organizations (CROs), and health authorities.

SENDsanitizer is an R package designed to generate synthetic SEND-formatted data by modifying real SEND-formatted datasets. It anonymizes the data by replacing sensitive information like dates and other specific details with predefined text, ensuring that identities cannot be traced. Additionally, potentially identifiable data elements are removed entirely to maintain privacy. For numerical values, SENDsanitizer generates synthetic data using Bayesian regression model.

Installation

Development version can be installed from GitHub.

# install devtools if already not installed
install.packages("devtools")

#install toxSummary package
devtools::install_github('phuse-org/SENDsanitizer')

To generate one synthetic study dataset from one real study

library(SENDsanitizer)
SENDsanitizer::sanitize(path='path/to/directory/of/xpt/files/of/study/',
where_to_save='path/to/directory/where/generated/files/should/be/saved/')

To generate one synthetic study dataset from multiple real study

library(SENDsanitizer)
study_01 <- 'path/to/directory/of/xpt/files/of/study_01/'
study_02 <- 'path/to/directory/of/xpt/files/of/study_02/'
multiple_studies <- c(study_01,study_02)
SENDsanitizer::sanitize(path= multiple_studies,
where_to_save='path/to/directory/where/generated/files/should/be/saved/')

Install from cloned repo

Clone the GitHub repo and set repo as working directory.

devtools::load_all(".")
SENDsanitizer::sanitize(path='path/to/directory/of/xpt/files/of/study/',
where_to_save='path/to/directory/where/generated/files/should/be/saved/')

Notes on Example SEND Studies:
It is recommended to use multiple example studies for better results. These SEND format example studies must have similar arms/dosing regimens (with the option to include or exclude recovery animals), SEND Version, and have the same SSTYP and species. The script checks for these values to be similar and will provide errors based on which of these conditions is not met.