metalite

Unified representation of metadata structure for clinical analysis & reporting (A&R) by leveraging the Analysis Data Model (ADaM) datasets.

Installation

The easiest way to get metalite is to install from CRAN:

install.packages("metalite")

Alternatively, to use a new feature or get a bug fix, you can install the development version of metalite from GitHub:

# install.packages("remotes")
# remotes::install_github("Merck/metalite")
install.packages("metalite", repos = c('https://merck.r-universe.dev', 'https://cloud.r-project.org'))

Overview

The metalite framework is designed to:

• Standardize function input for analysis and reporting.
• Separate analysis logic from data source.
• Enable the use of pipes (|>).
• Reduce manual steps to develop and maintain documentation in clinical trial development.
• Ensure consistency between analysis specification, mock, and results.

Use cases

The metalite package offers a foundation to simplify tool development and create standard engineering workflows. For example, metalite can be used to:

• Standardize input and output for A&R functions.
• Create analysis and reporting planning grid.
• Create mock table.
• Create and validate A&R results.
• Trace analysis records.

Note: metalite is a low-level R package that needs to work with other R packages to complete the work. The idea is illustrated in the diagram above.

Design principles

We built metalite with the following principles:

• Automation: prefer a function call more than a checklist.
• Single-entry: enter in one place, sync to all deliveries.
  • For example, enter data source one time for all AE analysis.
• End-to-end: cover all steps in software development lifecycle (SDLC) from define to delivery.