Incertus.jl -- The Julia Lego Blocks for Randomized Clinical Trial Designs

TL;DR

Incertus.jl is a Julia package that facilitates the creation and evaluation of randomization sequences for multi-arm clinical trials, supporting flexible, efficient, and customizable designs through simulation and integration with R.

Contribution

The paper introduces Incertus.jl, a flexible, efficient Julia package for generating and assessing randomization procedures in clinical trials, with capabilities for customization and validation.

Findings

Supports multi-arm trial randomization with target ratios

Enables Monte Carlo simulation for operating characteristics

Integrates with R for broader usability

Abstract

In this paper, we present Insertus.jl, the Julia package that can help the user generate a randomization sequence of a given length for a multi-arm trial with a pre-specified target allocation ratio and assess the operating characteristics of the chosen randomization method through Monte Carlo simulations. The developed package is computationally efficient, and it can be invoked in R. Furthermore, the package is open-ended -- it can flexibly accommodate new randomization procedures and evaluate their statistical properties via simulation. It may be also helpful for validating other randomization methods for which software is not readily available. In summary, Insertus.jl can be used as ``Lego Blocks'' to construct a fit-for-purpose randomization procedure for a given clinical trial design.