optimIA

optimIA implements Bayesian adaptive commensurate designs in R to integrate historical data, expert opinions, and real-world evidence for adaptive borrowing and optimized interim analysis timing in clinical trials, particularly for rare and pediatric genetic disease trials.

Key Features:

• Adaptive Borrowing from Historical Information: Incorporates external sources such as historical data, expert opinions, and real-world evidence to adaptively borrow information into the current trial analysis.
• Optimized Timing of Interim Analysis: Uses a payoff function to determine optimal timing for interim analyses, balancing potential sample size reduction from early stopping with the probability of correct futility or efficacy decisions.
• Calibration with Acceptable Frequentist Properties: Conducts simulation-based calibration at the design stage to maintain long-run frequentist properties, including control of Type I error rates and statistical power.
• Application in Rare Disease Trials: Applied in pediatric trials targeting rare genetic diseases to address limited patient availability and improve decision efficiency.

Scientific Applications:

• Rare disease clinical trials: Supports design and decision-making in clinical research for rare diseases by enabling adaptive borrowing and interim analysis optimization.
• Pediatric rare genetic disease trials: Illustrates the approach in pediatric settings testing new drug effects for rare genetic diseases where patient populations are limited.

Methodology:

Implemented as an R package using Bayesian adaptive commensurate design principles, a payoff function for interim analysis timing, and simulation-based calibration to control Type I error and statistical power.