# crm12comb: Phase I/II adaptive design for drug combinations based on CRM design through R

## TL;DR

The paper introduces crm12Comb, an R package that helps design adaptive Phase I/II trials for drug combinations using a Bayesian approach to improve cancer therapy development.

## Contribution

The novelty lies in providing a flexible and user-friendly R package for adaptive drug combination trials using CRM methodology.

## Key findings

- crm12Comb supports patient assignment and simulation studies for evaluating trial parameters.
- The package handles toxicity and efficacy as binary outcomes with partial orderings for drug combinations.
- It offers flexibility through user-specified parameters and various link functions with prior distributions.

## Abstract

Adaptive designs for integrated phase I/II trials of drug combinations are increasingly utilized to speed up the drug development process and enhance drug efficacy, particularly in the realm of cancer therapy. The model-based Continual Reassessment Method (CRM) for dose-finding is widely used to leverage accumulated data in guiding patient allocation, drawing on principles from the Bayesian framework. In this paper, we present crm12Comb, an R package we developed to streamline the Phase I/II adaptive design process for drug combinations using the CRM approach. This package supports patients’ assignment guidance in a single trial based on existing data, as well as simulation studies for conducting extensive simulations with multiple trial parameters to evaluate operating characteristics and create visual representations. It accounts for toxicity and efficacy as binary outcomes, applying partial orderings to the dose-toxicity and dose-efficacy relationships for drug combinations. crm12Comb allows for a wide range of user-specified parameters, including maximum number of patients, cohort size, drug combinations, and a variety of link functions with prior distributions, offering flexibility to accommodate diverse clinical scenarios.