Bayesian Optimal Interval (BOIN) Design for Phase I Clinical Trials BOIN Suite: A Software Platform to Design and Implement Novel Early-Phase Clinical Trials JCO Clinical Cancer Informatics, 5, 91-101 Cite the software: Zhou, Y , Liu, Y , Yuan, Y , Lee, J J , Zhou, H , Chen, N , Kuo, Y (2026) Bayesian Optimal Interval (BOIN) Design for Phase I Clinical Trials (V3 0 17 0) [Computer software]
Trial Design Time-to-Event BOIN (TITE-BOIN) allows for real-time dose assignment for new patients while some enrolled patients’ toxicity data are still pending, thereby significantly shortening the trial duration It is as easy to implement as the rolling 6 design, but yields much better performance
Bayesian Optimal Interval (BOIN) - Clinical Biostats The Bayesian Optimal Interval (BOIN) design is a structured approach for dose-finding in phase I clinical trials It aims to balance effective dose escalation with patient safety by using observed dose-limiting toxicity (DLT) rates to guide dose adjustments
An overview of the BOIN design and its current . . . - ScienceDirect BOIN designs provide a complete suite for dose finding in early phase trials, and a consistent way to explore different scenarios in a unified manner with easy access to software [1] to implement most of these designs
A comparative study of Bayesian optimal interval (BOIN) design with . . . Bayesian optimal interval (BOIN) design is a model-assisted phase I dose-finding design to find the maximum tolerated dose (MTD) The hallmark of the BOIN design is its concise decision rule — making the decision of dose escalation and de-escalation
Approval [Rx ONLY] Goal and Intended Applications The BOIN design is a statistical methodology for phase I dose finding clinical trials where the goal is to find the maximum tolerated dose (MTD) of a new drug