Phase I Clinical Trial Designs: Bayesian Logistic Regression Model (BLRM)

By Kurt Preugschat

The Bayesian Logistic Regression Model (BLRM) is redefining Phase I clinical trial design by bringing flexibility, precision, and patient-centered safety into early drug development. Unlike traditional rule-based approaches, BLRM integrates prior knowledge with real-time patient data to guide dose selection, creating an adaptive feedback loop that evolves with every participant’s experience. BLRM is especially powerful in complex settings, such as combination therapies and non-linear dose-response relationships, where traditional methods often fall short. While implementation requires statistical expertise, extensive simulation, and regulatory transparency, the payoff is significant: safer trials, faster identification of optimal biologic doses, and improved confidence in early decision-making. As computing capabilities expand and regulatory acceptance grows, BLRM is poised to become a cornerstone of modern Phase I trial design—accelerating development while protecting patients.