Advancing Precision in Drug Development: Enrichment Strategies in Clinical Trials

Music City Center 

The promise of personalized medicine hinges on accurately identifying patient subgroups that will benefit most from specific therapies, particularly in the development of immunotherapies and targeted treatments. As drug development increasingly moves towards precision medicine, enrichment designs play a critical role in identifying and focusing on responder populations. This talk will explore cutting-edge adaptive enrichment designs in clinical trials that leverage advanced statistical models to dynamically target these subgroups, enhancing trial precision and efficacy. We will discuss recent advancements in enrichment strategies, including Bayesian group sequential enrichment designs based on adaptive regression of response and survival time on baseline biomarkers (Biometrics, 2022), personalized dose-finding algorithm based on adaptive Gaussian Process regression (Pharmaceutical statistics, 2024), and new enrichment basket trial designs currently in development. These methodologies enable real-time adjustments in patient inclusion criteria based on evolving biomarker data, dynamically refining trial populations to enhance both precision and efficacy. Each example highlights how adaptive enrichment strategies can streamline decision-making, reduce costs, and accelerate timelines, ultimately making clinical trials more responsive to patient heterogeneity and advancing the field of precision medicine.

decision-making, enrichment, personalized medicine