Clinical Trials in Precision Medicine

Abstract

Precision medicine clinical trials -- designed to evaluate therapies in molecularly or biologically defined patient subgroups rather than broad diagnostic categories -- have emerged as the dominant paradigm in oncology drug development and are expanding rapidly into rare disease, neurology, and inflammatory disease research. Their promise is better therapeutic signal detection in responsive subgroups and reduced exposure of unlikely-responders to ineffective or toxic therapies. Their complexity -- adaptive randomisation, master protocols, multiple biomarker-defined arms, Bayesian decision frameworks -- places substantial demands on trial design, statistical methods, and operational execution. We evaluated five clinical trial design frameworks across 428 precision medicine trials at 22 European academic trial centres in Paris, Barcelona, Amsterdam, Stockholm, and Vienna between 2014 and 2024, spanning oncology, rare disease, and immunological conditions. Frameworks ranged from conventional randomised controlled trial with biomarker stratification through fully adaptive master protocol platforms with Bayesian decision rules and real-time biomarker qualification. Performance was benchmarked using our Precision Medicine Trial Efficiency Score (PMTES), integrating time-to-signal-detection, sample size efficiency, biomarker qualification rigour, patient access equity, and regulatory acceptance. The adaptive master protocol platform framework achieved the highest PMTES (0.921), reducing time-to-signal-detection by 42.4% and total sample size by 38.2% while identifying 2.6 times more biomarker-defined responder subgroups than conventional designs. Basket trial designs in oncology and N-of-1 sequential trials in rare diseases were the design categories showing greatest efficiency advantages over traditional approaches.