Adaptive Biomarker-Based Design for Early Phase Clinical Trials
Alessandra Serra1, Gaëlle Saint-Hilary2, Sandrine Guilleminot3
1University of Cambridge, MRC Biostatistics Unit, Cambridge, UK.
Statistics in Medicine
|October 9, 2025
Summary
This study introduces a biomarker-guided clinical trial design for early-phase oncology studies. The adaptive approach improves decision-making by refining patient populations based on predictive biomarkers, even with limited sample sizes.
Area of Science:
- Clinical trial design
- Biomarker discovery
- Oncology research
Background:
- Precision Medicine relies on identifying predictive biomarkers for patient stratification.
- Early phase adaptive trial designs enhance efficiency through in-trial modifications.
- Current designs may miss efficacy signals in biomarker-defined subgroups.
Purpose of the Study:
- To propose a novel one-arm, two-stage, early-phase biomarker-guided design.
- To enable adaptive decisions at interim analysis for population refinement.
- To improve efficacy signal detection in biomarker subgroups.
Main Methods:
- Development of a two-stage, one-arm adaptive design.
- Incorporation of interim analysis for population selection/enrichment.
- Simulation studies to evaluate design performance.
Main Results:
- The proposed biomarker-guided design enhances decision-making in early phase trials.
- It offers advantages over classical designs lacking biomarker enrichment.
- Effective even with limited sample sizes, it aids in identifying efficacy signals.
Conclusions:
- Biomarker-guided adaptive designs are valuable for early-phase oncology trials.
- This approach optimizes patient selection and improves the chances of detecting efficacy signals.
- It represents a significant advancement for patient-centric clinical development.
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