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Updated: Apr 3, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
Published on: October 11, 2018
The FOCUS4 design for biomarker stratified trials
1Medical Research Council Clinical Trials Unit, University College London, 125 Kingsway, London WC2B 6NH, UK. r.kaplan@ucl.ac.uk.
New clinical trial designs are essential for efficient oncology drug development. The multi-arm multi-stage (MAMS) and FOCUS4 designs improve screening of new therapeutics and biomarker-stratified trials.
Area of Science:
- Oncology
- Clinical Trial Design
- Biomarker Development
Background:
- Randomised clinical trials (RCTs) are the gold standard but standard designs are inefficient for modern drug development.
- The increasing number of targeted oncology agents necessitates more efficient trial designs.
- Biomarker-stratified trials, when conducted individually, are highly inefficient.
Purpose of the Study:
- To introduce and discuss advanced clinical trial designs tailored for oncology.
- To address the inefficiencies in screening new therapeutic agents and biomarker-stratified trials.
- To present the Multi-Arm Multi-Stage (MAMS) and FOCUS4 trial designs as solutions.
Main Methods:
- The Multi-Arm Multi-Stage (MAMS) design allows for early stopping of unpromising agents.
- The FOCUS4 trial design employs a platform for multiple parallel biomarker-stratified RCTs.
- Adaptive design capabilities allow for modifications based on accumulating evidence.
Main Results:
- MAMS designs efficiently screen multiple agents, concentrating resources on promising candidates.
- The FOCUS4 platform enhances efficiency by integrating multiple biomarker-drug pairings.
- Adaptive designs improve the responsiveness of trials to emerging data.
Conclusions:
- Advanced trial designs like MAMS and FOCUS4 are crucial for efficient oncology drug development.
- These designs optimize resource allocation by focusing on agents with higher likelihoods of benefit.
- Implementing adaptive strategies in biomarker-stratified trials leads to more effective drug development pipelines.
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