Related Experiment Video
Updated: Apr 11, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
Published on: October 11, 2018
Biomarker informed add-arm design for unimodal response
Jing Wang1,2, Mark Chang1,3, Sandeep Menon1,4
1a Department of Biostatistics , Boston University , Boston , Massachusetts , USA.
Abstract:
In this article, we propose a biomarker informed add-arm design for unimodal response. The new design contributes to optimizing the procedure of dose-finding when a biomarker of the study primary endpoint exists and prior evidence indicates a unimodal dose-response relationship. Designs with up to seven active treatment arms were considered. We propose the statistical approach for the Type I error control and carry out extensive simulation studies for the power performance of the design. The proposed design is shown to outperform the corresponding biomarker informed two-stage winner design in power on an average.
More Related Videos
04:09Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
Published on: October 10, 2018
08:58Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
Published on: October 17, 2025
Related Concept Videos
Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs
Methods of Medium Optimization
Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs
Dose-Response Relationship: Selectivity and Specificity
Dose Response Curve: Conventional Versus Nonmonotonic