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Predictive Subgroup Methodologies and Molecular Basket Designs
Session Chair(s)
Robert A. Beckman, MD
Professor of Oncology and of Biostatistics, Bioinformatics, and Biomathematics
Georgetown University Medical Center, United States
Optimal designs for predictive biomarkers and their associated subgroups are presented from both the public health and drug developers' perspectives. Novel basket designs grouping tumors based on molecular characteristics will be discussed.
This session has been developed by the DIA Adaptive Design Scientific Working Group.
Learning Objective : Describe risks of subgroup identification and optimal nonadaptive and adaptive designs; Explain possibilities of basket or bucket trials which group tumors based on similar molecular characteristics including new methodologies in this area.
Speaker(s)
Optimizing the Biomarker Subpopulation Strategy in Late Stage Clinical Development
Carl-Fredrik Burman, PhD
AstraZeneca R&D, Sweden
Assoc. Prof. in Biostatistics, Chalmers Univ of Tech; Senior Principal Scientist
Design for a Confirmatory Histology Agnostic Molecular Basket Study
Robert A. Beckman, MD
Georgetown University Medical Center, United States
Professor of Oncology and of Biostatistics, Bioinformatics, and Biomathematics
Predictive Biomarker Classifiers and Molecular Classifiers: A Perspective
Rajeshwari Sridhara, PhD
FDA, United States
Senior Biostatistician Consultant, Oncology Center of Excellence, FDA
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