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  • Dec
    10

    IEMS Seminar: Statistical Modeling and Optimization for Optimal Adaptive Trial Design in Personalized Medicine

    Department of Industrial Engineering and Management Sciences

    11:00 AM M228, Technological Institute

    EVENT DETAILS

    Xingyuan Ethan Fang

    Penn State University

    Title: Statistical Modeling and Optimization for Optimal Adaptive Trial Design in Personalized Medicine

    Abstract: We provide a new modeling framework and adopt modern optimization tools to attack an important open problem in statistics. In particular, we consider the optimal adaptive trial design problem in personalized medicine. Adaptive enrichment designs involve preplanned rules for modifying enrollment criteria based on accruing data in a randomized trial. We focus on designs where the overall population is partitioned into two predefined subpopulations, e.g., based on a biomarker or risk score measured at baseline for personalized medicine. The goal is to learn which populations benefit from an experimental treatment. Two critical components of adaptive enrichment designs are the decision rule for modifying enrollment, and the multiple testing procedure. We provide a general framework for simultaneously optimizing these components for two-stage, adaptive enrichment designs through Bayesian optimization. We minimize the expected sample size under constraints on power and the familywise Type I error rate. It is computationally infeasible to directly solve this optimization problem due to its nonconvexity and infinite dimensionality. The key to our approach is a novel, discrete representation of this optimization problem as a sparse linear program, which is large-scale but computationally feasible to solve using modern optimization techniques. Applications of our approach produce new, approximately optimal designs. We shall further discuss several extensions to solve other related statistical problems.

    Biography: Ethan is an assistant professor at Penn State University. Before joining Penn State, he got his PhD from Princeton University in 2016 and his bachelor's degree from the National University of Singapore in 2010. He works on different problems such as statistical learning, high-dimensional inference and adaptive trial design from both statistical and computational perspectives. He won numerous awards in statistics and optimization such as Best Paper Prize for Young Researchers in Continuous Optimization (jointly with Mengdi Wang and Han Liu). the environment and is a Fellow of the American Statistical Association.

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    TIME Tuesday, December 10, 2019 at 11:00 AM - 12:00 PM

    LOCATION M228, Technological Institute    map it

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    CONTACT Agnes Kaminski    a-kaminski@northwestern.edu EMAIL

    CALENDAR Department of Industrial Engineering and Management Sciences

  • May
    8

    Extending Care: A Conversation about Conservation and Futurity

    Block Museum of Art

    6:00 PM Block Museum of Art, Mary and Leigh

    EVENT DETAILSmore info

    TIME Wednesday, May 8, 2024 at 6:00 PM - 7:30 PM

    LOCATION Block Museum of Art, Mary and Leigh    map it

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    CONTACT Block Museum of Art    block-museum@northwestern.edu EMAIL

    CALENDAR Block Museum of Art

  • Jun
    10

    Northwestern Engineering PhD Hooding and Master's Degree Recognition Ceremony

    McCormick School of Engineering and Applied Science

    9:00 AM Welsh-Ryan Arena

    EVENT DETAILSmore info

    TIME Monday, June 10, 2024 at 9:00 AM - 11:00 AM

    LOCATION Welsh-Ryan Arena   

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    CONTACT Amy Pokrass    amy.pokrass@northwestern.edu EMAIL

    CALENDAR McCormick School of Engineering and Applied Science

  • Jun
    10

    Northwestern Engineering Undergraduate Convocation

    McCormick School of Engineering and Applied Science

    2:00 PM Welsh-Ryan Arena

    EVENT DETAILSmore info

    TIME Monday, June 10, 2024 at 2:00 PM - 4:00 PM

    LOCATION Welsh-Ryan Arena   

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    CONTACT Amy Pokrass    amy.pokrass@northwestern.edu EMAIL

    CALENDAR McCormick School of Engineering and Applied Science