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Invited Paper Session

Beyond the Black Box: Tools and Techniques for Explaining Causal ML Models in Different Phases of Dr

Mon, Aug 4, 10:30 AM - 12:20 PM Room CC-207A Music City Center

Margaret GamaloOrganizerTing WangChair

Biopharmaceutical Section co: Section on Medical Devices and Diagnosticsco: Section on Statistical Learning and Data Science Applied

5 Presentations

Connecting the Dots: Leveraging AI/ML Tools to Increase Interpretability of Genomic Signatures from Mouse to Human

10:35 AM - 10:55 AM

AI/ML, translation, mouse model

A graph neural network architecture in Biopharmaceutical Research: Enhancing Decision-Making

10:55 AM - 11:15 AM

Co-authors: Vachan Naik (Pfizer Inc), Yuxi Zhao (Pfizer), Margaret Gamalo (Pfizer)

Machine Learning graph neural network Clinical trials

Interpretability of individualized treatment regimens

11:15 AM - 11:35 AM

Yue Shentu (Merck & Co)

individualized medicine, subgroup identification, interpretable machine learning

Modern approaches for evaluating individual treatment effects from clinical and real-world data

11:35 AM - 11:55 AM

Co-authors: Ilya Lipkovich, David Svensson (AstraZeneca), Bohdana Ratitch (Bayer), Alex Dmitrienko

Personalized medicine Subgroup identification individualized treatment regimen

Transforming Heart Failure Treatment: Leveraging CausalML Powered Real-World Evidence for Personalized Guideline-Directed Medical Therapy

11:55 AM - 12:15 PM

Yunxun Wang (Bayer U.S. LLC)

Causal Machine Learning personalized medicine guideline-directed medical therapy Heart Failure real-world evidence real-world data

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