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Machine Learning and Simulations to Facilitate Clinical Trials
Session Chair(s)
Raviv Pryluk, PhD
PhaseV, United States
The past decade has seen significant strides in machine learning and AI technologies. This session will provide an in depth investigate the various uses of machine learning and AI-based simulations within clinical development, ranging from data analysis, endpoint selection, the potential improvement of decision making within trial teams by clarifying tradeoffs to clinicians and statisticians, and more.
Learning Objective : Describe the potential benefits of simulations in clinical trial protocol development and trial analysis, and the benefits of employing machine learning tools throughout clinical development; Discuss the novel approaches to conducting studies with such tools incorporated and relate to the regulatory guidance for adaptive trial design where relevant.
Speaker(s)
Doing More with Less: Using ML to Drastically Improve Trial Simulation and Design
Raviv Pryluk, PhD
PhaseV, United States
Digital Twins for Clinical Trials
Andrew Stelzer
Unlearn.ai, United States
Head of Business Development
Clinical Trial Simulation: the Antidote to Wishful Thinking
Sam Miller, MSc
Exploristics, United Kingdom
Head of Strategic Consulting
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