10 | THE ROLE OF ARTIFICIAL INTELLIGENCE IN CLINICAL TRIAL DESIGN AND ANALYSIS

Abstract

The focus of this talk is on how real-world data, trial infrastructure, and quantitative modeling techniques are being used to complement traditional randomized controlled trials (RCTs). For the integration of real-world data, the pros and cons of emulated trials and synthetic control arms will be presented, along with their specificities in statistical data analysis methods. I will provide an overview of some of the methodological developments in our team over the last decade, which use penalised Cox or machine learning methods on data from clinical trials to predict survival outcomes or the magnitude of treatment effects. Keywords: diagnostic and prognostic biomarkers; other; other therapeutics and clinical trials in lymphoma No potential sources of conflict of interest.

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