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Bio
Raphaël Porcher is a Professor of Biostatistics with expertise in innovative statistical methods for causal inference and personalized medicine, and emulation of complex target trials with observational data, and a chair in the PR[AI]RIE-PSAI AI cluster.
As PI or Co-Investigator of several nationally-funded (e.g., French Agence Nationale de la Recherche) or European Union-funded (e.g., H2020 programs) projects, his research focuses on 1) causal inference methods to estimate the effect of interventions with real-world data, especially in the case of time-varying treatments; 2) statistical and AI methods for personalized medicine, including clinical trials designs and the analysis of observational studies; 3) methodological issues in target trial emulation; and 4) the use of observational data for drug assessment by regulators of heath technology assessment. He also has long-lasting experience in designing and analyzing studies aiming to emulate a target trial, including complex situations of treatment durations or with time-varying treatments.
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