Rima Lebcir - HP2 & TIMC

Thesis: EMULATE – Exploring the impact of data sources and methodological choices on drug effectiveness estimation through target trial emulation

Abstract: Investigating how real-world data can reliably complement randomized trials for drug evaluation using advanced statistical emulation methods.

"I am Rima Lebcir, a data scientist holding a Master's in Statistics, Modelling, and Data Science. My academic background and professional experience in data transformation and predictive modeling have fueled my passion for tackling complex, data-driven research questions.

My motivation for this PhD is to address a critical challenge in healthcare: reliably estimating drug effects using real-world data. The EMULATE project allows me to apply advanced causal inference methods to explore how different data sources and analytical choices influence results, aiming to enhance the trustworthiness of real-world evidence for regulatory decisions.

I chose the CBS for its interdisciplinary environment and strong focus at the intersection of data science, clinical research, and public health, which perfectly aligns with my career aspirations.

Following my PhD, I aim to pursue a career in academic or industrial research, developing robust methodological frameworks to support evidence-based medicine and health policy."