Linda Nab

University Medical Center Utrecht (UMC Utrecht)  Assistant Professor

 Fellowship project title: Research software for efficient causal inference from large-scale electronic health records 

The goal: Randomised trials are the gold standard for studying causal effects across disciplines, but many research questions cannot feasibly be answered with this design: even sizeable clinical trials may fail to detect if a vaccine produces an increased risk of a relatively rare condition. Instead, researchers and regulators increasingly focus on analyzing real-world data, in the form of population-scale electronic health records, to study the safety and effectiveness of (health) interventions. To achieve this, researchers often rely on a complex and computationally expensive causal inference technique known as sequential target trial emulation. In this project, we aim to develop a flexible and computationally efficient software package that allows researchers to apply sequential trial emulation to large-scale databases.  

The why: This software package will be used directly in EU-wide regulatory studies, for example of vaccine safety. A further overarching aim of the project is to help build a knowledge base on effective scientific software development in real-world evidence settings. 

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