Large amounts of observational medical data in the Finnish registries provide unique opportunities for studying the effects of common prescription drugs on diseases. The purpose of this project is to combine novel methods from the field of causal machine learning with classic causal inference methods from epidemiology in order to develop a framework for causal discovery using nationwide Finnish data on prescription drug use and diseases. The project aims to increase our understanding of how drugs work by discovering new unknown side-effects and beneficial effects. Discovery of new beneficial effects might lead to the repurposing of existing drugs for new indications. The project will also evaluate key existing unresolved questions around the effects of drugs.

2021

2024