Drug repurposing using real-world data: a pharmacoepidemiologic approach

My thesis explores how real-world data, collected from routine healthcare delivery, can be utilised to find new uses for existing drugs, a.k.a. drug repurposing. I reviewed previous studies and found that while many focused on testing specific drug repurposing ideas, newer methods like machine learning are utilised to generate new ideas. I conducted studies confirming that beta-blockers might help breast cancer patients and that cyclooxygenase-2 inhibitors could improve diabetes outcomes. I also demonstrated using innovative data mining techniques to identify potential new uses for glucose-lowering drugs. Overall, my research shows how we can leverage real-world data to advance drug repurposing efforts.