Presented By  

• Mollie Wood, PhD, MPH is an assistant professor in Epidemiology at UNC Gillings School of Global Public Health. Her research focuses on the safety of medication use during pregnancy, specifically for chronic conditions like depression, migraine, and diabetes, combining expertise in reproductive epidemiology, pharmacoepidemiology, and methods. 

• Sonia Grandi, PhD is a Scientist and Assistant Professor at the Research Institute of the Hospital for Sick Children and University of Toronto. As a perinatal pharmacoepidemiologist, her research focuses on the safety of treatments for chronic cardiometabolic and immune-mediated conditions in pregnancy. She also specializes in causal inference methods using administrative health data. 

• Stephan Lanes, PhD, MPH is a Principal Scientist at Carelon Research, part of Elevance Health. He focuses on drug safety and the application of epidemiologic methods to health data in collaboration with industry, academic, and government partners

Learning Objectives  

• Identify subtle immortal time biases in administrative perinatal data. 
• Evaluate and apply robust study designs to eliminate time-related bias. 
• Implement analytical strategies (e.g., time-varying exposure) to align treatment with eligibility.