Emaan Rashidi, MHS, moderator, is a PhD student in the Department of Epidemiology at the Johns Hopkins Bloomberg School of Public Health, where she also earned her MHS in Epidemiology in 2021. Before beginning her doctoral training, she worked as a Senior Consultant Epidemiologist at IQVIA, leading the design of pharmacoepidemiologic studies for regulatory use. She has applied rigorous epidemiologic methods across a range of therapeutic areas, including oncology, gastroenterology, and rheumatology. Her current research focuses on leveraging observational study designs and Artificial Intelligence/Machine Learning tools to enhance the validity and impact of real-world evidence.

John Diaz-Decaro, PhD, is a pharmacoepidemiologist and the Founder and Principal of Black Swan Causal Labs, where he builds applied tools at the intersection of AI, causal inference, and real-world evidence, including agentic AI systems for protocol fidelity evaluation, MCP-enabled research infrastructure, and causal graph validation. He chairs the Digital Technology and Artificial Intelligence Special Interest Group at ISPE and serves on the editorial board of Pharmacoepidemiology and Drug Safety, contributing to its AI/ML section. Before founding Black Swan, he led enterprise epidemiology and RWE strategy at Moderna as a Senior Director and Lead Epidemiologist, and held global epidemiology roles at GSK. His work focuses on bringing methodological rigor, transparency, and auditability to the use of generative and agentic AI in pharmacoepidemiology. He holds a PhD from UCLA with a specialization in epidemiology and biostatistics.

Duncan Mahood is an epidemiologist, data scientist, and Founder & CEO of EpiToolsAI, where he develops and deploys enterprise AI solutions that support pharmacoepidemiology and evidence synthesis workflows. His work focuses on designing agentic AI systems that assist scientific decision-making while maintaining transparency, reproducibility, and human oversight. In parallel, Duncan works on the Global Evidence & Outcomes team at Takeda Pharmaceuticals, supporting evidence generation and AI implementation initiatives within oncology R&D. Prior to joining Takeda, he was a consultant at Epidemiologic Research & Methods (ERM), where he led research and analytics projects for pharmaceutical and biotechnology clients across a wide range of therapeutic areas. Originally trained as an infectious disease epidemiologist, Duncan has experience spanning oncology, rare diseases, vaccines, environmental health, and real-world evidence generation. His interests center on applying AI to accelerate evidence synthesis and epidemiologic research while preserving scientific rigor and domain expertise.

Katie Mues, PhD, MPH is a pharmacoepidemiologist with over a decade of experience working within industry. Katie is currently leading the agentic AI strategy within Datavant Life Sciences, playing a connective role between the scientific and product leadership as Datavant transforms their RWE platform to be agentic in nature. Katie previously served as a Vice President of Science at Aetion, where she led a team of scientists and analysts in the design, execution, and dissemination of RWE studies for biopharma customers across medical devices and vaccines. Prior to Aetion, Katie spent 7 years at Amgen as an epidemiologist within the Center for Observational Research and as a Medical Affairs Director, supporting the design and execution of several cardiovascular registry studies. Katie currently serves as an Adjunct Assistant Professor at Emory's Rollins School of Public Health, where she previously completed her PhD and MPH in epidemiology.

Serena Guo, MD, PhD conducts research in pharmacoepidemiology and pharmacoinformatics, primarily focused on cardiometabolic diseases, neurodegenerative conditions (e.g., dementia) and cancer, with the goal of promoting precision therapeutics. Her research draws on large real-world data (e.g., electronic health records, insurance claims data) and advanced analytics (e.g., AI/machine learning, causal-principled modeling) to: 1) assess comparative effectiveness/safety and heterogeneous treatment effects (HTEs) of treatments and interventions, and 2) develop intelligent clinical decision support tools to be integrated into clinical care.

Dr. Guo has published over 150 peer-reviewed manuscripts. Several articles have been published in top-tier journals, including Annals of Internal Medicine, Nature Communications, and JAMA Neurology, and featured in media outlets, including the Washington Post, NPR, and CNN. Her research programs have been funded by the NIDDK, NIA, NIMHD, CDC, the PhRMA Foundation and pharmaceutical collaborators. She is currently an Associate Professor of Pharmacy Practice at Purdue University.

Luis Pinheiro MPH, PharmD, is a Signal Management Lead at the European Medicines Agency (EMA), where he is responsible for monitoring the safety of a portfolio of biopharmaceuticals and oncological products. He also provides pharmacoepidemiology and data science expertise in drug safety data analysis and coordinates the data analysis support to safety referrals within the Signal and Incident Management Service.

Prior to joining the EMA, he was the Head of the Signal Detection Unit (ad interim) at Infarmed, the Portuguese Regulatory Authority and Portuguese representative at the Pharmacovigilance Working Party at EMA. Before that, he worked in the Faculty of Pharmacy, University of Lisbon for eight years.

Luis received his Master’s in Epidemiology from the Faculty of Medicine, New University of Lisbon and is currently pursuing a doctorate with Dr Peter Rijnbeek’s group at Erasmus MC.