Facebook-f Twitter Youtube Linkedin-in

Conference starts in -1126 days

Main Menu

Educational sessions – Friday 30 October 2026

TRACK A: Designing Transparent and Reproducible Real-World Drug Studies
(More suitable for beginners/intermediate)

This track introduces core pharmacoepidemiologic study designs and the strengths and limitations of major real-world data sources. With a focus on transparency, reproducibility, and emerging AI-assisted approaches, participants will gain hands-on skills in prompt engineering for protocol development, statistical analysis in SAS and R, and effective data visualization for pharmacoepidemiologic research.

Krishna Undela

Krishna Undela

Krishna Undela, PhD, is an Assistant Professor in the Department of Pharmacy Practice at the National Institute of Pharmaceutical Education and Research (NIPER) Guwahati, with teaching and research expertise across pharmacoepidemiology, pharmacovigilance, pharmacoeconomics, clinical pharmacy, and evidence-based medicine. He has extensive experience conducting pharmacoepidemiological studies in hospital and community settings, with a strong focus on chronic disease medication management, evidence synthesis, pharmacovigilance data mining, and health economics. He has authored more than 140 scientific publications and delivered more than 220 invited lectures at national and international forums. He also serves in several international professional roles, including with the International Society for Pharmacoepidemiology and the International Society of Pharmacovigilance.

Read bio

Celine SL Chui

Celine SL Chui

Celine SL Chui, PhD, is an Assistant Professor at the University of Hong Kong, with international experience at the London School of Hygiene & Tropical Medicine and City St George’s, University of London. Her research uses real-world evidence, knowledge translation, and implementation science to improve population health, including major work in vaccine safety surveillance, neurological and mental health epidemiology, and AI-enabled cardiovascular risk prediction. She has published more than 150 peer-reviewed articles in leading journals including The Lancet Infectious Diseases, BMJ, JAMA Internal Medicine, npj Digital Medicine, and Neurology. She has received multiple awards and recognitions, including the International Society for Pharmacoepidemiology Emerging Leader Award.

Read bio
TRACK B: Emulating a Hypothetical Drug Trial Using Real-World Data
(More suitable for advanced)

This advanced track provides an in-depth introduction to advanced target trial emulation methods, covering database integration and optimization, clone–censor–weighting, and sequential trial-based designs. Through practical exercises and real-world examples, participants will engage in an interactive, hands-on learning experience to develop practical skills in applying these advanced methods to real-world research.

Joshua Lin

Joshua Lin

Joshua Lin, MD ScD, is a practicing internist, Associate Professor at Harvard Medical School, Executive Director of the Center for Integrated Healthcare Data Research, and Director of the Program of Optimal and Safe Prescribing in the Elderly (PROSPER) in Mass General Brigham Integrated Health Care System, Boston. As Principal Investigator, he has led multiple large U.S. national studies to optimize drug safety and effectiveness in vulnerable populations using target trial emulation when randomized trials are not feasible. His work extensively advances causal inference using AI combined with electronic health records and administrative claims data.

Read bio
TRACK C: Machine Learning in Real-World Drug Studies: Introduction to Prediction and Natural Language Processing (NLP) models

This track introduces machine learning-based prediction modelling and NLP applications in real-world drug studies. Participants will gain practical exposure to basic coding workflows, machine learning–driven disease phenotyping strategies, while learning to critically evaluate epidemiologic biases in NLP-enhanced analyses.

Yanmin Zhu

Yanmin Zhu

Yanmin Zhu, PhD, is an Assistant Professor in the Division of Pharmacoepidemiology and Pharmacoeconomics at Brigham and Women’s Hospital and Harvard Medical School. Her research focuses on using real-world data, including healthcare claims and electronic health records, to study the determinants of maternal and newborn health. She has led work on machine learning approaches for gestational age estimation and on large language model methods for outcome phenotyping. Her current research aims to develop practical and reproducible ML/LLM-guided frameworks to generate real-world evidence and strengthen clinical research using structured and unstructured data.

Read bio

Richeek Pradhan

Richeek Pradhan

Richeek Pradhan, MD PhD, is a Lecturer at the Centre for Medicine Use and Safety, Monash University, with training in clinical pharmacology, epidemiology, health informatics, and pharmacoepidemiology. His research uses real-world data and causal inference methods to study medication safety, effectiveness, and potential new uses of existing medicines. He has also worked on natural language processing approaches to identify social determinants of health, characterize medication discontinuation from electronic health records, and strengthen drug safety surveillance using structured and unstructured clinical data. His work spans antihyperglycemic agents, cancer, liver disease, chronic obstructive pulmonary disease, ageing, and medication safety, with publications in journals including BMJ, Diabetes Care, Gut, and JAMIA.

Read bio
TRACK D: Learning from Real-World Evidence to Inform Policy and Practice

This policy-focused track examines how real-world drug studies inform regulatory processes, reimbursement decisions in Australia and globally, and using real world data for health economic evaluations of drugs. Participants will understand how evidence is translated into policy and funding decisions.

Zanfina Ademi

Zanfina Ademi

Zanfina Ademi, PhD, is Professor of Health Economics at Monash University and founding head of the Health Economics and Policy Evaluation Research Group. Trained as a pharmacist, epidemiologist, and health economist, her work sits at the intersection of real-world evidence, health economics, reimbursement, and policy translation. She serves on the Economics Sub Committee of the Pharmaceutical Benefits Advisory Committee (PBAC), supporting the evaluation of medicines for Pharmaceutical Benefits Scheme listing in Australia. Her research has informed national and international policy decisions across medicines, vaccines, genomic testing, cardiovascular and kidney disease, and Alzheimer’s therapies, with publications in journals including NEJM, BMJ, The Lancet, JAMA, Diabetes Care, PharmacoEconomics, and Value in Health.

Read bio