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This webinar will explore the pivotal role of estimands in real-world evidence (RWE) studies, bridging the gap between regulatory guidance and practical implementation. The session will address challenges unique to RWE settings, such as heterogeneous patient populations, complex treatment regimens, and the impact of intercurrent events on study outcomes with a focus on generating RWE that can inform regulatory decision-making. Through practical examples, case studies, and an engaging panel discussion featuring domain experts, this session will highlight best practices for defining estimands that enhance the interpretability and reliability of RWE findings. Participants will leave with a systematic approach to estimand definition, empowered to conduct RWE studies that are robust, actionable, and aligned with evolving regulatory standards.

This webinar will held virtually on June 5 2025 at 11:00 (EDT)/ 16:00 (BST) / 17:00 (CEST)

Speakers

Bios

Ibrahim Turkoz, Johnson & Johnson (Moderator)

Ibrahim Turkoz, PhD, is a Scientific Director at Johnson & Johnson Innovative Medicine R&D. With over 25 years of clinical research experience in the pharmaceutical industry, he has worked across all phases of clinical drug development. Prior to joining J&J, Dr Turkoz held positions at several leading pharmaceutical consulting firms.

His current research interests encompass causal inference and comparative effectiveness, and he employs innovative methodologies for the design and execution of pragmatic trials and prospective observational studies. Dr Turkoz is a founding member of The International Society for CNS Clinical Trials and Methodology. He has authored and co-authored over 80 articles in peer-reviewed journals.

Hongwei Wang, AbbVie

Dr Hongwei Wang is a Sr. Research Fellow and Immunology TA Head, Medical Affairs & Health Technology Assessment Statistics at AbbVie. Prior to that, he worked at Sanofi and Merck. Hongwei received his PhD in Statistics from Rutgers University and his research interests include real-world studies, network meta-analysis, advanced analytics and their application to different stages of drug development.

Hana Lee, FDA

Hana Lee, PhD, is a Senior Statistical Reviewer in the Office of Biostatistics (OB) at the Center for Drug Evaluation and Research (CDER), FDA. She leads and oversees FDA-funded projects that support the development of the agency’s real-world evidence (RWE) programme.

She also serves as a co-lead of the RWE Scientific Working Group of the American Statistical Association (ASA) Biopharmaceutical Section, an FDA public–private partnership involving scientists from the FDA, academia and industry to advance the understanding of real-world data (RWD) and RWE to support regulatory decision-making. In 2024, Hana received the FDA’s most prestigious award for excellence in advancing and promoting statistical innovation in the use of RWD/RWE for regulatory decision-making.

Birol Emir, Pfizer

Birol Emir, PhD, is Executive Director and Head of Real-World Evidence (RWE) Statistics at Pfizer. He is a Fellow of the American Statistical Association and has served as Adjunct Professor of Statistics and as a lecturer at Columbia University in New York. His primary focuses have been on real-world evidence generation, predictive modelling, and data analysis.

Birol has numerous publications in refereed journals and co-authored Interface between Regulation and Statistics in Drug Development (Alemayehu, Emir and Gaffney 2021, CRC Press). He has also co-edited a book to fill the gap in health economics and outcomes research. Birol has given many invited talks and short courses at statistical and clinical conferences.

Ben Ackerman, Johnson & Johnson

Ben Ackerman is a Principal Biostatistician at Johnson & Johnson Innovative Medicine, where he provides support across therapeutic areas to design and analyse randomised trials, namely those that combine trial data with real-world data. He has expertise in causal inference methods to address biases in both randomised trials and non-experimental studies. Previously, he worked as a Quantitative Scientist at Flatiron Health – an oncology real-world data vendor – where he oversaw the design of studies leveraging EHR data to improve cancer care in the United States. Ben holds a PhD in Biostatistics from the Johns Hopkins Bloomberg School of Public Health. 

This introductory webinar aims to orient attendees on the intersection of the estimands and target trial emulation (TTE) frameworks, along with a suggested causal roadmap overview. After two presentations from publication authors, there will be a panel discussion comprised of a regulatory agency representative and the two authors/presenters. Attendees should have a basic knowledge of estimands from the ICH E9(R1) Addendum.

• A causal roadmap for generating high-quality real-world evidence (22Sep2023)

• Real-World Evidence to Support Causal Inference: Methodological Considerations for Non-Interventional Studies (18Jun2024)

This Webinar took place on 22 April 2025. Catch up by viewing the recording and the slides.

Speakers

Bios

Matt Baldwin, Amgen (Moderator)

Matt Baldwin is a Biomedical Data Stewardship Senior Manager at Amgen, where he leads data standards efforts for ADaM datasets. After 10 years as a biostatistician, he made the switch to data standards three years ago and couldn’t be happier. He has a passion for improving clinical data analysis processes with statisticians and programmers. His current interests include the implementation of estimands and many aspects around real-world data.

Matt started volunteering with DIA in 2015, but now exclusively participates in volunteer teams with CDISC and PHUSE. His PHUSE Working Group involvement mainly falls under Optimizing the Use of Data Standards and Real World Evidence.

Dr Rachele Hendricks-Sturrup, Duke-Margolis Institute for Health Policy

Dr Rachele Hendricks-Sturrup is the Research Director of Real-World Evidence (RWE) at the Duke-Margolis Institute for Health Policy in Washington, DC, strategically leading and managing the Institute’s RWE Collaborative and RWE policy research portfolio and education. As an engagement expert, biomedical researcher, bioethicist and policy practitioner with over 18 years of experience, her work centres on addressing implementation, regulatory, and ethical, legal and social implications (ELSI) at the intersection of health policy and innovation. She partners with Duke University faculty, scholars, students and external practising experts to advance the Institute’s biomedical innovation work.

Dr Lauren Eyler Dang, NIAID Biostatistics Research Branch

Dr Lauren Eyler Dang joined the NIAID Biostatistics Research Branch as a mathematical statistician in 2023. She obtained an MD from University of California, San Francisco, and an MPH and PhD in Biostatistics from University of California, Berkeley. Her research at NIAID focuses on applied and methodological causal inference problems and global infectious disease research.

Dr Juanjo Abellán, European Medicines Agency

Dr Juanjo Abellán is a mathematician and statistician. He has worked as a statistician in public offices, academia, and the pharmaceutical industry and has wide experience in epidemiology and clinical drug development. He works for the European Medicines Agency (EMA) in the Netherlands as part of the Data Analytics and Methods Task Force. His main interests focus on methodology for the generation of sound evidence in clinical trials and non-interventional studies to support regulatory decision-making around the efficacy, effectiveness and safety of medicines. He has been working on estimands for more than 10 years. He has coordinated the development of the EMA reflection paper on Use of RWD in Non-Interventional Studies To Generate RWE for Regulatory Purposes and has contributed to the development from the EMA side of the Data Analysis and Real World Interrogation Network (DARWIN EU), a platform for the generation of real-world evidence for regulatory purposes.