Evaluation of a new treatment has always required a benefit-risk (B-R) assessment. Guidance on how to select specific B-R frameworks and quantitative methods, along with case studies and best practice sharing, is mostly focused on pre-marketing applications. This tutorial contains two parts. Part I covers the role of BR assessments in medicine development and regulation, key elements of BR evaluations in a product’s life cycle, and general guidance. In addition, we will present practical examples, lessons learned, and best practices that illustrate how to conduct structured B–R assessment in clinical development and regulatory submission. With a goal of potentially expanding BR assessment to utilizing real world evidence (RWE), Part II presents the utility of RWE that could 1) help expedite generation of research hypotheses that sharpen the focus of clinical research, including the designs of randomized controlled trials (RCTs), 2) in pre-approval setting, augment conventional RCT data with data from patients whose diversity reflects real word practice, resulting in better insight on safe and effective use of innovation; and 3) in post-approval arena, RWE generated from long-term observation of patient outcomes will identify factors in safety, clinical effectiveness and personalization of care that are difficult to identify among short-term RCTs conducted among highly homogenous groups of patients. Case studies with the use of RWEs will be shared in the tutorial.
Dr. Weili He is the head of Global Medical Affairs Statistics, Data and Statistical Sciences at AbbVie. Prior to joining AbbVie, Weili worked in Clinical Biostatistics at Merck & Co., Inc. for over 20 years. Her research interests include survival and longitudinal data modeling, missing data imputation, cancer Phase I & II designs, repeated categorical data modeling, surrogate marker evaluations, adaptive design methodologies and implementations, methods for benefit-risk assessment, and methods utilizing real world evidence to augment clinical research and HTA assessment. Dr. He has published extensively in the areas of adaptive designs and benefit-risk evaluations, and is the author of more than 50 peer-reviewed publications in statistical and medical journals. She is also an editor of the book, “Practical Considerations for Adaptive Trial Design and Implementation”, published by Springer in 2014, and the book, “Benefit-Risk Assessment Methods in Medical Product Development: Bridging Qualitative and Quantitative Assessments”, published by CRC Press in 2016. She has also been involved in many professional activities and services, including serving as co-chair of the QSPI Benefit-Risk working group since 2013, co-chair of the DIA ADSWG KOL lecture series from 2012-2016, co-lead of the DIA ADSWG Best Practice Subteam from 2014-2016, Associate Editor for the journal of Statistics in Biopharmaceutical Research (SBR) since 2014, and co-chair of the 2017 ASA Biopharmaceutical Regulatory-Industry workshop.
Dr. Qi Jiang is an Executive Director of Global Biostatistical Science at Amgen. In this role, she is biostatistical therapeutic area head for oncology and hematology and is the lead of the Center of Excellence for Safety and Benefit-Risk. In addition, Qi provides oversight to Amgen’s biostatistical efforts in Asia Pacific. Before joining Amgen, Qi worked at the Harvard School of Public Health, Merck, and Novartis. Qi has many years of clinical trial experience across a broad spectrum of therapeutic areas and has authored over 70 peer-reviewed publications on method development, study design, and data analysis and reporting. In addition, Qi is an editor of the book “Quantitative Evaluation of Safety in Drug Development” published in 2014, and an editor of the book “Benefit-Risk Assessment Methods in Medical Product Development” published in 2016. Qi is also a co-lead of American Statistical Association Biopharmaceutical Section Safety Working Group and a co-lead of the Quantitative Sciences in the Pharmaceutical Industry (QSPI) Benefit-Risk working group. Qi is an Associate Editor for Statistics in Biopharmaceutical Research and is a Fellow of the American Statistical Association.