Statistical Innovation in Pharma
Title: Real-World Data and Evidence in Study Designs Supporting Clinical Development
Friday, Aug 15th, 2025
Speaker: Frank Fan, Head of the Real World Evidence (RWE) Center of Excellence
Bristol Myers Squibb
Dr. Frank Fan is a seasoned biostatistics leader with over 20 years of experience in the pharmaceutical and biotech industries. He currently serves as the Head of the Real World Evidence (RWE) Center of Excellence at Bristol Myers Squibb, where he leads a team of statisticians and programmers to drive the strategy and implementation of real-world evidence in regulatory submissions across various disease areas. Prior to joining BMS, Dr. Fan has held several pharma company positions throughout his career in various disease area from early to late stages of clinical development. He has also contributed to academia as an adjunct faculty at Bentley University. Dr. Fan holds a Ph.D. in Statistics from the University of Wisconsin-Madison. He is the author/co-author of many statistical and clinical papers, organizer of several statistical conferences. Dr. Fan is also an executive committee member of the International Society for Biopharmaceutical Statistics, where he has been involved in organizing international conferences and managing the organizational finances.
Abstract
TBD
Statistical Excellence: How CMC Statisticians Drive Biologic Product Success
Friday, Aug 15th, 2025
Speaker: Sara Byers, Statistician
Bristol Myers Squibb
Sara Byers is a CMC Statistician with over five years of experience in Design of Experiments (DOE), statistical modeling, data analytics, and process capability. Currently, Sara serves as a Principal Statistician in Quantitative Sciences & Digital Transformation at Bristol-Myers Squibb. In this role, she supports various biologics development activities, including process development, analytical method development, stability studies, and risk assessments. Additionally, she leads or plays a key role in multiple initiatives focused on automating report generation and routine data analysis. Sara holds a Ph.D. in Biostatistics from the University of Georgia, as well as an M.S. and B.S. in Mathematics from the College of Charleston.
Abstract
Chemistry, Manufacturing, and Controls (CMC) statisticians are crucial in biologics development, providing essential support from pre-clinical through commercial stages of a product’s lifecycle. By applying rigorous statistical methods, they optimize manufacturing processes and analytical methods, leading to consistent and reliable production of biologic therapies. They analyze stability studies to ensure products maintain their efficacy and safety throughout their shelf life. Additionally, they conduct comprehensive risk assessments to identify and mitigate potential issues that could compromise product safety and efficacy, facilitating faster and more efficient regulatory approvals. A career as a CMC statistician is both rewarding and impactful, offering the opportunity to work at the intersection of science, technology, and statistics to make a tangible difference for patients. In this talk, I will share insights into this vital role and how CMC statisticians contribute to the delivery of safe and effective biologic products to improve patient health outcomes.
Making Big Impact Through Micro-innovations
Friday, Aug 15th, 2025
Speaker: Junjing “Jane” Lin, Associate Director
Takeda
Dr. Junjing “Jane” Lin is an Associate Director in Oncology Statistics at Takeda, where she serves as a program statistics lead for early to late-phase oncology drug development. Driven by a passion for curiosity and innovation, she routinely contributes to enhancing drug development processes through creative statistical thinking: she has been a functional representative for multiple generative AI initiatives at Takeda, influencing standard business practices across therapeutic areas; she served as a project co-lead in the MIT-Takeda AI/ML collaboration program; leveraging her expertise in causal inference, Bayesian statistics, machine learning, and more, she often develops new methods to support drug development and submissions, contributing to more than 20 peer-reviewed methodology publications in these fields. Additionally, Dr. Lin plays an active role in the scientific community, serving on the steering committee for ASA Biopharmaceutical Section Regulatory-Industry workshop in 2023 and 2024, and on the editorial boards of BMC Medical Research Methodology and the Journal of Biopharmaceutical Statistics, where she curated a special issue on Real-World Evidence. Prior to her tenure at Takeda, she held a position at AbbVie and earned her doctoral degree in Statistics and Applied Probability from the University of California, Santa Barbara in 2015.
Abstract
TBD
Title: Exploring Group Sequential Design for Time-to-Event Endpoints: Fundamentals, Examples, and Simulations
Friday, Aug 15th, 2025
Speaker: Yujie Zhao, Biostatistician
Merck & Co.
Yujie Zhao is a Biostatistician of the Methodology Research group of Merck & Co., Inc. Her primary areas of research interest lie in statistical design and analysis in clinical trials, with a specific focus on topics such as group sequential design and non-proportional hazards. Yujie is actively involved in the development of R packages, including gsDesign2 and simtrial. Prior to joining Merck, she completed her PhD in Industrial Engineering at the Georgia Institute of Technology.
Abstract
Group sequential design (GSD) is a statistical methodology employed in clinical trials to enable interim analyses and potential early termination based on accumulating data. It has gained significant popularity in the field of clinical trials due to its ability to enhance decision-making and expedite the development of effective treatments. The implementation of GSD has grown progressively intricate in recent times. For instance, in several recent trials, the treatment effect may vary over both time and strata. In this presentation, we focus on GSD for time-to-event endpoints, including the design procedures and comparative examples utilizing the gsDesign2 R package at https://cran.r-project.org/web/packages/gsDesign2/, as well as simulations via the simtrial R package at https://cran.r-project.org/web/packages/simtrial/.