Tutorial- Wednesday at 10:30 AM EDT
Title: Robust Safety Monitoring and Signal Detection Using Alternatives to the Standard Poisson Distribution
Presenters: Benjamin Duncan, Abbvie

Abstract:
Proper and timely characterization of the safety profile of a pharmaceutical product under development, is imperative for assessing the overall benefit-risk relationship of the product, and for making key development decisions. For ongoing clinical development, a comprehensive and robust safety monitoring and safety signal detection (SSD) program which is based upon inferential statistical reasoning is critical. Methods presented here can be applied to SSD as well as periodic safety monitoring (e.g., SUSAR reporting, Development Safety Update Report [DSUR], Investigator Brochure IB], etc.). Various statistical properties, distributions, and models, utilizing a Bayesian framework are considered and further examined, to identify robust methods applicable to a broad set of scenarios and situations. Methods developed for incidence counts (including those with under-dispersed distributions) with variable time-at-risk, and with underlying constant or non-constant hazard rates, are proposed and compared to traditional methods designed to assess adverse event incidence rates or binomial incidence proportions, which assume an underlying constant hazard rate and subsequent Poisson distribution for modeling event counts.

References:

1."Amit, O. Heiberger, R. Lane, P. (2008). Graphical Approaches to the Analysis of Safety Data from Clinical Trials. Pharmaceutical Statistics; 7(1): 20-35.
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2. Thomas SJ, Moreira ED Jr, Kitchin N, et al. (2021) Safety and efficacy of the BNT162b2 mRNA Covid-19 vaccine through 6 months. N Engl J Med.


Bios:


Benjamin Duncan is a Director of Safety Statistics at Abbvie Inc., and has 30 years of experience in the biopharmaceutical industry in the design and analysis of clinical trials, across all phases of development and in multiple therapeutic areas. At Abbvie, he is responsible for partnering with Patient Safety in providing integrated safety and benefit risk analyses in the immunology therapeutic area and previously supported the oncology therapeutic area. Statistical research interests include safety signal detection and general drug safety analysis, dose response, and related areas. He received his B.S. in Statistics from The University of Georgia, and his M.S. in Biostatistics from The University of North Carolina.