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Date: Tuesday\, November 10\, 2026 | 11:00 AM &n
dash\; 12:30 PM EST
Location: Online via Zoom
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strong>Jointly organized by: ASA BIOP Safety Working Group\, PHUS
E\, and PSI/EFSPI
Who is this event intended for? This webinar is intended for statisticians\, safety scientists\, phys icians\, and other researchers involved in the planning and interpretation of safety analyses in clinical trials. It is particularly relevant for th ose who want to deepen their understanding of safety estimands and the met hodological considerations in safety data analysis.
Benefit of attending: Understand key estimand considerations for single a nd aggregated safety analyses and learn from oncology experience on estima ting adverse event (AE) incidence and assessing whether an AE represents a n adverse drug reaction (ADR).
This ASA BIOP Safe ty Working Group webinar\, co-organized with PHUSE and PSI/EFSPI\, provide s an overview of the ICH E9(R1) Estimand Framework and its relevance and a pplication to the analysis of clinical trial safety data\, for both single studied and aggregated analysis across multiple studies.
Through pr esentations by industry experts\, attendees will gain insight into the use of the Estimand Framework for safety analyses. The webinar will explore h ow different clinical safety questions can be translated into appropriate estimands and aligned with corresponding estimators. Speakers will also di scuss practical considerations for defining and handling intercurrent even ts\, including competing risks and informative censoring\, and their impli cations for interpreting safety outcomes.
As the second webinar in a planned series on analysis of safety information in clinical trials\, thi s session will present examples from oncology and non-oncology settings to illustrate current thinking and practical approaches to applying ICH E9(R 1) principles in safety analyses.
\nTo register for this event\, please \;click here.
| Speaker\n | Biography\n | |
 < em>George Kordzakhia\, Ph.D. &n bsp\;Statistical Science Senior Director\, AstraZeneca \; | Dr. George Kordzakhia is a Statistical Science Senior Di rector in the Cardiovascular\, Renal and Metabolic (CVRM) Biometrics group at AstraZeneca in Gaithersburg\, USA. Before joining AstraZeneca in 2022\ , he spent more than 15 years at the FDA\, working in the Center for Drug Evaluation and Research (CDER). There\, he led statistical teams supportin g multiple clinical review divisions and played a key role in the regulato ry evaluation of new drug applications\, gaining an in-depth understanding of the statistical\, clinical\, and regulatory considerations that shape the assessment of drug safety and benefit-risk. At AstraZeneca\, Dr. Kordzakhia provides statistical leadership and strategic input to clinica l development programs across the CVRM portfolio. He has also contributed to several scientific publications on statistical safety analysis in clini cal trials. Drawing on his experience on both the regulatory and industry sides\, he is committed to advancing rigorous\, transparent\, and practica l statistical approaches to safety evaluation. \; | Safety Estimands for Sin gle Studies and Aggregated Analysis Aggregated analyses acr oss multiple clinical trials are crucial for comprehensive safety evaluati ons. The aggregation of studies offers significant benefits\, such as enha nced precision in estimations. However\, it demands a methodical approach to prevent the introduction of unnecessary biases in comparative analyses and to ensure that estimates remain meaningful. In this presentation\, we employ the ICH estimand framework to guide the aggregation of clinical tri als\, discussing essential principles and statistical considerations vital for planning integrated safety analyses. |
 Ellen Snyder\,
Ph.D. | Dr. Ellen Sim Snyder has worked in the Biostatistics Depa rtment at Merck &\; Co.\, Inc.\, Rahway\, New Jersey\, USA\, for more t han 30 years. She spent more than 20 years in Late Development Statistics\ , leading and supporting new drug applications across multiple therapeutic areas\, and has led the Oncology Therapeutic Area in Clinical Safety Stat istics for 11 years. Between completing her master&rsquo\;s and PhD degree s in Biostatistics at the University of North Carolina at Chapel Hill\, sh e worked in Clinical Epidemiology at the University of Pennsylvania School of Medicine. In this role\, she taught statistics to postdoctoral medical fellows in the International Clinical Epidemiology Network (INCLEN) and p rovided statistical support for large pharmacoepidemiologic and other epid emiologic studies. She has authored or coauthored more than 50 publication s in the medical and statistical literature. She is an active member of th e ASA Biopharmaceutical Section Safety Working Group\, where she leads the Oncology Safety and Safety Estimands for Observational Studies task force s and serves on the Methodology and Leadership Teams. She recently joined the PHUSE Safety Analytics Team and APPRAISE\, a European Union-funded pha rmacovigilance project involving partners from the pharmaceutical industry \, academia\, and the European Medicines Agency.\n | Estimating &\;
Comparing the Incidence of Adverse Events using Clinical Trial Data Focusi
ng on Oncology Trials: \; A Safety Estimand Perspective (Part 1 of 3)<
/strong> This presentation will examine the estimation of adve rse event (AE) incidence from clinical trial data and analyses to assess w hether an AE represents an adverse drug reaction (ADR)\, with an emphasis on oncology studies. It will highlight the application of the ICH E9(R1) E stimand Framework to define the safety question\, select aligned estimator s\, and report estimates at clinically meaningful time points\, in additio n to conventional AE tabulations. Various intercurrent-event strategies fo r addressing treatment switching or discontinuation\, censoring\, and comp eting events that lead to unequal exposure times\, will be examined from a safety perspective. The discussion will explain why cumulative incidence estimates based on a while-on-treatment strategy for selected intercurrent events may be misleading when interpreted as AE risk over a common period or as evidence for or against a causal relationship with the drug. The pr esentation will also consider Section 10.7 of ICH M11 in relation to plann ing safety analyses\, including risk estimation and comparison. |
 Wei Wang\, Ph.D. | Dr. Wei Wang is an Associate Director of Biostatistics at Da iichi Sankyo\, where he serves as a cross-program lead safety statistician supporting the clinical development of oncology compounds. Prior to joini ng Daiichi Sankyo\, he worked at Merck as a safety statistician supporting multiple oncology development programs. His research interests include st atistical methods for safety monitoring in ongoing clinical trials\, causa l inference\, and survival analysis. He is an active contributor to the AS A Biopharmaceutical Section Safety Working Group. Wei received his PhD in Biostatistics from Rutgers University. | Estimating &\; Comp
aring the Incidence of Adverse Events using Clinical Trial Data Focusing o
n Oncology Trials: \; A Safety Estimand Perspective (Part 2 of 3) This presentation focuses on a si mulation study comparing common estimators of adverse event (AE) incidence &mdash\;the crude proportion\, Kaplan&ndash\;Meier (KM) estimate\, and Aal en&ndash\;Johansen (AJ) estimate of cumulative incidence&mdash\;across sev eral data scenarios with and without censoring and competing events. The r esults illustrate how censoring and competing events affect the estimators and how each estimator addresses a different clinical question. &nb sp\; \; |
 Viviana Rodriguez\,
Ph.D. | Dr. Viviana Rodriguez is an Associate Principal Scient ist in Biostatistics and Research Decision Sciences (BARDS)\, Clinical Saf ety Statistics\, at Merck &\; Co.\, Inc. Rahway\, New Jersey\, USA. A F ulbright Scholar\, she received her Ph.D. in Biostatistics from Virginia C ommonwealth University in 2020. She provides statistical leadership for on cology safety programs and contributes to strategic BARDS initiatives supp orting drug development and safety evaluation. Before joining Merck\, she spent 15 years in academia as an Assistant Professor\, leading and collabo rating on applied clinical research across multiple disciplines. Her profe ssional interests include generalized statistical modeling\, survival anal ysis\, compositional data analysis\, and drug safety.\n | Estimating &a mp\; Comparing the Incidence of Adverse Events using Clinical Trial Data F ocusing on Oncology Trials: \; A Safety Estimand Perspective (Part 3 o f 3) Kaplan&ndash\;Meier (KM) and Aalen&ndash\;Johansen (AJ) estimators rely on the assumption of noninformative censoring\, which may be questionable when treatment discontinuation is associated with subsequ ent adverse event (AE) risk. This presentation will examine analyses for a ssessing departures from this assumption and introduce inverse probability of censoring weighting (IPCW) as an approach to addressing potentially in formative censoring. An overview of IPCW will explain how weights are calc ulated using the inverse of each participant&rsquo\;s estimated conditiona l probability of remaining uncensored\, with the probabilities and resulti ng weights updated over time during follow-up. \; |
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