The estimand framework a crucial step in defining the question of interest, needing interdisciplinary collaboration for valid inference. In this webinar, we will clarify the concept of estimands, the different types of intercurrent events and how to handle them, using examples. Emphasis will be placed on the importance of properly defining the estimand in study protocols to ensure alignment with research questions.
Speakers:
Stephane Verdun After a PhD in Applied Statistics, Stéphane headed the biostatistics unit at a small #biotech, working with laboratory and genomics data to develop models to diagnose cancer and predict cancer severity. He then spent 7 years in the Delegation for Clinical Research and Innovation of Lille Catholic Hospitals, supporting all statistical activities from the definition of research questions and project methodology all the way to reporting and co-authoring scientific publications. These include estimating sample size, analysis trials results, developing protocols, writing and reviewing of SAP, just to name a few. In this role, he focused on late phase, retrospective or RWE studies. His activities now in Venn Life Sciences cover a large range of biostatistical activities, from handling data in CDISC format, programming simple or complex statistical analyses, as well as bringing input on statistical methodology, clinical trials design and estimand definitions.
Elodie Blondiaux A biostatistician by training, Elodie has 15 years of experience in Clinical Development of pharmaceutical products and diagnostics devices. She started her career as a statistician with Sanofi in late phase trials before moving to the CRO business where she was involved in a wide range of clinical trials from Phase I to Phase IV and non-interventional studies. She has worked in several therapeutic areas, including cardiology, haematology, infectious diseases, gene therapy, and rare diseases. Her experience covers all aspects of biostatistical activities in pharmaceutical industry, including methodology and design of clinical trials, as well as statistical support of clinical trial conduct itself as statistical analysis plan writing and data analysis.
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