Designing Event-based Studies: Reduce Sample Size and Increase Predictability
Many organizations find it difficult to design event-based studies such as cardiovascular or oncology trials. Understanding how many patients will be needed and how long the trial will take requires advanced statistical approaches. Such complexities make it more difficult or time consuming to optimize the operating characteristics and ensure the trial will meet your organization’s objectives. Join Cytel for an online seminar with industry thought leader Pantelis Vlachos to learn methodologies to overcome these challenges.
This webinar describes advanced techniques that have the potential to help you:
- Reduce the number of patients and duration required without compromising the validity of your study
- Be more confident that your interim analyses will be timed appropriately and more easily communicate timeline uncertainty
- Make more informed decisions about how to proceed given data observed at the interim
Together, these approaches can help you avoid unnecessarily prolonging a study. As a result, you can more confidently set expectations across your organization, make better use of limited R&D resources, improve the experience of your patients, and help them more rapidly access effective therapies.
Pantelis Vlachos, Principal, Strategic Consulting, Cytel
Pantelis is Principal/Strategic Consultant for Cytel, Inc. based in Geneva. He joined the company in January 2013. Before that, he was a Principal Biostatistician at Merck Serono as well as a Professor of Statistics at Carnegie Mellon University for 12 years. His research interests lie in the area of adaptive designs, mainly from a Bayesian perspective, as well as hierarchical model testing and checking although his secret passion is Text Mining. He has served as Managing Editor of the journal “Bayesian Analysis” as well as editorial boards of several other journals and online statistical data and software archives.