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Recent Developments in the Analysis of Adaptive Designs and Their Relevance to Platform Trials
Friday, June 3, 2022
10 a.m. to 12 p.m.
Novartis Pharma AG, Basel, Schweiz
Ekkehard Glimm, PhD, is Senior Director in Biostatistics at Novartis Pharma in Basel, Switzerland. He has a PhD in mathematics from the University of Magdeburg in Germany on a topic from multivariate statistics. Ekkehard joined Novartis in 2005, working first in Oncology Biostatistics and in the Statistical Methodology group since 2006. Since 2021, he is also an adjunct professor for biostatistics at the Medical Faculty of the University of Magdeburg, Germany.
Since joining Novartis, Ekkehard's work has focused on adaptive clinical trial designs, methods for multiple endpoints in clinical trials and analysis of rare adverse events in clinical projects. He has authored and co-authored around 50 papers published in peer-reviewed scientific journals and is an associate editor of Pharmaceutical Statistics and the Biometrical Journal.
Confirmatory platform trials are recently gaining popularity in the pharmaceutical industry. Several such trials have been initiated in the past years; many of these (such as GBM Agile and PANCAN Precision Promise) are multi-sponsor trials. In contrast to similar master protocol designs (such as basket trials) which are well-established in earlier phases of clinical development, the use of platform trial designs for confirmatory studies is still subject to some debate.
In particular, there is currently no consensus on the importance of type I error control. In the spectrum from strict control of the Familywise-error rate control (FWER) across the entire platform to no type I error control at all, few researchers take the extreme positions, but within this range, opinions vary. Among the alternative concepts, compromises such as population-wise and treatment-wise error rate control have been suggested.
This talk will discuss some of these concepts. Subsequently, we will consider how type I error rate control can be guaranteed in platform trials when techniques such as response adaptive randomization or permitting new treatments into an ongoing platform trial are used. It turns out that adaptive design methodology can be adapted to such uses, but a power loss cannot be avoided.