Collaborative Platform Trials to Fight COVID-19

Featuring Dr Olivier Collignon, Statistics Leader at GSK

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Abstract: 'Collaborative Platform Trials to Fight COVID-19: methodological and regulatory considerations for a better societal outcome'

In the current pandemic drug developers are facing a challenging situation where, while speed is of the essence, quality of the evidence remains of primary importance. After the first reports of COVID-19 spreading to numerous countries a rush to initiate clinical trials has been observed. Many of these trials have been designed in isolation and are likely to fail providing robust statistical evidence and meeting regulatory standards. With more coordination, the number of patients involved in these trials would have been sufficient to have generated robust evidence for several investigational treatments.

We will discuss potential alternatives for a better societal outcome. In this respect a collaborative Phase 2 platform trial comparing several treatments to a shared control arm appears as an attractive solution, and we will discuss possible adaptive designs allowing to drop inefficacious treatments as data accrue. We will emphasize certain difficulties such as the heterogeneity of the target population, the potentially high number of false positive treatments progressed to Phase 3 and a time-varying standard of care.

Regulatory perspectives on the approval and reimbursement of treatments elicited by such trials during the pandemic will be given. Finally, while stressing the importance of governmental bodies in coordinating and fostering collaboration, we will argue that an optimal platform trial will differ with our societal objective: do we want to progress faster at the risk of approving potentially suboptimal treatments? Or do we want to find the most efficacious treatment at the risk of indirectly diminishing the number of lives saved?

About the speaker:

Dr Olivier Collignon works as Statistics Leader at GSK in the United Kingdom where he contributes to the development of clinical trials for immune-inflammatory diseases. He holds a PhD in Applied Mathematics and is especially interested in adaptive designs, basket/umbrella trials and historical controls and their applications to oncology. His expertise also consists in developing variable selection methods to detect promising biomarkers and build efficient clinical prediction models.

He previously worked as biostatistician in France and Luxembourg for 13 years. During this mission at the Luxembourg Institute of Health he was seconded at the European Medicines Agency in London for 4 years, where he gained regulatory experience and participated to the scientific evaluation of the design and results of clinical trials to obtain marketing authorization of new drugs in Europe.

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