Many approaches for designing and analyzing clinical trials using historical (or other external study) data have been proposed in the recent past. For example, proposals have been made for bridging studies, the combination of randomized and non-randomized
evidence, and also for more general problems such as across-phases probability of success calculations. In addition, the ever-increasing number of patient registries and databases for routinely collected data, and recent data sharing initiatives (e.g.,
TransCelerate), further underline the importance of these approaches. However, there are still many open questions concerning the role which clinical trials that use such data can have in drug development. In our opinion, the three most important
- What is the state of the art regarding approaches to incorporate historical data into the formal design and analysis of clinical trials?
- Which statistical methods should we use to make historical and current data comparable?
- What are the regulatory requirements necessary for the acceptance of historical data in drug approval?
The scope of this SIG is to provide some answers to the above questions through a variety of activities. These will include:
- Publishing reviews of the available methods, sources of historical data and case studies.
- Collaborating with experts to refine and possibly extend the available methods.
- Interacting with regulators to obtain a better understanding of their requirements.
- Providing trainings, workshops and talks.
- Promoting good practice through templates for study protocols and statistical analysis plans.
Who we are
|Nicky Best (co-lead)
|Simon Wandel (co-lead)
|PRA Health Sciences
|Medical University of Vienna
|George Washington University
|Johnson & Johnson
How to get in touch
Contact: Nicky Best (GSK) or Simon Wandel (Novartis)
Email: firstname.lastname@example.org or email@example.com