There is an increasing interest in the use of external data to model parameter estimation during the study design phase, adaptation within a study or partial or full replacement of a concurrent control. External control arms (ECAs) use data outside of a clinical trial (historical trials, or real-world data) to make efficacy and other comparisons of interest against a trial experimental arm. ECAs have been widely applied in oncology and rare indications to contextualize evidence from single-arm trials in regulatory and HTA submissions.

Bayesian borrowing methods can be used to reduce the sample size of a control arm, allowing the randomisation of more patients to the active treatment, and can also be used to combine multiple data sources into a single control arm.

In this upcoming webinar, the speakers will discuss uses of ECAs and Bayesian borrowing alongside the product life-cycle from clinical development to HTA applications.

Key topics

Through the presentation of real-life case studies, the speakers will discuss methodological aspects and practical considerations for designing and implementing:

• Traditional ECAs derived from real-world data to support single arm trials
• Quantitative bias analysis, a brief overview of how they support ECAs
• Randomized studies design using Bayesian borrowing