Event Details
Overview
In this webinar we will review the range of statistical methodologies used to harness the potential of Real-World Data (RWD) in clinical development, particularly in the context of rare diseases and small populations like paediatrics. The session will include theoretical understanding and practical case studies, with a special focus on Bayesian methods and causal inference.
Tim Friede will present how randomized controlled trials can benefit from the inclusion of real world data, especially in rare diseases. There are various promising ways of linking data from RCTs and RWD. Therefore, a more routine joint consideration of RCT and RWD data appears desirable, in particular in rare diseases.
Brad Carlin will provide a brief review of the Bayesian adaptive approach to clinical trial design and analysis, and then will discuss a variety of areas in which Bayesian methods offer a better (and perhaps the only) path to regulatory approval. Topics to be covered are expected to include:
- Leveraging historical controls and other auxiliary data
- Methods for rare and pediatric disease
- Causal inference tools to incorporate RWD/RWE
Following the talks there will be discussion and Q&A.
Who is this event intended for? Biostatisticians and drug developers in pharmaceutical industry, as well as students, people working in academia and regulators who are involved in/interested in learning about the challenges and benefits of using RWD in clinical trials in small populations and rare diseases.
What is the benefit of attending? Attendees will gain insights into different uses of RWD in small populations and rare diseases.
Timings
14:00-15:30 BST | 15:00-16:30 CEST