The Cancer Drug Development Forum (CDDF) held a live webinar titled “Bayesian Approaches in Drug Development” on Thusrday, July 11 2024, at 17:00 (CEST) / 11:00 (EST).
WEBINAR OUTLINE
A Bayesian approach is a way to formally combine knowledge from previous data or ‘beliefs’ with data from a study, thus formally integrating all available knowledge to make statements about the probability that certain treatment effects exist and in the estimation of their magnitude. Such explicit incorporation of existing data into the design and analysis of clinical trials may seem well suited for drug development and it has been argued that Bayesian approaches have the potential to reduce the time and cost to bring new treatments to patients.
Formal integration of prior beliefs is, however, not common practice in drug regulation. The pharmaceutical industry and drug regulators traditionally analyse each study as a stand-alone entity, using Frequentist statistical methods such as significance tests and confidence intervals in the documentation of efficacy of new treatments. At present, Bayesian methods are usually confined to making go/no go decisions in early phases or to make decisions on whether to implement prespecified changes in adaptive trials, though use is expanding in terms of analysis of subgroups and in extrapolation exercises.
In this CDDF webinar we discussed opportunities and challenges of expanding the use of Bayesian approaches in drug development.
Agenda: (CEST time zone)
17:00 – 17:05 Introduction – Axel Glasmacher (CDDF, DE)
17:05 – 17:30 Lecture by Rob Hemmings (Consilium, UK)
17:30 – 18:00 Panel Discussion – moderated by Axel Glasmacher (CDDF, DE) and Eva Skovlund (CDDF, NO)
WEBINAR OUTPUT