Episode 56: Bayesian Clinical Trial Design

In this QCast episode, co-hosts Jullia and Tom explain how priors, posterior probabilities and predictive probabilities support clinical decisions. They also discuss external data borrowing, adaptive trial features, simulation, regulatory expectations and the operational work needed to deliver interim decisions without weakening trial credibility.Key TakeawaysA Bayesian design combines prior information with current trial data to produce an updated probability distribution.Adaptive decisions depend on timely, review-ready data and predefined governance.Historical borrowing may improve efficiency, but it can also introduce bias when external evidence does not match the current trial.🔗 Learn More & Get Support: Visit quanticate.com to explore our biometrics services and discover how we can support your next clinical trial. 📝 Episode Notes & Transcript: Find show notes, resources, and a full transcript at quanticate.com/podcast.🔔 Stay Connected: Subscribe to QCast on Apple Podcasts, Spotify, or your favourite platform to never miss an episode.About QuanticateFounded in 1994, Quanticate is a biometrics-focused CRO with over 30 years' experience delivering expert clinical and post-marketing data services worldwide. Specialising in the collection, management, standardisation, analysis, and reporting of data, we support pharma and biotech companies globally with high-quality solutions for clinical development. We specialise in:Clinical Data Capture & ManagementBiostatistics & Statistical ConsultancyStatistical Programming & PK/PD AnalysisMedical Writing & PharmacovigilanceRegulatory & Submission SupportAI & AutomationPost-Marketing Safety & Real-World DataQuanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.