QCast: Data-Driven Dialogue in Drug Development

Episode 56: Bayesian Clinical Trial Design

Quanticate Episode 56

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0:00 | 9:55

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 Takeaways

  • A 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.


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📝 Episode Notes & Transcript: Find show notes, resources, and a full transcript at quanticate.com/podcast.
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About Quanticate

Founded 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 & Management
  • Biostatistics & Statistical Consultancy
  • Statistical Programming & PK/PD Analysis
  • Medical Writing & Pharmacovigilance
  • Regulatory & Submission Support
  • AI & Automation
  • Post-Marketing Safety & Real-World Data

Quanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.