Description

In this QCast episode, Jullia and Tom unpack Statistical Analysis Plans (SAPs) — the blueprints that define how clinical trial data are turned into evidence. They explore what a SAP includes, how it links to the protocol and estimand framework, and the controls that keep analyses credible, reproducible, and inspection-ready. 

Key Takeaways

•  Treat the SAP as the bridge between protocol intent and statistical execution. 
•  Anchor all analyses to the estimand framework to maintain alignment and interpretability. 
•  Finalise and version-control the SAP before data lock to prevent bias and audit issues. 
•  Define derivations, flags, and datasets explicitly to enable traceable, reproducible code. 
•  Keep interim analysis logic clear, with independent oversight and documented firewalls. 
•  Apply disciplined change control and independent quality checks throughout analysis. 
•  Make every method explainable to clinicians — clarity, not complexity, drives confidence. 

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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.