Episode Details

In this QCast episode, Jullia and Tom look at how clinical data quality is shaped from study set-up through collection, review and integration. They discuss why clear definitions, well-designed data flows and proportionate quality control matter, particularly when trial data move across multiple systems or vendors.

Key Takeaways

• Clinical data should be judged by whether they are fit for the decisions and analyses the study needs to support, rather than by cleanliness alone.
• Quality problems often begin upstream. CRF design, data definitions, mappings and study instructions can create issues that later queries cannot fully correct.
• Review effort should focus on critical data and recurring patterns. Trend review can help identify process problems that isolated record checks may miss.

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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.