In this QCast episode, Jullia and Tom unpack how real world data is analysed to complement clinical trials. They clarify the difference between real world data and real world evidence, explore the main data sources and their trade-offs, and explain how these datasets support trial decisions across feasibility, effectiveness in routine care, and longer-term safety.

Key Takeaways

• Understand the difference between real world data and real world evidence, and why real world analysis is increasingly used to add scale, context, and longer follow-up alongside trials.
• Recognise the strengths and limitations of common real world data sources, including EHRs, claims, registries, labs, and patient-generated data.
• Apply practical best practices, including pre-specifying definitions and algorithms and documenting assumptions.

🔗 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 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.

In this QCast episode, Jullia and Tom unpack how machine learning is being applied across the pharmaceutical industry. They discuss what machine learning means in a regulated drug development context, where it is already supporting discovery, development, and trial operations, and how teams can use these methods responsibly without undermining scientific or regulatory confidence.

Key Takeaways

• Understand how machine learning differs from traditional statistical approaches, and why it is particularly useful for prediction and pattern recognition in complex, high dimensional data.
• Recognise where machine learning is delivering tangible benefits across discovery, clinical trials, and real world evidence, while remaining subject to the same data integrity and governance expectations as other methods.
• Apply practical best practices, including starting with clear questions, investing in data quality and validation, and balancing model performance with transparency to support trust and regulatory acceptance.

🔗 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 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.

In this QCast episode, Jullia and Tom explore medical coding in clinical data management, clarifying how clinical narratives are translated into standardised terminology, why consistent coding underpins safety review and regulatory confidence, and how coding decisions shape analysis-ready datasets across a study’s lifecycle.

Key Takeaways

• Understand how medical coding aligns adverse events, medical history, and medications using controlled dictionaries to support reliable aggregation and interpretation.
• Recognise why clear coding conventions, dictionary version control, and integration with safety systems are critical for audit readiness and signal detection.
• Apply practical best practices, including improving verbatim data quality, coding continuously rather than at the end of a study, and maintaining transparent oversight to reduce rework and risk.

🔗 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 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.