EPISODE · Sep 25, 2025 · 12 MIN
Episode 14: Using R Programming for Clinical Trial Data Analysis
from QCast: Data-Driven Dialogue in Drug Development
In this QCast episode, Jullia and Tom break down how the R programming language is being used for clinical trial data analysis. They explore its role across the trial lifecycle, from planning and cleaning through efficacy, safety, and reporting.Key TakeawaysUse the language for simulations, cleaning, modelling, safety, and reporting across the trial lifecycle.Build “reporting datasets” to simplify creation of inspection-ready tables and figures.Validate processes with pinned versions, documentation, and independent review.Start small with pilot outputs, then scale once confidence and consistency are proven.Automate style elements and maintain version control to ensure reproducibility.🔗 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.
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In this QCast episode, Jullia and Tom break down how the R programming language is being used for clinical trial data analysis. They explore its role across the trial lifecycle, from planning and cleaning through efficacy, safety, and reporting. Key Takeaways Use the language for simulations, cleaning, modelling, safety, and reporting across the trial lifecycle.Build “reporting datasets” to simplify creation of inspection-ready tables and figures.Validate processes with pinned versions, docum...
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Episode 14: Using R Programming for Clinical Trial Data Analysis
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