QCast: Data-Driven Dialogue in Drug Development

Episode 47: The Creation of ADaM Datasets for PK Analysis


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In this QCast episode, Jullia and Tom discuss how ADaM datasets are created for pharmacokinetic, or PK, analysis. They look at the role of ADPC for concentration data and ADPP for derived PK parameters, including how these datasets relate to SDTM PC and PP. The episode also covers why timing, dosing information, analysis values, flags and study-specific rules matter when preparing PK data for reporting and review.

Key Takeaways

  • ADPC supports PK concentration data, while ADPP supports derived PK parameters such as Cmax, Tmax, AUC and half-life. Both datasets help turn PK data into an analysis-ready structure.
  • PK results depend on the relationship between dosing and sample collection. Planned and actual time points, relative time variables and pre-dose samples all need careful handling.
  • Analysis values, flags and criteria variables help show which records were analysed, which were excluded and why. This makes PK outputs easier to review and reproduce.


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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.

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QCast: Data-Driven Dialogue in Drug DevelopmentBy Quanticate