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QCast: Data-Driven Dialogue in Drug Development
Quanticate
27 episodes
1 week ago
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 parti...
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Life Sciences
Science
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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 parti...
Show more...
Life Sciences
Science
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Episode 15: CRF Annotation in Clinical Trials
QCast: Data-Driven Dialogue in Drug Development
12 minutes
3 months ago
Episode 15: CRF Annotation in Clinical Trials
In this QCast episode, Jullia and Tom demystify case report form annotation in clinical trials. They explain what an annotated CRF is, why it is central to traceability and compliance, and how teams use CDASH at collection and SDTM at tabulation to keep mappings clean. Key Takeaways Treat the annotated CRF as the contract between collection and analysis to ensure end-to-end traceability.Start from CDASH templates and map cleanly to SDTM; extend standards only with clear rationale.Lock units a...
QCast: Data-Driven Dialogue in Drug Development
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 parti...