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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 23: Query Management in Clinical Trials
QCast: Data-Driven Dialogue in Drug Development
10 minutes
1 month ago
Episode 23: Query Management in Clinical Trials
In this QCast episode, Jullia and Tom unpack query management in clinical trials, outlining what queries are, how they move from detection to closure, and how thoughtful design, clear communication, and focused metrics turn them from administrative noise into a practical quality tool that protects data integrity, timelines, and inspection readiness. Key Takeaways Define query management as part of study design, not just an operational clean up activity.Use clear, targeted edit checks and conc...
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...