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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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...
Episode 12: AI and Automation in Clinical Data Management
QCast: Data-Driven Dialogue in Drug Development
13 minutes
3 months ago
Episode 12: AI and Automation in Clinical Data Management
In this QCast episode, Jullia and Tom explain how AI and automation make clinical data work smoother from smarter screening and electronic consent to streaming device data, auto-summarising notes, targeted monitoring, and faster reports. They outline the basics for linking core trial systems, clarify what regulators expect on validation and audit trails, and share a simple first-year plan with quick wins and common traps to avoid. Key Takeaways Start small with a high-value workflow, define s...
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...
