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 26: Medical Coding in Clinical Data Management
QCast: Data-Driven Dialogue in Drug Development
9 minutes
2 weeks ago
Episode 26: Medical Coding in Clinical Data Management
In this QCast episode, Jullia and Tom explore medical coding in clinical data management, clarifying how clinical narratives are translated into standardised terminology, why consistent coding underpins safety review and regulatory confidence, and how coding decisions shape analysis-ready datasets across a study’s lifecycle. Key Takeaways Understand how medical coding aligns adverse events, medical history, and medications using controlled dictionaries to support reliable aggregation and inte...
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...
