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...
In this QCast episode, Jullia and Tom unpack Statistical Analysis Plans (SAPs) — the blueprints that define how clinical trial data are turned into evidence. They explore what a SAP includes, how it links to the protocol and estimand framework, and the controls that keep analyses credible, reproducible, and inspection-ready. Key Takeaways Treat the SAP as the bridge between protocol intent and statistical execution. Anchor all analyses to the estimand framework to maint...
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...
