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 10: Managing Clinical Data Challenges with a DSMB
QCast: Data-Driven Dialogue in Drug Development
12 minutes
4 months ago
Episode 10: Managing Clinical Data Challenges with a DSMB
In this QCast, Jullia and Tom uncover how Data and Safety Monitoring Boards (DSMBs) keep trials safe and on track—what they are, when you need one, and how to avoid data pitfalls at interim looks. They unpack the DSMB charter versus the Data Safety Monitoring Plan, translate stopping boundaries into plain English, and share practical tactics for clean, blinded packages that enable confident decisions. Key Takeaways Proportional oversight keeps risk in check; higher-risk or adaptive tria...
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...
