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Since machine learning (ML) requires resources from across the organization, this course is designed for anyone interested in sponsoring or joining a ML project within their organization which focuses on pharmacovigilance (PV). Therefore, we will specifically explore ML and its application within the PV regulatory landscape and provide a high-level introduction to ML, including tools and project tips. The core of the course will also dive deeper into applications within PV, including examples from our own experiences with ICSR identification, and discussion around what the future of ML in PV could look like. There will be time for Q&A but this years course will also be very interactive between the instructors and attendees, with both questions and some relevant tool demonstrations.

An additional registration fee is required for all preconference short courses.

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Who should attend?

This short course is designed for members of Pharma, Academia, Regulators, and Medicine interested in Machine Learning in PV.

Learning objectives

At the conclusion of this course, participants should be able to:

  • Identify advances that make ML practical;
  • Describe how ML can be applied to the regulatory and PV landscape;
  • Develop potential future use cases for ML in PV.

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