AIDD 605 Application of AI/ML to Pharmacovigilance
This graduate-level course provides an in-depth exploration of the application of Artificial Intelligence (AI) and
Machine Learning (ML) techniques to pharmacovigilance, the science and activities related to the detection,
assessment, understanding, and prevention of adverse effects or any other drug-related problems. Students will
gain a comprehensive understanding of the role of AI/ML in improving pharmacovigilance processes, including
adverse event detection, signal detection, risk management, and regulatory reporting. The course will cover
fundamental concepts of AI/ML relevant to pharmacovigilance, such as data preprocessing, feature selection,
model development, and evaluation. Through case studies from relevant drug development context and
practical exercises, students will develop the skills necessary to apply AI/ML techniques to real-world
pharmacovigilance challenges. Ethical considerations, regulatory requirements, and best practices for
implementing AI/ML in pharmacovigilance will also be discussed.
Grade Mode: Standard