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Overview

*Short Courses require an additional registration fee. You do not need to be registered for the forum to attend*


This Short Course will be offered virtually – Join from anywhere!

This session will describe the importance of proactive, multi-disciplinary planning for aggregate assessment of clinical trial safety data. A framework developed by the Aggregate Safety Assessment Planning (ASAP) task force of the DIA-ASA Interdisciplinary Safety Evaluation (DAISE) working group will be discussed; including identification of safety topics of interest and the use of preferred term groupings such as the recently issued FDA Medical Queries. In addition, approaches for the evaluation of safety data from ongoing clinical trials and how aggregate safety data assessment can support IND safety reporting decisions will be addressed. As part of this session, the identification of background event rates for the study population and potential challenges in their application will be discussed.


Registered attendees for this virtual Short Course will receive access to the course recording for 2 full months post-course! This allows you to remain flexible with your schedule and not worry if you need to step out momentarily. Have a conflict with the dates of the course, but are interested in the content? Register anyway and you will receive access to the recording!


Receive $150 off your Global Pharmacovigilance and Risk Management Conference registration by registering for at least two short courses and the main conference. Purchases must be made at the same time to receive the discount. Discount will be reflected on the last page of the cart.

Learning objectives

Upon completing this course, attendees will be able to:
  • Explain the components of the Aggregate Safety Assessment Plan (ASAP)
  • Combine multidisciplinary qualitative evaluation with quantitative methods for signal detection using aggregate safety data from clinical trials
  • Describe approaches to identifying background rates for clinical trial events to inform signal detection