Advanced methodologies for signal detection in emergency-use cases (COVID-19)

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Event Overview:

Statistical signal detection is a crucial tool for rapidly identifying potential risks associated with pharmaceutical products. New methods for signal detection offer the potential to identify adverse reactions from vaccines and drugs earlier.

With the accelerated environment created by the COVID-19 pandemic, commonly applied signal detection methodologies are subject to the statistical issues of masking and confounding.

The Regression-adjusted Gamma Poisson Shrinker (RGPS) signal detection methodology combines the application of conventional signal detection methodologies with the power of regression to control masking and confounding effects.

How can pharmacovigilance organizations apply advanced methodologies such as RGPS to improve the safety of emergency-use authorization products?

Key Learning:

• The potential for masking and confounding relationships between target products and adverse events
• An investigation of masking related to COVID-19 vaccine signal detection
• The applications of RGPS in emergency-use authorization situations
• New results to date, including examples of issues with confounding and masking

Speakers Name and Title:

JOSEPH TONNING, MD, MPH, FAMIA
Medical and Pharmaceutical Consultant, ThinkTrends, LLC &
Former Senior Medical Officer, FDA

RAVE HARPAZ
Senior Director Research and Data Science
Oracle Health Sciences

BILL DUMOUCHEL
Chief Statistician
Oracle Health Sciences

Times and Date:

November 29th 2022 9 am CT |10 am ET | 3 pm BST | 4 pm CET

Sponsor:

Oracle

Register Free: https://www.pharmexec.com/pe_w/signal