Date of Award


Document Type

Open Access Thesis

Degree Name

Medical Doctor (MD)

First Advisor

Paul G Barash MD,

Second Advisor

Bryan A. Liang, M.D., Ph.D., J.D.


Based on data collected from clinical trials and post-approval surveillance systems, the Food and Drug Administration (FDA) issues warnings to communicate increasingly dangerous and/ or preventable risks to doctors and their patients. The black box warning, the highest of all warnings issued by the FDA, emphasizes risks the FDA has deemed are critical to safe use of the drug. The warning has numerous implications for the pharmaceutical companies and physicians. The purpose of this thesis is to discuss the infrastructure of the adverse effect detection system, the effects of the Food and Drug Amendments Act (FDAAA) of 2007, and the need for FDA to reevaluate the black box warning system. Recent studies and public scandals have demonstrated the warning system is flawed, from the information on which FDA drug safety advisory committees base their decisions to the methods by which they communicate their findings. Most critically, the warnings often go unheeded by doctors due to inconsistencies in the warning system, and the language and methods by which this information is communicated. The FDAAA of 2007 addresses many of these underlying issues. Mending these dysfunctional systems will undoubtedly strengthen the advisory committees ability to properly assess safety issues. However, even if data gathering systems are perfected, doctors most likely will not abide by an inconsistent warning system that inflates or downgrades safety information. Only when the warnings accurately reflect the risk-benefit profile of a medication will healthcare providers regain trust in the FDAs ability to identify, label and communicate these issues.


This is an Open Access Thesis.

Open Access

This Article is Open Access