Improving pattern discovery in the FDA Adverse Event Reporting System with Network Analysis

A research opportunity is available in the Office of Surveillance and Epidemiology (OSE), at the Center for Drug Evaluation and Research (CDER), Food and Drug Administration (FDA), located in Silver Spring, Maryland. CDER performs an essential public health task by making sure that safe and effective drugs are available to improve the health of people in the United States. As part of the FDA, CDER regulates over‐the‐counter and prescription drugs, including biological therapeutics and generic drugs. This work covers more than just medicines.

The current methods of statistical data mining are limited in their ability to facilitate the identification of patterns of potential clinical interest from spontaneous reporting systems of medical product adverse events. Network analysis (NA) allows for simultaneous representation of complex connections among the key elements of such a system and can facilitate pattern discovery.

Under the guidance of the mentor, the participant will learn how to apply NA to the FDA Adverse Event Reporting System (FAERS) to improve adverse event pattern discovery and safety signal identification. Through guided reading of published literature on methods of NA, especially as applied to document networks, the participant will gain general knowledge of NA techniques. The participant will also learn about the role of current methods of analysis of FAERS data, including statistical disproportionality methods, for drug safety assessment at FDA. The participant will also learn how to apply NA software tools to FAERS data.

Qualifications:

The qualified candidate should have received a doctoral degree in one of the relevant fields, or be currently pursuing the degree with completion before June 30, 2023. Degree must have been received within the past five years.

Preferred Qualifications:

•   A strong background in programming for data analysis, using the R programming language

•   Familiarity with medical terminology, pharmacology, and drug safety assessment

•   Qualified Master’s degree recipients will be considered

  Eligibility Requirements:

 Master’s Degree or Doctoral Degree received within the last 60 months or anticipated to be received by 6/30/2023

Discipline(s):

•   Computer, Information, and Data Sciences (1 )

•   Life Health and Medical Sciences (3 )

•   Mathematics and Statistics (3 )

  Anticipated Start Date: 2023. The start date is flexible and will depend upon a variety of factors. Application Deadline: 6/30/2023 3:00:00 PM Eastern Time Zone

  Applications accepted at https://www.zintellect.com/ Fellowship Reference Code: FDA‐CDER‐2023‐1252

  For questions, contact: Robert Ball, MD, MPH at Robert [dot] Ball [at] fda [dot] hhs [dot] gov