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Data Science for Safety Professionals On-Demand Training

Analyzing and interpreting safety data throughout product development.

Overview

Consistency in the safety data analysis and interpretation strategy throughout product development and clinical trials is paramount. This on-demand course will provide an improved understanding of the behaviors and ways of working related to successful safety planning. It will also provide perspective on what good safety data analysis looks like during each phase of development through interactive case studies and discussion.

This on-demand course takes an average of 9 hours to complete. Learners have access to the course for one year from the date of purchase.

Featured topics

  • How to review data and determine appropriate questions to ask
  • How to identify patterns in laboratory and adverse event data indicative of a safety signal
  • How to evaluate signals for possible confounding and bias
  • How to apply the principals of causality assessment based on CIOMS, FDA and Bradford Hill criteria
  • How to develop an aggregate safety analysis plan
  • How to approach signal detection in the post-marketing environment
  • Role of artificial intelligence and machine learning
  • Role of real-world evidence and real-world data

Who should attend?

This course is designed for professionals working in safety data sciences, product safety, as well as medical coders. The course may also be of value to statisticians.

Learning objectives

At the conclusion of this course, participants should be able to:

  • Determine how to detect and account for instances of bias and confounding
  • Utilize causality criteria to arrive at a decision regarding the causal role of a drug in producing an adverse event
  • Plan for aggregate data analysis throughout the product lifecycle
  • Identify safety considerations in clinical trials
  • Recognize how signal detection in post-marketing differs from clinical trial data
  • Determine the evolving use of RWD/RWE

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