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DIA Global Center

2017年4月07日 (金) 午後 2:00 - 2017年4月07日 (金) 午後 11:00

21 Dupont Circle NW, Suite 300, Washington, DC 20036

Introduction to Signal Detection and Data Mining

概要

This introductory training course will review approaches to the implementation of signal detection and data mining as part of your pharmacovigilance operations. The requirement for companies to perform signal detection is mandatory in Europe and highly recommended in the US.  Many simple techniques can be applied to the generation and review of potential signals, which can also be augmented by the application of sophisticated data mining algorithms.

Topics discussed will include signal identification and assessment, application of available regulatory guidance documents, review of data visualization tools to facilitate signal detection and evaluation, and the use of EU GVP Module IX to structure and organize a signal management process.

何を学ぶか

  • Why signal detection is needed
  • Regulatory requirements
  • Approaches to signal detection
  • Good pharmacovigilance practices
  • Data mining fundamentals
  • Introduction to the Bayesian Confidence Propagation Neural Network (BCPNN)
  • Proportional Reporting Ratio (PRR)
  • Multi-item Gamma Poisson Shrinker (MGPS)
  • Signal detection strengthening and management
  • Signal detection process and operation
  • Risk management basics in the US and the EU

参加対象

Professionals who work in:

  • Clinical safety and pharmacovigilance
  • Pharmacoepidemiology
  • Regulatory affairs
  • Clinical development/Clinical sciences
  • Project management

学習目的

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

  • Understand how the signal detection process is used to define the safety profile of a product
  • Define signal detection and differentiate the stages of a signal management system
  • Describe the regulations and guidance documents driving the practice of signal detection in US and EU
  • Discuss various methods of qualitative and quantitative signal detection and data mining
  • Recognize how signal management systems can be organized and implemented within their company

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