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Signal Management in Pharmacovigilance Virtual Live Training Course

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Overview

This virtual live training course covers essential concepts of signal detection and signal management and provides guidance on how to apply these concepts at participants' function and their organisation, including the data mining techniques for large volume ADR data analysis.

The entire course is in line with the latest guidelines on EU Good Pharmacovigilance Practices (GVP): Module IX – Signal management (rev. 1), Commission Implementing Regulation (EU) No. 520/2012, CIOMS VIII and relevant EMA guidelines.

This training is primarily developed based on EU legislation, but it also covers regulatory expectations for signal management in the US, Switzerland, Canada, Australia, and few other countries.

Participants benefit from the hands-on experience of trainers who have worked for many years in signalling activities and are ready to not only explain the legislation, but also provide personal experience and most commonly followed practices that are often considered as industry standards.

Training includes enough time for group works questions and discussions.

 

Featured topics

  • Signal Detection – Theory, methods (frequentist (PRR, ROR) and Bayesian (MGPS, BCPNN)), data mining
  • Signal Management – Detection, validation, confirmation, analysis and prioritisation, assessment, and recommendation for action
  • Regulatory expectations in the EU, US, Switzerland, Canada, Australia
  • EVDAS introduction and implementation in signal management 
  • Strategy for implementation of signal management process in your own organisation (covering both small and large companies)

 

Who should attend?

This virtual live training course is designed for professionals working in:

  • Pharmacovigilance (including EU QPPVs)
  • Drug Safety and Risk Management
  • Signal Management and Safety Science
  • Pharmacoepidemiology
  • Information Technology
  • Pharmacovigilance Consultancies and Service Providers
  • Quality and Compliance

Course level: Intermediate, for professionals with 2-3 years (or more) of experience in Pharmacovigilance, or related functions who are working in PV around signal management.

The individual modules always have introduction and space for discussion of more complex questions and scenarios.

 

Learning objectives

After the completion of this virtual live training course, participants will be able to:

  • Apply the essential concepts and principles of signal management in PV and implement or improve this process in their own organisation
  • Understand different approaches to signal management that are followed by various organisations
  • Operate and implement EVDAS into signal management process 
  • Understand the regulatory expectations at different geographic regions

Learning objectives will be achieved using a combination of trainer presentations, trainer-led plenary discussions, and case studies.

 


TECHNICAL REQUIREMENTS

To test your system compatibility, please click on the link: https://diaglobal.zoom.us/test

Operating Systems

  • Windows: XP 32-bit (SP3), 2003, Vista 32-bit/64-bit, Windows 7 32-bit/64-bit
  • Mac OS X: 10.5, 10.6, 10.7
  • Linux: 32-bit Ubuntu 10.x,11.x 32-bit Fedora 15/16, 32-bit Red Hat 5/6, 32-bit OpenSuSE 11.4

Minimum System Requirement

  • Windows: Processor – Requires Sun Java 5 or higher, Recommend ActiveX be enabled for Internet Explorer
  • Mac OS X: Processor – JavaScript and cookies enabled, Requires Apple Java 5 or higher, No support for Remote Access
  • Linux: Processor – JavaScript and cookies enabled, Requires Apple Java 5 or higher, No support for Remote Access

Browsers

  • Windows: Internet Explorer 6, 7, 8, 9, (Win7 Only), Firefox latest (32-bit), Chrome latest
  • Mac OS X: Safari 4-Mar; Firefox 2/3/3.5
  • Linux: Mozilla 1.7, Firefox 2/3/3.5

Internet Connection Speed

  • Windows: Intel or AMD processor (1GHz or faster), At least 512 MB RAM (at least 2 GB RAM for Vista)
  • Mac OS X: Intel processor, At least 512 MB RAM
  • Linux: At least 512 MB RAM

Display

  • 800x600 pixel resolution or greater (1024x768 pixels recommended)

 

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+41 61 225 51 51


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