Course Descriptor

This course in collaboration with ERA Sciences provides an introduction to Data Reliability with an emphasis placed on four key reliability enablers – Data Integrity, Risk Management, Stakeholder Engagement and Application Lifecycle Management (ALM). 

Training material will include Data Integrity core concepts such as ALCOA+, Data and records Lifecycle Management, Impact of poor data practices and multiple learning case studies and scenarios challenging the trainee to understand how actions and activities can make/break data reliability efforts.

Inspection observation examples including FDA Warning letters and 483s will be examined and data risk areas discussed during learner work sessions.  References to 21 CFR part 11 and Annex 11 will be included to enhance understanding of the regulatory landscape. The importance of a Data Integrity Culture of excellence will be discussed over the two days. There will be multiple test yourself opportunities and a short assessment to benchmark your learning.

Introduction to Data Reliability and Integrity in Collaboration with ERA Sciences

SKU: Introduction-to-Data-Reliability-and-Integrity Category:

1,600.00

Clear
Dates:
  • 26/09/2022 - 27/09/2022

    15 Places Remaining

Fee:
€1600
Suitable for:

This course is particularly well suited to those new to pharma or Biopharma or who are currently working within the Life Sciences area and wish to improve their understanding of data reliability and integrity . It will be relevant right across an organisation and in particular to those working in Quality, Manufacturing, Supply Chain and IT and related disciplines such as validation and metrology. No experience is necessary although experienced data practitioners will still gain from the multiple scenario-based learning opportunities.

 

Who should attend

This course is particularly well suited to those new to pharma or Biopharma or who are currently working within the Life Sciences area and wish to improve their understanding of data reliability and integrity . It will be relevant right across an organisation and in particular to those working in Quality, Manufacturing, Supply Chain and IT and related disciplines such as validation and metrology. No experience is necessary although experienced data practitioners will still gain from the multiple scenario-based learning opportunities.

 

Learning outcomes

  • Understand why Data Reliability and Integrity are key differentials for an organisation’s success
  • Learn how to examine the GxP data lifecycle and identify where data risks may exist
  • Become part of a Data Culture of Excellence driving better results and decisions

Assessment

There will be multiple test yourself opportunities to benchmark your learning.

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