Quality Risk Management tools to improve data integrity in micro QC

Supported by:

1 June 2021

Supported by:

1 June 2021


Several aspects of data integrity are being discussed these days. Finding which approach, product, or tool suits your organisation best can be challenging, but is essential to help reduce risk and keep your processes controlled.

This webinar visually summarised the ICH Q9 Quality risk management GMP document and explained how you can use the approach and tools described to proactively improve your microbiological QC assays in terms of data integrity. During this hour, we provided examples for endotoxin, sterility, and micro ID tests on how to use the failure mode, effects, and criticality analysis (FMECA) method to identify, analyse and evaluate the inherent data integrity risks.

Learning objectives:

  • Definition of risk, principles of risk, and the Quality Risk Management (QRM) process.
  • Available QRM tools and the benefits that our organisation can take from this approach.
  • QRM examples for endotoxin, sterility and microbiological ID testing using the FMECA method.


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    Jordi Iglesias, Technology and Market Development Manager II, Charles River Laboratories

    Jordi Iglesias is a product specialist with Charles River’s Microbial Solutions team, serving as a technology and market development manager for the Endosafe® (endotoxin testing) brand in Europe while providing support in Spanish-speaking regions. Previously, he worked in the pharmaceutical industry as an aseptic and microbiology lab manager at Zoetis for nearly 15 years. While there he designed product validations (bioburden, sterility and endotoxins), environmental monitoring plans, cleaning and disinfection programmes, and training for aseptic area operators; he was also part of the human performance (human error assessment) group. In addition to his role at Charles River, Jordi is a member of the European Directorate for the Quality of Medicines (EDQM) microbiology group.

    One response to “Quality Risk Management tools to improve data integrity in micro QC”

    1. Hi,

      1) What method/tools would you advice for integration of quality risk management into industry and regulatory operations?

      2) Would you advice on algorithm based system for generation of final risk assessment score or would individual discretion based on set principles/SOPs suffice? I believe algorithms are lesser prone to biases than the maul system where favoritism can corrupt the system with cover-ups taking on the center stage.

      Thank you.

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