IVT’S 6TH ANNUAL
VALIDATION WEEK
MAINTAIN INTEGRITY IN
ELECTRONIC DATA AND
COMPUTERISED
SYSTEMS
17 March 2015, Amsterdam NL
Siegfried Schmitt
AGENDA
Data Integrity - What Are We Talking About?
Interactive Exercise - Learn from Inspection Findings
Integrate Data Integrity into Your Quality System
Legacy Systems
Summary and Outlook for the Future
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DATA INTEGRITY - WHAT ARE WE TALKING ABOUT?
Data Integrity
The extent to which all data are complete, consistent and accurate
throughout the data lifecycle
Data governance
The sum total of arrangements to ensure that data, irrespective of the
format in which it is generated, is recorded, processed, retained and
used to ensure a complete, consistent and accurate record
throughout the data lifecycle.
Ref. MHRA GMP Data Integrity Definitions and Guidance for Industry January 2015
http://tinyurl.com/k6wwm5y
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DATA INTEGRITY - WHO IS BEHIND IT?
PAREXEL Regulatory Handbook Data Integrity: FDA and Global Regulatory Guidance
by Siegfried Schmitt, January 2015 - http://tinyurl.com/py57y3c
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DATA INTEGRITY - WHO IS BEHIND IT?
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DATA INTEGRITY - THE MAIN CRITERIA
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THE INSPECTORS HAVE BEEN TRAINED
2010 / 2011
US FDA Inspectors received data integrity training
2012
World Health Organisation trained
2013
MHRA with guests from throughout the EU trained
MHRA Data Integrity - Issues: Understanding and Resolution
Rachel Carmichael, GMDP Inspector, 8th Sep 2014
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INTERACTIVE EXERCISE - LEARN FROM INSPECTION
FINDINGS
Instructions:
• Please work in groups
• You will be given a scenario that happened during an inspection
• You will be given options on how to respond/react
• In your group please discuss the options and pick one that you
think is the most appropriate
• We will then discuss the outcome
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INTERACTIVE EXERCISE - LEARN FROM INSPECTION
FINDINGS
The inspection of the Quality Control laboratory is underway
The list of samples for the current date is requested. The list
contains a total of 68 individual samples.
The inspector asks to be shown all 68 samples. 4 samples are
missing.
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INTERACTIVE EXERCISE - LEARN FROM INSPECTION
FINDINGS
The inspection of the Quality Control laboratory is underway
The list of samples for the current date is requested. The list
contains a total of 68 individual samples.
The inspector asks to be shown all 68 samples. 4 samples are
missing.
Option 1:
The analyst calls production and asks them to prepare 4 new
samples with the original labels. Once the samples arrive in the
laboratory, the analyst calls the inspector back and presents the
samples. The analyst explains that the samples had accidentally
been moved to an office.
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INTERACTIVE EXERCISE - LEARN FROM INSPECTION
FINDINGS
The inspection of the Quality Control laboratory is underway
The list of samples for the current date is requested. The list
contains a total of 68 individual samples.
The inspector asks to be shown all 68 samples. 4 samples are
missing.
Option 2:
As it is already late in the day (the inspector will be leaving soon), a
massive search for the samples is undertaken. It is found that the
samples must have been discarded as they can no longer be located.
The analyst writes a memo to file, which states that the samples were
accidentally discarded. This memo is presented to the inspector the
following day.
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INTERACTIVE EXERCISE - LEARN FROM INSPECTION
FINDINGS
The inspection of the Quality Control laboratory is underway
The list of samples for the current date is requested. The list
contains a total of 68 individual samples.
The inspector asks to be shown all 68 samples. 4 samples are
missing.
Option 3:
It is not possible to find out (overnight) what happened to the 4
samples. You open a deviation investigation and you inform the
inspector of this approach. You indicate that the investigation will
encompass all laboratories.
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INTERACTIVE EXERCISE - LEARN FROM INSPECTION
FINDINGS
The jury has decided
Option 1
What really happened…
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Option 2
Option 3
INTEGRATE DATA INTEGRITY INTO YOUR QUALITY
SYSTEM
Adapt your Quality system so you can detect, correct and prevent
data integrity issues
Data ownership
Internal audit including data integrity - may require additional
techniques or tools
Have forensic expertise in-house to analyse electronic data
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INTEGRATE DATA INTEGRITY INTO YOUR QUALITY
SYSTEM
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LEGACY SYSTEMS
If you have a system that has data integrity issues then you can only
fix it by going forward. There is no retrospective remediation
Include legacy systems in your data integrity compliance activities
Identified issues can be managed as a compliance issue - manage in
your quality system
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WHERE ARE YOU?
MHRA Data Integrity - Issues: Understanding and Resolution
Rachel Carmichael, GMDP Inspector, 8th Sep 2014
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SUMMARY AND OUTLOOK FOR THE FUTURE
Data integrity issues are not necessarily the result of willful
malpractice, but are often caused by insufficiently controlled
processes, poor documentation practices, suboptimal quality
oversight, and often enough, professional ignorance.
Occasionally people do intentionally falsify data
Data governance embedded in the quality system and quality culture
is a must have
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CONTACT DETAILS
Siegfried Schmitt, PhD FRSC CChem CSci
Principal Consultant
PAREXEL International
+44 7824 592401
[email protected]
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