Data Integrity – Essentials & Solutions
Fréderique Backaert – November 8th 2016
What you will learn
• Data Integrity – Why / What
• Data life cycle
• Core Data Integrity concepts & building blocks
• Short & mid-term actions enabling a focused road to compliance
pi | contact@3-14.com | www.3-14.com2 | © 2016 pi
Data Integrity – Why
pi | contact@3-14.com | www.3-14.com3 | © 2016 pi
Scope & Application
21 CFR Part 11
FDA
2003
“generics scandal”
late 1980s
Data Integrity
Pilot Program
FDA
2010
2007
FDA
computerised systems
in GCP
1997
FDA
21 CFR Part 11
Final Rule
Quality
Impact on Patient
Business
Oct, 2016
CFDA
guidance
(draft)
(draft)
guidance PIC/S
Aug, 2016
Jul, 2016
MHRA
guidance
(draft)
guideline
WHO
Jun, 2016
Apr, 2016
FDA
Data Integrity
guidance (draft)
guidance
MHRA
Mar, 2015
2011
EudraLex
Volume 4
Annex 11
# 483 citations on
Data Integrity topics
Insufficient data security
Poor data storage and archives
No adequate data review processes
Poor knowledge of data streams
Data Integrity part of routine GMP inspectionsFocus on
raw data
Focus on
computerised systems
Focus on
“ALCOA”
“The extent to which all data are accurate, complete and consistent throughout
the data life cycle” (MHRA, March 2015)
Applies for both electronic & paper-based documentation streams in GMP
regulated environments.
Data Integrity – What
pi | contact@3-14.com | www.3-14.com4 | © 2016 pi
validated
reviewed
data/metadata good documentation practices
training
method management
guaranteed throughout
the legal hold
“all phases in the life of data” (MHRA, March 2015)
Data life cycle
pi | contact@3-14.com | www.3-14.com5 | © 2016 pi
Review
Creation Record
Processing
Calculations
Report
Reprocessing
Recalculations
(Meta)Data
Modifications
Retirement Archive Retention Backup
Data owner
User - reviewer
User - author
Administrator
Core concepts:
ALCOA
Audit trail review
ALCOA model
pi | contact@3-14.com | www.3-14.com6 | © 2016 pi
ALCOA
• Acronym created by the FDA as a guide to the expectations concerning source data
A – Attributable
Who performed the action that gathered the data?
Paper Electronic
initials of author no generic login accounts
actions are documented &
dated
metadata unambiguously
linked to data
good documentation
practices
validation for intended use
ALCOA model
pi | contact@3-14.com | www.3-14.com7 | © 2016 pi
• Acronym created by the FDA as a guide to the expectations concerning source data
L – Legible
The data remains available & accessible throughout the
life cycle
Paper Electronic
permanent ink,
single-line cross-outs
maintain human
readability
reason of change old and new values
good documentation
practices
validation for intended use
ALCOA
ALCOA model
pi | contact@3-14.com | www.3-14.com8 | © 2016 pi
• Acronym created by the FDA as a guide to the expectations concerning source data
C – Contemporaneous
The data is recorded as the action takes place
Paper Electronic
chronological
batch record design
automatic saving
controlled printing
date & time stamps cannot
be altered
good documentation
practices
software design
validation for intended use
ALCOA
ALCOA model
pi | contact@3-14.com | www.3-14.com9 | © 2016 pi
• Acronym created by the FDA as a guide to the expectations concerning source data
O – Original
Documentation should be performed on original records
Paper Electronic
no scratches
no copies of electronic
records can be made
good documentation
practices
software design
validation for intended use
ALCOA
Original
ALCOA model
pi | contact@3-14.com | www.3-14.com10 | © 2016 pi
• Acronym created by the FDA as a guide to the expectations concerning source data
A – Accurate
Records should be honest and thorough
Paper Electronic
witness checks
technical controls on
input fields
reason of change all changes are reviewed
good documentation
practices
audit trail review
validation for intended use
ALCOA
Original
automatic
or
systematic
Audit trail review
pi | contact@3-14.com | www.3-14.com11 | © 2016 pi
“metadata which represents a log of performed GMP-critical actions which facilitates a
reconstruction of the performed GMP activities”
forensic
Analysis 1 Analysis 2 Analysis 3
Analysis performance
Method management
User management
Data management
System configuration
frequency
Review 1 Review 3Review 2
Audit trail review
pi | contact@3-14.com | www.3-14.com12 | © 2016 pi
“metadata which represents a log of performed GMP-critical actions which facilitates a
reconstruction of the performed GMP activities”
Analysis performance
Method management
User management
Data management
System configuration
frequency
Data review – Analysis audit trail
Part of batch release process
• actions in line with procedures and/or
with pre-validated conditions
• accuracy, completeness & consistency of (meta)data
• focus on data creation, modification and deletion
Review 1 Review 2 Review 3
Audit trail review
pi | contact@3-14.com | www.3-14.com13 | © 2016 pi
“metadata which represents a log of performed GMP-critical actions which facilitates a
reconstruction of the performed GMP activities”
Analysis performance
Method management
User management
Data management
System configuration
frequency
Analysis 1 Review 1 Analysis 2 Review 2Analysis 3 Review 3 Periodic Review
Periodic review – System audit trail review
Frequency depends on modern QRM
• method creation or method parameter changes
• system configuration changes
• data backup and/or archival
• login of business admin or system admin
• focus on holistic changes to instrument / software
The road to compliance
pi | contact@3-14.com | www.3-14.com14 | © 2016 pi
Data Integrity
Compliance
Quality System
Instrument
Software
Qualification status
Data management
CSV approach
Data Integrity policy
Corporate security
procedure
Measurement
Trending
CAPA handling
Deviation management
Culture
Company tolerance
for common mistakes
Open communication
Management responsibility
Materials
Procedures
Audit trail review
Data review tools
Ability & Motivation
Human
Day-to-day focus on
ALCOA principles
Separated roles
& responsibilities
Deviation
management
The road to compliance
pi | contact@3-14.com | www.3-14.com15 | © 2016 pi
Short-term actions
• Identify business processes with data streams
mapping of all business processes
• DI evaluations with pi’s proprietary DI Quick Scan
assessment of both electronic and paper-based streams in
business processes towards current DI requirements
quick matrix-based, system-by-system
efficient 1:1 relation with regulatory requirements
prioritised according to GMP criticality
Outcome
reveals
non-conformities
&
identifies
globalised CAPA plan
detailed data flows
&
GMP criticality of
all data streams
The road to compliance
pi | contact@3-14.com | www.3-14.com16 | © 2016 pi
Mid-term actions
• Data Integrity remediation
full project support including assessment program, driving
the CAPA plan and deployment of remediation.
• Data Integrity training
setting-up training programs tailored to different focus areas:
production, internal audit, quality assurance, quality control, …
• Data Integrity strategy
implementing a risk-based, lean and effective data integrity
strategy, on par with the latest GMP requirements and
embedded within your corporate quality system.
Outcome
corporate-driven
culture towards DI
Data Integrity
compliance
secured base
Conclusions
pi | contact@3-14.com | www.3-14.com17 | © 2016 pi
• Data Integrity remains to have a direct impact on patient
business and
quality of product & processes.
• Data Integrity, as a KPI, is an indicator for LEAN data flows.
• DI Quick Scan is a swift assessment towards Data Integrity compliance for both
paper & electronic based data streams.
• DI Quick Scan sets the standard for a roadmap towards Data Integrity compliance.
About the speaker
Fréderique Backaert
Business Developer
pi
Fréderique Backaert holds a PhD in Organic Chemistry and has been working for pi life sciences consultancy
for more than two years. In the meanwhile, he has been challenged with specific data integrity improvement
programs in the pharmaceutical industry.
These experiences were the fundamentals of pi's risk-based solutions towards arising data integrity questions.
18 | © 2016 pi pi | contact@3-14.com | www.3-14.com
Our Data Integrity services include:
Data Integrity services
DI Quick Scan
• Two step process, on both paper and electronic records, including a
quick scan using our proprietary method and tools and in-depth audit
of QC and manufacturing records.
• Thorough audit of your software, analysing whether or not they meet
current data integrity requirements.
• An efficient yet detailed analysis, saving you time and assuring a
minimal disruption of operations.
Data Integrity Remediation
• Full project support, including assessment, driving the CAPA plan
and deployment and implementation of remediation
Data Integrity Strategy
• Design and roll-out of a lean and effective data integrity strategy, on
par with the latest GMP requirements and embedded within your
QMS
Data Integrity Training
• On-site training on Data Integrity for management, operations, QC
and QA staff .
• Focus on data integrity methodology and compliance program, the
importance of data integrity and on creating the right culture to
maintain data integrity.
19 | © 2016 pi pi | contact@3-14.com | www.3-14.com
References
pi | contact@3-14.com | www.3-14.com20 | © 2016 pi
• 21 CFR Part 11 Electronic records; Electronic Signatures
• Guidance for Industry, Part 11 Electronic records; Electronic Signatures – Scope & Application
• Guidance for Industry Computerized Systems Used in Clinical Investigations
• EudraLex Volume 4 Annex 11 - Computerised systems
• MHRA GMP Data Integrity Definitions and Guidance for Industry March 2015
• Data Integrity and Compliance With cGMP Guidance for Industry
• Guidance on good data and record management practices
• MHRA GxP Data Integrity Definitions and Guidance for Industry
• Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
Our value proposition
19 | © 2016 pi pi | contact@3-14.com | www.3-14.com
pi is the strategic partner of choice to some of the world’s leading life science companies.
We offer our clients unique expertise and strategic consultancy of the highest quality.
We dedicate ourselves to bringing excellence to the life sciences industry.
We’ve grown by learning how to be better.
Better resourced to focus our faculty of consultants’ singular experience and knowledge.
Better managed to share their depth of understanding.
Better prepared to challenge orthodox thinking.
And better able to redefine accepted best practice.
To accept no other standard than excellence.
Connect with us on LinkedInVisit our website Follow us on Twitter

Data Integrity webinar - Essentials & Solutions

  • 1.
    Data Integrity –Essentials & Solutions Fréderique Backaert – November 8th 2016
  • 2.
    What you willlearn • Data Integrity – Why / What • Data life cycle • Core Data Integrity concepts & building blocks • Short & mid-term actions enabling a focused road to compliance pi | contact@3-14.com | www.3-14.com2 | © 2016 pi
  • 3.
    Data Integrity –Why pi | contact@3-14.com | www.3-14.com3 | © 2016 pi Scope & Application 21 CFR Part 11 FDA 2003 “generics scandal” late 1980s Data Integrity Pilot Program FDA 2010 2007 FDA computerised systems in GCP 1997 FDA 21 CFR Part 11 Final Rule Quality Impact on Patient Business Oct, 2016 CFDA guidance (draft) (draft) guidance PIC/S Aug, 2016 Jul, 2016 MHRA guidance (draft) guideline WHO Jun, 2016 Apr, 2016 FDA Data Integrity guidance (draft) guidance MHRA Mar, 2015 2011 EudraLex Volume 4 Annex 11 # 483 citations on Data Integrity topics Insufficient data security Poor data storage and archives No adequate data review processes Poor knowledge of data streams Data Integrity part of routine GMP inspectionsFocus on raw data Focus on computerised systems Focus on “ALCOA”
  • 4.
    “The extent towhich all data are accurate, complete and consistent throughout the data life cycle” (MHRA, March 2015) Applies for both electronic & paper-based documentation streams in GMP regulated environments. Data Integrity – What pi | contact@3-14.com | www.3-14.com4 | © 2016 pi validated reviewed data/metadata good documentation practices training method management guaranteed throughout the legal hold
  • 5.
    “all phases inthe life of data” (MHRA, March 2015) Data life cycle pi | contact@3-14.com | www.3-14.com5 | © 2016 pi Review Creation Record Processing Calculations Report Reprocessing Recalculations (Meta)Data Modifications Retirement Archive Retention Backup Data owner User - reviewer User - author Administrator Core concepts: ALCOA Audit trail review
  • 6.
    ALCOA model pi |contact@3-14.com | www.3-14.com6 | © 2016 pi ALCOA • Acronym created by the FDA as a guide to the expectations concerning source data A – Attributable Who performed the action that gathered the data? Paper Electronic initials of author no generic login accounts actions are documented & dated metadata unambiguously linked to data good documentation practices validation for intended use
  • 7.
    ALCOA model pi |contact@3-14.com | www.3-14.com7 | © 2016 pi • Acronym created by the FDA as a guide to the expectations concerning source data L – Legible The data remains available & accessible throughout the life cycle Paper Electronic permanent ink, single-line cross-outs maintain human readability reason of change old and new values good documentation practices validation for intended use ALCOA
  • 8.
    ALCOA model pi |contact@3-14.com | www.3-14.com8 | © 2016 pi • Acronym created by the FDA as a guide to the expectations concerning source data C – Contemporaneous The data is recorded as the action takes place Paper Electronic chronological batch record design automatic saving controlled printing date & time stamps cannot be altered good documentation practices software design validation for intended use ALCOA
  • 9.
    ALCOA model pi |contact@3-14.com | www.3-14.com9 | © 2016 pi • Acronym created by the FDA as a guide to the expectations concerning source data O – Original Documentation should be performed on original records Paper Electronic no scratches no copies of electronic records can be made good documentation practices software design validation for intended use ALCOA Original
  • 10.
    ALCOA model pi |contact@3-14.com | www.3-14.com10 | © 2016 pi • Acronym created by the FDA as a guide to the expectations concerning source data A – Accurate Records should be honest and thorough Paper Electronic witness checks technical controls on input fields reason of change all changes are reviewed good documentation practices audit trail review validation for intended use ALCOA Original
  • 11.
    automatic or systematic Audit trail review pi| contact@3-14.com | www.3-14.com11 | © 2016 pi “metadata which represents a log of performed GMP-critical actions which facilitates a reconstruction of the performed GMP activities” forensic Analysis 1 Analysis 2 Analysis 3 Analysis performance Method management User management Data management System configuration frequency Review 1 Review 3Review 2
  • 12.
    Audit trail review pi| contact@3-14.com | www.3-14.com12 | © 2016 pi “metadata which represents a log of performed GMP-critical actions which facilitates a reconstruction of the performed GMP activities” Analysis performance Method management User management Data management System configuration frequency Data review – Analysis audit trail Part of batch release process • actions in line with procedures and/or with pre-validated conditions • accuracy, completeness & consistency of (meta)data • focus on data creation, modification and deletion Review 1 Review 2 Review 3
  • 13.
    Audit trail review pi| contact@3-14.com | www.3-14.com13 | © 2016 pi “metadata which represents a log of performed GMP-critical actions which facilitates a reconstruction of the performed GMP activities” Analysis performance Method management User management Data management System configuration frequency Analysis 1 Review 1 Analysis 2 Review 2Analysis 3 Review 3 Periodic Review Periodic review – System audit trail review Frequency depends on modern QRM • method creation or method parameter changes • system configuration changes • data backup and/or archival • login of business admin or system admin • focus on holistic changes to instrument / software
  • 14.
    The road tocompliance pi | contact@3-14.com | www.3-14.com14 | © 2016 pi Data Integrity Compliance Quality System Instrument Software Qualification status Data management CSV approach Data Integrity policy Corporate security procedure Measurement Trending CAPA handling Deviation management Culture Company tolerance for common mistakes Open communication Management responsibility Materials Procedures Audit trail review Data review tools Ability & Motivation Human Day-to-day focus on ALCOA principles Separated roles & responsibilities Deviation management
  • 15.
    The road tocompliance pi | contact@3-14.com | www.3-14.com15 | © 2016 pi Short-term actions • Identify business processes with data streams mapping of all business processes • DI evaluations with pi’s proprietary DI Quick Scan assessment of both electronic and paper-based streams in business processes towards current DI requirements quick matrix-based, system-by-system efficient 1:1 relation with regulatory requirements prioritised according to GMP criticality Outcome reveals non-conformities & identifies globalised CAPA plan detailed data flows & GMP criticality of all data streams
  • 16.
    The road tocompliance pi | contact@3-14.com | www.3-14.com16 | © 2016 pi Mid-term actions • Data Integrity remediation full project support including assessment program, driving the CAPA plan and deployment of remediation. • Data Integrity training setting-up training programs tailored to different focus areas: production, internal audit, quality assurance, quality control, … • Data Integrity strategy implementing a risk-based, lean and effective data integrity strategy, on par with the latest GMP requirements and embedded within your corporate quality system. Outcome corporate-driven culture towards DI Data Integrity compliance secured base
  • 17.
    Conclusions pi | contact@3-14.com| www.3-14.com17 | © 2016 pi • Data Integrity remains to have a direct impact on patient business and quality of product & processes. • Data Integrity, as a KPI, is an indicator for LEAN data flows. • DI Quick Scan is a swift assessment towards Data Integrity compliance for both paper & electronic based data streams. • DI Quick Scan sets the standard for a roadmap towards Data Integrity compliance.
  • 18.
    About the speaker FréderiqueBackaert Business Developer pi Fréderique Backaert holds a PhD in Organic Chemistry and has been working for pi life sciences consultancy for more than two years. In the meanwhile, he has been challenged with specific data integrity improvement programs in the pharmaceutical industry. These experiences were the fundamentals of pi's risk-based solutions towards arising data integrity questions. 18 | © 2016 pi pi | contact@3-14.com | www.3-14.com
  • 19.
    Our Data Integrityservices include: Data Integrity services DI Quick Scan • Two step process, on both paper and electronic records, including a quick scan using our proprietary method and tools and in-depth audit of QC and manufacturing records. • Thorough audit of your software, analysing whether or not they meet current data integrity requirements. • An efficient yet detailed analysis, saving you time and assuring a minimal disruption of operations. Data Integrity Remediation • Full project support, including assessment, driving the CAPA plan and deployment and implementation of remediation Data Integrity Strategy • Design and roll-out of a lean and effective data integrity strategy, on par with the latest GMP requirements and embedded within your QMS Data Integrity Training • On-site training on Data Integrity for management, operations, QC and QA staff . • Focus on data integrity methodology and compliance program, the importance of data integrity and on creating the right culture to maintain data integrity. 19 | © 2016 pi pi | contact@3-14.com | www.3-14.com
  • 20.
    References pi | contact@3-14.com| www.3-14.com20 | © 2016 pi • 21 CFR Part 11 Electronic records; Electronic Signatures • Guidance for Industry, Part 11 Electronic records; Electronic Signatures – Scope & Application • Guidance for Industry Computerized Systems Used in Clinical Investigations • EudraLex Volume 4 Annex 11 - Computerised systems • MHRA GMP Data Integrity Definitions and Guidance for Industry March 2015 • Data Integrity and Compliance With cGMP Guidance for Industry • Guidance on good data and record management practices • MHRA GxP Data Integrity Definitions and Guidance for Industry • Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
  • 21.
    Our value proposition 19| © 2016 pi pi | contact@3-14.com | www.3-14.com pi is the strategic partner of choice to some of the world’s leading life science companies. We offer our clients unique expertise and strategic consultancy of the highest quality. We dedicate ourselves to bringing excellence to the life sciences industry. We’ve grown by learning how to be better. Better resourced to focus our faculty of consultants’ singular experience and knowledge. Better managed to share their depth of understanding. Better prepared to challenge orthodox thinking. And better able to redefine accepted best practice. To accept no other standard than excellence. Connect with us on LinkedInVisit our website Follow us on Twitter

Editor's Notes

  • #4 Despite the presence of GMP regulations with respect to electronic systems