Pharma data integrity

““DATA INTEGRITYDATA INTEGRITY””DATA INTEGRITYDATA INTEGRITY
RECENT APPROACH BY REGULATORY
AGENCIES
By:
Girish A. Swami (M.Pharma, PGDIPR, PGDDRA)( , , )
Cell :+91-9881492626
E-Mail: pr.girish@gmail.com

““DATA INTEGRITYDATA INTEGRITY””
Key to GMP ComplianceKey to GMP Compliance
Girish A. Swami (M.Pharma, PGDIPR, PGDDRA)

Presentation OverviewPresentation Overview
• What is data Integrity ?What is data Integrity ?
• USFDA/WHO/ Global Environment
D t I t it G l E l• Data Integrity General Examples
• Basic data Integrity Expectations
• ALCOA Principles
• Manufacturers ExpectationsManufacturers Expectations
• Conclusion

“DATA INTEGRITY”
“Data integrity refers to the accuracy and
consistency of data generated during GxP”
“Data integrity is a prerequisite for the regulated
healthcare industry as decisions andy
assumptions on Product quality and Compliance
ith th li bl l t i twith the applicable regulatory requirements are
made based on data”

What is data IntegrityWhat is data Integrity
• The Extent to which all data are complete,p ,
consistent and accurate throughout the data
lifecycle
• From initial data generation and recording
through processing (including transformation orthrough processing (including transformation or
migration), use, retention, archiving, retrieval
and destruction.

Data integrity is the accuracy and
consistency of stored data, indicated
by an absence of any alteration in
data between two updates of a data
record Data integrity is imposedrecord. Data integrity is imposed
within a system at its design stage
through the use of standard rules
and procedures, and is maintained
through the use of error checking
and validation routinesand validation routines.

Data Integrity: what are we aiming for?Data Integrity: what are we aiming for?

Data integrity – Why a hot topics now ?
• Agencies expects that pharmaceutical companies should
retain complete and accurate records and all raw dataretain complete and accurate records and all raw data
and to make that available to inspectors
• The integrity of data generated by a regulated
pharmaceutical companies and laboratories matters
most, because properly recorded information is the basis
for manufacturers to assure product identity strengthfor manufacturers to assure product identity, strength,
purity, and safety and non-compliances found in the
integrity of data leads warning letters and a regulatoryg y g g y
action from the agencies

‘I lid t li bl‘Invalid or not reliable
data is a sign of poorg p
control on the operations
and equipment and
therefore the compan istherefore the company is
unable to ensure the
expected quality of
process’

Why so much interest now? Global
E iEnvironment

Regulatory Basis‐ GuidelinesRegulatory Basis Guidelines
• MHRA GMP Data Integrity Definitions andMHRA GMP Data Integrity Definitions and
Guidance for Industry - Published March
20152015
FDA’ A li ti I t it P li t• FDA’s Application Integrity Policy at
www.fda.gov
• Eudralex-Volume 4 Good manufacturingg
practice (GMP) Guidelines

Warning letters issued by FDA

Challenges noted by the agencies
• Non contemporaneous Recording: Failure to record activities atNon contemporaneous Recording: Failure to record activities at
the time when activity was performed. There is evidence that the
records were signed by company personnel when the person was
actually absent on that day.
• Document back-dating: Backdating stability test results to meet the
required commitments.
• Copy of existing data as new information: Test results from
previous batches were used to substitute testing for another batch or
acceptable test results were created without performing the test.
• Re-running samples to obtain better results: Multiple analyses of
assay were done with the same sample without adequate
justification and in some cases samples were tested unofficially or
as a trial analysis until desired test results obtainedas a trial analysis until desired test results obtained.
• Data fabrication and data discarding: Original raw data and
records were altered for e.g., by using of correction fluid org , y g
Manipulation of a poorly defined analytical procedure and
associated data analysis in order to obtain passing results.

While sources of data integrity violations include batch
records, equipments cleaning records and training
recordsrecords.
Around 80% of issues are quality control (QC) related,
with HPLC the number one cause
Chromatography:Chromatography:
# Deletion of data;
# Overwriting of data;
# Alt i f i t ti t# Altering of integration parameter;
# Continually testing until they arrive at the results they want.

Manufacturers ExpectationsManufacturers Expectations
– DESIGNING OF EFFECTIVE (QMS) -DESIGNING OF EFFECTIVE (QMS)
QUALITY MANAGEMENT SYSTEMS
– IMPLEMENTATION OF QMS ACROSS THE
ORGANIZATION

QUALITY SYSTEMS
A. ACHIEVEMENT OF QUALITY
Documentation System
T i i S tTraining System
Vendor Qualification System
Equipment Qualification System
V lid i SValidation System
B. CONSTANT MONITORING OF QUALITY
Review System
Deviation Management System
Environmental Monitoring System
Out Of Specification System
APQR System
Product Complaint Handling Systemg y
Voluntary Recall / Statutory Recall System

QUALITY SYSTEMS
C. MAINTENANCE AND IMPROVEMENT OF QUALITY
Self Inspection System
CAPA System
Change Control System
Root cause analysis systemy y
Quality Risk Management
Regular Management Review of Key Quality Parametersg g y y

REVIEW SYSTEM
• BMR BPR CDR are issued & filled documents are• BMR, BPR, CDR are issued & filled documents are
reviewed and managed by QA.
• All batch specific deviations are assessed and closed
before release of a batch.
• All the batches are released by QA, after verification of
batch specific BMR, QC results.

OUT OF SPECIFICATION SYSTEM (OOS)( )
Th d t lit t i t i l t dThe product quality at various stages is evaluated
against approved specifications.
The test results that do not meet established
specification are investigated through Out Ofp g g
Specification system to determine root cause and
remedial actions are implemented through CAPA
tsystem.

ANNUAL PRODUCT QUALITY REVIEW (APQR) SYSTEM:
APQR is performed to monitor the consistency in
manufacturing process and product quality. Trends of
QC test results and critical process parameters are
reviewed periodically.p y
This product specific review also includes outcome of
various quality systems such as deviations, change
control, internal audit, OOS, OOT, review of control
samples and stability data.samples and stability data.
Outcome of APQR is used for further enhancement of
the process and product quality.

QUALITY RISK MANAGEMENT
• Risk assessment ensures identification of hazards , analysis
and evaluation of associated risks.
• This procedure assesses the severity of impact, occurrence
and detection of a particular risk and assigns a risk priority
scorescore.
These are defined as follows:
• Severity of impact- A measure of the possible consequences
of a hazard
• Occurrence- The likelihood of hazard occurring
• Detection- The ability to determine the existence of hazard

QUALITY RISK ASSESSMENT
Steps followed for initiation of Risk Assessment:Steps followed for initiation of Risk Assessment:
• Identifying the risk areas
• Empowering a suitable team for risk assessment
• Review of risk assessment document for correctnessReview of risk assessment document for correctness
and completeness
Miti ti f th d i k• Mitigation of the assessed risk.
• Reassessment of the risk.

REGULATORY GUIDELINES
• Food and Drug Administration –FDAg
• Centre for Drug Evaluation and Research – CDER
• European Agency for the Evaluation of Medicinal
Products – EMEA
• PIC/S
• WHO
• Schedule - MSchedule M

DOCUMENTATION SYSTEM
QUALITY
STATEMENT
COMMITMENT
STATEMENT
QUALITY POLICIES
APPROACH /
THOUGHT PROCESSTHOUGHT PROCESS
EXECUTIONSTANDARD OPERATING
PROCEDURES
FORMS AND FORMATS
EXECUTION
PLAN

ConclusionConclusion
Four vital steps towards Data IntegrityFour vital steps towards Data Integrity
• Education and CommunicationEducation and Communication
• Detection and Mitigation of RisksDetection and Mitigation of Risks
• Technology and IT Systemsgy y
• Governance of DI

Education and CommunicationEducation and Communication
Culture and education is the foundation for a strong Data IntegrityCulture and education is the foundation for a strong Data Integrity
mindset
Education and consistent communication ensure:
•A common understanding
•Awareness of impact
•Ownership
•Leadership support

Detection and Mitigation of RisksDetection and Mitigation of Risks
Understand current risks

Technology and IT Systems

Governance of DIGovernance of DI
Establish governance structureEstablish governance structure

Thank YouThank You
Girish A. Swami
(M.Pharma, PGDIPR, PGDDRA)
Cell :+91-9881492626Cell :+91 9881492626
E-Mail: pr.girish@gmail.com

Pharma data integrity

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