Data Integrity 101

Data Integrity 101
ONE QUALITY SOLUTIONS LTD.
19 MAY 2023
www.1qualitysolutions.com
ONE QUALITY SOLUTIONS LTD I WWW.1QUALITYSOLUTIONS.COM 1

Instruction for the Audience
 Your microphone will remain mute. Please unmute during discussion or Q & A
and then mute again.
 Post your questions and comments in the chat box.
 Participate in discussion.
 Share your experience and ideas.
One Quality Solutions Ltd I www.1qualitysolutions.com 2

Disclaimer
 This webinar presentation is the property of One Quality Solutions Ltd.
 The contents of this presentation cannot be changed or modified in any way.
 One Quality Solutions Ltd. is the sole owner of all the intellectual property rights related to this
presentation.
 This presentation can be shared with others or used for training purposes, provided that credit
is given to One Quality Solutions Ltd.
 The information provided in these slides is general in nature and cannot be regarded as
applicable for assessment of specific Data Integrity issue. In order to evaluate a specific Data
Integrity issue, it is necessary to evaluate relevant data.
 Users are responsible to use current guideline checking relevant websites.

Know the Speakers
Mohammed Raihan Chowdhury
Head of Quality Systems and Services
One Quality Solutions Ltd.
Ex-Data Integrity Lead of Novartis
Bangladesh
Sharmin Afroz
Sr. Asst. Manager, Product Development-ARD
Data Integrity Expert of Laboratory Instrument
Radiant Pharmaceuticals Ltd.
Bangladesh

Agenda
1. Introduction to Data Integrity
Key Definitions
What is Data Integrity?
Why it is important?
2. ALCOA+ Principles
History of ALCOA+
ALCOA+ and ALCOA++
3. Document Control
Example observation from Warning Letter
How to implement document control?
4. User Access Management
How to implement user access management?
5. Audit Trail Review
How to implement audit trail review?

Learning
Objective
 New employees or fresh graduate
will learn basic data integrity
 Experienced professionals can
refresh the data integrity
knowledge
 You will learn following:
ALCOA+ principles to ensure Data Integrity
Document control
Requirements of User Access and Audit Trail
review

Introduction to Data Integrity
 In 2020, a pharmaceutical company
received 17 customer complaints
regarding blue color fiber in tablets
 Investigation revealed that the blue color
fiber was identified during granulation by
Production and IPC personnel but not
recorded.
 Consequences: Recall of affected 3
batches, Rejection of 900 Kg raw material,
DI investigation for alleged persons.

Introduction to Data Integrity
What could be done differently to prevent
the Recalls and huge rejection of raw
material?
If the Production and IPC person ensured
the data recording without hiding, the recall
and rejection of raw material could be
prevented.

What is Data Integrity?
Data integrity refers to how reliable and trustworthy data is,
ensuring it remains complete, consistent, accurate, and
attributable throughout its lifecycle. Data should be legible,
contemporaneously recorded, and original.

Why it is important for Pharmaceutical Companies?
 After product release to market, you have two things: Batch Records and Retained Sample.
 If you receive complaints, first you need Batch Records for investigation.
 If the data in the batch records is not reliable or not available, you can not perform the
investigation.
 Data in the batch records confirms the quality of the product. If the data in the batch records is
not trustworthy or not available, you can not claim your product as quality product.
 Data integrity is a regulatory requirement, and failure to maintain it may result in regulatory
action, including suspension of a manufacturing license.

Data, Raw Data and Meta Data
Data: Data are defined as pieces of information and can exist in a variety of forms. Data
can be numbers, text, graphics, audio, pictures, or graphs. Data can be in electronic or
paper form, and can be presented as raw data, metadata, reports, and/or final results.
Raw data: Raw data may be on paper for data manually generated and recorded, such as
doctor's notes in a clinical trial. Or, raw data may be generated and stored electronically,
such as data produced by lab equipment and captured by a Laboratory Instrument
Management System (LIMS).
Metadata: Metadata is a set of data that describes and gives information about other
data, including the context to understand the data. This can be other data attributes such
as initials, signatures, or the date and time stamp associated with the capture of the data.
For example, 10 means nothing without kg next to it. 10 is the data. The descriptor kg is
the metadata. Another example of metadata is when a doctor records a patient's blood
pressure in a clinical trial, the blood pressure reading would be the data, while the
doctor's name and the date taken would be examples of metadata.

Origin of ALCOA+
 The ALCOA story goes back to last century: Stan Wollen, an FDA GLP inspector, was involved in training
fellow inspectors on new inspection techniques. He developed the acronym as a means of understanding
and evaluating GLP study data for data quality.
 As aluminium kitchen foil made by the ALCOA company was widely available, he used ALCOA as the basis
for the following five criteria that could be applied to any data set:
Attributable
Legible
Contemporaneous
Original
Accurate
 ALCOA data quality criteria have been taken by various regulatory guidance documents and have been
repurposed as a cornerstone of data integrity.

ALCOA Principles
A
L
C
O
A
Attributable: Information is captured that identifies the source of the data. Audit trails and
electronic signatures are examples.
Legible: Information is readable. Reports, tables, and listings must be legible.
Contemporaneous (same-time): Information is recorded at the time of data generation or event
observation.
Original: Data should be used or presented as it was created the first time.
Accurate: Data can be verified as correct via repeatable calculation, algorithm, or analysis.

ALCOA+ Principles
ALCOA+
Enduring: Data are preserved and retrievable during their lifetime according to the data type retention
period.
Complete: All data are present.
Available: Data are conveniently accessible at any time.
Consistent: Data are compatible, free from variation, and non-contradictory.

ALCOA++?
ALCOA++
The tenth and latest ALCOA criterion is “traceable,” from the EMA guidance on computerized systems
and electronic data in clinical trials.
Data should be traceable throughout the data life cycle. Time stamps traceable to a trusted time
source. Contemporaneous and consistent activities traced to trusted time stamps.
Metrological standards and equipment used traceable to international standards. Analytical reference
standards and other calibration standards obtained from a trusted source.
Ability to trace from an activity and the individual attributed to the work to their training records.

Document Control
In warning letter to Centurion Laboratories Private Limited (04 May 2019), following observation
mentioned:
On October 24, 2018, our investigator observed torn documents of stability study data, analytical
testing sheets, analysis calculations, and release forms that were placed into clear trash bags.
Stability study documents for three batches were salvaged from the trash and compared to the
official and approved records. Out-of-specification (OOS) results were among the data found,
however the official results were recorded as within specification. Additionally, it was observed
that blank stability study forms were prepared, pre-signed, and approved by the quality unit
before recording the test data.

Document Control
In warning letter to Aspire Pharmaceuticals, Inc. (22 Nov 2022), following observation mentioned:
Your quality control (QC) analysts routinely recorded raw data, such as sample weights, into
unofficial notebooks during release testing. Our inspection found an analyst maintained two
separate notebooks recording different sample weights for the same assay test. Your analyst
admitted to altering the sample weights in the approved notebook so that calculations based on
those results would meet your release specifications. At least batches of Aspire Daytime Mucus
and Sinus soft gel bulk product failed to meet your firm's internal assay specification for the active
ingredients. Your quality unit released these batches based on a review of inaccurate laboratory
data.

How to Implement Document Control?
 Only authorized person should have access to required document management system.
 Authorized personnel should issue the batch manufacturing and testing documents and all
other Forms. Record of issuance must be in place.
 Technical or procedural control should be in place, so end user will be unable to change any
content or page of the issued documents and Forms.
 Partially or fully executed batch manufacturing and testing documents and forms can not be
discarded in any way.
 Unused batch manufacturing and testing documents and forms must be returned to issuer.
 User must record data in the issued documents or forms. Unofficial documentation is not
acceptable.
 Documents issuer must perform reconciliation: issuance Vs archived/received from users

How to Implement Document Control?
 Documents must have identifier (title and identification) and version control.
 Document distribution must be controlled through-out the document life-cycle.
 Users must have access to current version of documents only.
 Discard of documents must be approved by QA after the expiry of documents.

User Access Management
In warning letter to Missouri Analytical Laboratories Inc (30 Sep 2021), following user access
related observation mentioned:
Your firm failed to exercise appropriate controls over computer or related systems to assure that
only authorized personnel institute changes in master production and control records, or other
records (21 CFR 211.68(b)).
Unique user accounts and privilege levels were not assigned to individual users for software, and
the Windows operating system. The analysts had access to delete and overwrite data. Our
investigators found approximately 36 deleted data files or folders in the recycle bin.

How to Implement User Access Management?
 Individual user access must be in place.
 For systems generating, amending or storing GXP data, shared logins must not be used.
 Different access level/ segregation of duties must be in place. Such as, analyst/operator, supervisor,
administrator.
 Non-admin users must not have access to critical aspects of the computerized system, e.g. system clocks,
enable/disable of audit trail etc.
 The system administrator account must not be available for routine use.
 Admin must be independent. (example: IT or QA)
 Creation of admin access must be approved by QA.

How to Implement User Access Management?
 User access privileges must be defined for all computerized equipment. No one should have delete
access except system admin.
 Access controls should be applied to both the operating system and application levels.
 Activities of admin including system management activities must be attributable in audit trail.
 Systems should be able to generate a list of users with actual access to the system, including user
identification and roles. The list should be used during periodic user reviews.
 Systems should be able to generate a list of successful and unsuccessful login attempts, including:
User identification
User access role
Date and time of the attempted login, either in local time or traceable to local time
Session length, in the case of successful logins
 Computerized systems should have an inactivity logout, which, either at the application or the operating
system level, logs out a user who has been inactive longer than a predefined time.

Audit Trail Review
In warning letter to Adamson Analytical Laboratories Inc. (17 Aug 2021), following audit trail
related observation mentioned:
From at least April 2018, until February 2021, the high performance liquid chromatography
(HPLC) and GC instruments were found to be operating in the absence of an activated audit trail
to record information about each analytical test, such as:
• Type of injection
• Date and time
• Identity of analyst
• Reason for action taken (e.g., modifying a record)

Audit Trail Review
In warning letter to Aspire Pharmaceuticals, Inc. (22 Nov 2022), following audit trail related
observation mentioned:
……your laboratory Data Reviewer did not review the electronic audit trail for your analytical
testing.

How to Implement Audit Trail Review?
 Audit trail must be enabled for the GxP relevant computerized system/ equipment and remain enabled at all
times.
 There must be evidence of enabling the audit trail. There must be a periodic verification to ensure that the
audit trail remains enabled throughout the data lifecycle.
 Users must not be able to disable the audit trail. Where a system administrator disable the audit trail, a record
of that action must be retained in audit trail.
 Where relevant audit trail functionality does not exist, an alternative control should be applied. For example,
defining the process in an SOP, and use of logbooks. Alternative controls should be proven to be effective.
 Audit trail review must be performed before batch release.
 Items for review in audit trail should be determined by risk assessment.
 System audit trail review should be performed periodically based on risk assessment.

Wrap Up

Key Takeaways
 Data Integrity is to keep the original
data ‘as is’ ensuring ALCOA+.
 Only authorized persons shall access
the documents/forms for issuance
which will be traceable.
 End users are not able to change
content/page of issued
documents/forms.
 All users must have individual user
access in computerized system.
 Audit trail review must be performed
before batch release.

Resources
1. MHRA GXP Data Integrity Guidance and Definitions, Revision.1
2. US FDA Data Integrity and Compliance With Drug CGMP-Questions and Answers, December
2018
3. Data Integrity (New August 2016) of European Medicines Agency- Guidance on good
manufacturing practice and good distribution practice: Questions and answers
4. PIC/S GUIDANCE: GOOD PRACTICES FOR DATA MANAGEMENT AND INTEGRITY IN
REGULATED GMP/GDP ENVIRONMENTS; 1 July 2021
5. WHO Guideline on Data Integrity
6. ISPE Records and Data Integrity Guide

Q & A
ASK YOUR QUESTIONS

Thank you
FOR ANY QUERY: info.1qualitysolutions@gmail.com

Data Integrity 101

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Similar to Data Integrity 101

Similar to Data Integrity 101 (20)

Recently uploaded

Recently uploaded (20)

Data Integrity 101