pragmatic approach to achieve data integrity & compliance
TRANSCRIPT
Pragmatic Approach To Achieve
Data Integrity & Compliance
Presented by “Mukunth Venkatesan, CEO, Agaram Technologies
Mukunth Venkatesan started his career as a bio-medical instrumentation engineer.
He joined Agaram group 26 years back to lead the analytical instrumentation and R&D division for manufacturing HPLCs in India.
Mukunth moved on to establish a software development team for instrumentation. Once he cut his teeth in instrument software development, the next logical step was to start developing “Laboratory Informatics” software.
Agaram Technologies today is a well-established “Laboratory Informatics” player having implemented its Qualis© LIMS, Logilab ELN©, Logilab SDMS© and Qualis© DMS suite of products at a host of Pharmaceutical and Life Sciences laboratories across the globe.
CEO, Agaram Technologies
Mukunth Venkatesan
2
Available
Linking data to a source
along with metadata,
person & process
Legible
Data stored
electronically is
legible
Contemporaneous
System to record as &
when an activity is
performed with date &
time stamp
Original & True Copy
Original data along with
metadata verified &
signed by competent
person
Recalling ALCOA & What to Achieve
3
Accurate
Data captured directly
without human
intervention with cross
checking mechanism
4
Automation Architecture Model for Data Integrity Assurance
Audit trail of all activities
Server based date/time stamping of
Contemporaneous activities
Audit trail of client side activities
creation, modification, deletion,
renaming etc.
Automatic storage of original & meta
data generated in a controlled
environment (server)
Attributable to source (instrument & person)
Legible (electronic storage)
An environment for controlled access to
system or application
Attributable to source (instrument/software
& person)
Users should be able to continue to work
on data
Contemporaneous recording (LIMS, ELN)
Modify (method or reprocess or update) e.g.
CDS, Documents
Modified data to be automatically versioned
5
Basic Functional Requirements for Data Integrity
Review & approval
Check single source of truth
(Original /True copy)
cGMP data outcome (Result)
Should be taken from the server
data – Single source of Truth
6
Basic Functional Requirements for Data Integrity
How and where is original data created and what to
do with data?
• Data is created by users and instruments in local/network drives
• Automation should store a “True copy” in the server (controlled area)
Risk & Mitigation at Data Generation & Recording stage
7
How do you ensure that the data is complete, accurate and
traceable to meet ALCOA? Automation should ensure
• A (who, which instrument, why, what purpose
• L (Electronic copy should be legible & longevity)
• C (contemporaneous as & when created/modified)
• O (original copy to be saved and verifiable)
• A (Automatic capture without human intervention)
Is it possible to recreate, amend or delete
original data and metadata?
• Automation should help in identifying amendments & version data automatically
• “NO” possibility to delete or obscure data
8
How data is transferred to other locations or
systems for processing or storage?• Automation should help in download/restore of
data in a controlled manner for processing or storage
• Any change due to processing to be handled by automation system with version control
Risk & Mitigation at Data Generation & Recording stage
99
How is Meta data handled?
• Method used for processing to be identified as metadata for capture
• When no external metadata is available • Raw data should contain relevant metadata • Else manually record metadata
How is impact of data processing handled?
• Any change to data due to processing should always be captured by the automation system (version control)
Risk & Mitigation at Data Accessing & Processing stage
10
Does the person processing the data have the ability to
influence what data is reported?
• Person should not have any control over raw data generated
• Even if a person does trials, all such trials should be captured
independently along with version control
• Automation server should be “single source truth” with all
versions.
• Reporting of specific version of data should be a scientific and
informed decision.
Risk & Mitigation at Data Accessing & Processing stage
11
Risk & Mitigation of Completeness, Accuracy of reported data
Is data original (including the original data format) available
for checking?
• Always original format data should be available at server
• Accuracy of reported data can be cross checked based on
original data for data integrity
• Electronic integration eliminates manual intervention and
improves integrity AL
C
OA
12
Does the data reviewer have visibility and access to all data
generated & processed?
• Reviewer can check all versions of data generated from
single source of truth (server) without having to look at
disparate systems.
• Download and re-creation of output using the original
application helps in cross checking
Risk & Mitigation of Completeness, Accuracy of reported data
AL
C
OA
Prevention is better than
cure – both FDA and
MHRA recommend this
Approach
“Use of external devices or
system interfacing methods
that eliminate manual data
entries and human interaction
with the computerised
system”
Workshop will cover how to
achieve data integrity for:
• Instrument raw & meta data
(standalone & PC controlled)
• non-CFR compliant instruments
• Documents (MS-Office)
• Controlled blank form issuance
(e.g. cGMP record, data sheets, BMR,
Deviations etc.)Automation will be key to
achieve data integrity
Solutions designed to meet
ALCOA & 21 CFR Part 11
Pragmatic Approach for Data Integrity
www.agaramtech.com13
14
Instrument Raw & Meta data
Standalone & PC-Based Instruments
15
Instrument Data Capture Architecture
16
Data Lifecycle
Data Integrity Protected through Capture-Compliance-Risk Intelligence-Archival
Connect Capture Review Approve
17
Automated Raw Data Capture
Instrument Raw-data
Source
Capture Scheduler
Task
Upload Service
File Server Storage
FTP Service
Scheduler
Agent
Review Instrument Data
Print Report using LogiLAB PDF Printer
18
Human Readable data in PDF
Print Report in PDF
• Link raw-data & metadata using tags• Create user defined tags & hierarchy
Tags: Sample ID, Batch#, Test, Product CodeHierarchy
Product>Batch>Test>Instrument>ResultProject>Trial>Test>Instrument> Result
• Tags can be entered by users• Search data based on tags
Metadata tagging for
19
Standalone instruments – Mobile based tagging
• Use Mobile Device for
• Locking Instruments
• Setting Tags
• Viewing Data Captured
• Switching Instruments
• Confirm Data Captured
• View Data on the move
• Comply with data integrity
• Achieve Contemporaneous recording
20
21
Handling Non-CFR Compliant Instruments
Data Integrity & 21 CFR Part 11 Compliance
22
CFR Application Gateway
• Controlled access for non-compliant instrument software systems
• Publish applications through Gateway• Access applications based on rights• Audit Trial of User events• Automatic capture of Instrument files• Gateway controls desktop, apps,
folder & files including• Restricts
copy/paste/delete/rename/ modification
• Comply with 21 CFR part 11 and Data integrity guidelines
23
Human Generated Documents
MS-Office Documents and cGMP records
24
Documents & cGMP records
Protect applications like Excel, Word and any other application
• Application Access• Data modification
monitoring• Automated versioning• Audit trail for versioning• Deletion• Renaming
25
Fillable Form Issuance & Print Control
Controlled Documents, Form, filling, Issuance with Print Control
26
Fillable Documents Issuance
Manage Fillable forms• Creation• Editing• Review & Approval
Fillable forms• Request• Filling Meta data• Issue• Print control (Manual recording)• Electronic Recording
27
Automation Solution Options
Scientific Data Management System (SDMS) Electronic Lab Notebook (ELN)
Document Management System (DMS)
Electronic Review & Approval
Automatic data version control
Control over generated & processed data
System access control with audit trail
Instrument & Human generated data
Scientific Data Management System (SDMS)
28
Audit trail & Electronic Review
Contemporaneous recording with Data Versioning
Direct instrument to worksheet (no human interference)
Deploy in QC (Worksheet) & Production (BMR)
Template based data capture
Electronic Lab Notebook (ELN)
29
Print Control
PDF Document with Electronic signature
Controlled entry of cGMP records (batch#, Lot#)
Document Request & Issuance
Manage organisation wide
• Documents / Forms Preparation
• Review, Approval & Release
Electronic Document Management & Issuance control
30
31
Let’s Discuss!!!
Thank You!!!