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GLP Data Management and Integrity Audit Checklist

A comprehensive checklist for auditing data management practices and ensuring data integrity in GLP-regulated pharmaceutical laboratories, covering all aspects of data lifecycle from generation to archiving.

GLP Data Management and Integrity Audit Checklist

by: audit-now
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About This Checklist

Maintaining data integrity is paramount in Good Laboratory Practice (GLP) compliance for the pharmaceutical industry. This GLP Data Management and Integrity Audit Checklist is an essential tool for quality assurance professionals, data managers, and IT specialists to evaluate and ensure the robustness of data handling processes in GLP-regulated environments. By implementing this checklist, pharmaceutical organizations can strengthen their data governance, minimize the risk of data integrity breaches, and demonstrate compliance with regulatory expectations for data reliability and traceability.

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Industry

Healthcare

Standard

GLP - Good Laboratory Practice

Workspaces

Pharmaceutical Research and Development Laboratory

Occupations

Quality Assurance Specialist
Data Integrity Manager
IT Compliance Officer
Laboratory Information Management System (LIMS) Administrator
GLP Auditor
1
Is the data integrity maintained in compliance with ALCOA+ principles?
2
Describe the process for reviewing audit trails of electronic data systems.
3
On a scale of 1-5, how effective is the data lifecycle management process?
Min: 1
Target: 3
Max: 5
4
What is the current status of data security measures in place?
5
Is the laboratory compliant with current GLP regulations?
6
Outline the corrective action plan for any identified non-compliance.
7
Rate the training compliance of staff on GLP procedures from 1-5.
Min: 1
Target: 4
Max: 5
8
What was the date of the last compliance audit?
9
Is there an established data governance framework in the laboratory?
10
Describe the data quality assurance process implemented in the laboratory.
11
On a scale of 1-5, how effective are the data access controls in place?
Min: 1
Target: 4
Max: 5
12
How prepared is the laboratory for data incident response?
13
Is the electronic data system compliant with regulatory standards?
14
Outline the procedures for data backup within the electronic data systems.
15
How many times has the electronic data system experienced downtime in the last year?
Min: 0
Target: 3
Max: 100
16
When was the last validation of the electronic data system conducted?
17
Is sensitive data encrypted in accordance with industry standards?
18
Describe the access control measures in place for sensitive data.
19
What is the average response time (in hours) to data security incidents?
Min: 0
Target: 2
Max: 48
20
When was the last data security audit performed?

FAQs

The checklist covers areas such as data acquisition, processing, storage, archiving, security measures, audit trails, electronic signatures, and data backup and recovery processes.

Data integrity audits should be conducted at least annually, with more frequent checks recommended for critical systems or after significant changes to data management processes or technologies.

The audit should involve a cross-functional team including quality assurance personnel, IT specialists, data managers, and representatives from relevant laboratory departments to ensure a comprehensive review.

By regularly using this checklist, organizations can proactively identify and address data integrity issues, maintain comprehensive documentation of data management practices, and demonstrate a commitment to GLP principles, thus enhancing preparedness for regulatory inspections.

Yes, while the checklist has a strong focus on electronic data systems, it also includes elements relevant to paper-based records and hybrid systems to ensure comprehensive coverage of all data types in GLP environments.

Benefits of GLP Data Management and Integrity Audit Checklist

Ensures comprehensive assessment of data integrity practices

Helps identify and mitigate risks in data management processes

Facilitates compliance with GLP data integrity requirements

Supports the development of robust data governance strategies

Enhances the overall quality and reliability of laboratory data