This document provides an overview of FDA's guidance on data integrity and compliance with cGMP regulations. It discusses key concepts such as data reliability, risk-based approaches, and FDA's expectations around electronic records and electronic signatures. The document also addresses regulatory references to data handling, integrity and electronic systems in 21 CFR parts 210, 211 and 212.
Trends changed from Non compliance to RR --> Gap to RR --> Data Integrity --> DIB --> Smart Audit & Smart Data.
RR = Regulatory Requirements
DIB = Data Integrity Breach
Take a serious Note for Data Integrity whether you are small or big organization. Your Data is the Heart of your business. Regulatory bodies are highly conscious about such issues. For beginners in this path, my small note can help you a lot.
The document discusses FDA's expectations around data integrity and compliance with Good Manufacturing Practices (GMP). It provides clarification on key terms like data integrity, metadata, and audit trails. It also addresses FDA's expectations that firms implement strategies to manage data integrity risks in a flexible, risk-based manner. The document indicates that while electronic records and signatures are allowed, all CGMP data must be evaluated and maintained according to regulations. It concludes by answering questions to further clarify terminology.
This document discusses data integrity and its importance in the pharmaceutical industry. It defines data integrity as the extent to which all data is complete, consistent and accurate throughout its lifecycle. Regulatory agencies like the FDA and MHRA require data integrity to ensure patient safety. Lack of data integrity can result in warning letters or consent decrees from regulators. The document outlines principles like ALCOA+ to ensure data integrity. It discusses examples of data integrity issues found in warning letters and gives recommendations for proper implementation of data integrity controls and quality culture.
The document discusses data integrity and recent regulatory approaches. It defines data integrity as the completeness, consistency, and accuracy of data throughout its lifecycle. Regulatory agencies are increasingly focused on data integrity due to its importance in ensuring product quality and safety. Common data integrity issues found by agencies include fabricated, falsified, or missing records. Ensuring data integrity requires effective quality management systems, risk management, technology solutions, and governance.
Presentation on data integrity in Pharmaceutical IndustrySathish Vemula
Presentation on data integrity in Pharmaceutical Industry
Contents:
- Definition & Basics
- Criteria for integrity of laboratory data
- Regulatory Requirements
- Barriers to Complete Data
- Possible data integrity problems
- Previous observations
- FDA Warning Letters – 2013
- FDA Warning Letters – 2014
- FDA 483’s related to data integrity
- EU – Non compliance Reports
- WHO - Notice of Concern
- Summary of Data Integrity issues
- Consequences- Rebuilding Trust
- Conclusion
Data integrity, Pharmaceutical industry, Good Manufacturing Practice, GMP, Guidelines, Data management, DI and GMP Compliance, paper and electronic data, Archive and back up
Data integrity issues are regularly cited by global regulatory agencies in inspection reports. National cultures can influence compliance with data integrity standards due to differences in power distance, individualism, and time orientation. Regulators now specifically target data integrity during inspections and audit raw data to verify submitted information. Companies must consider cultural factors when ensuring global compliance and promote quality cultures through codes of conduct.
Data integrity - Regulatory Perspective and Challenges: santoshnarla
This document provides an agenda for a conference on ensuring product quality and patient safety. The agenda includes sessions on data integrity risk management, data integrity in clinical research, data quality management in clinical research, regulations impacting data integrity, creating a culture of quality for data integrity, data management perspectives and challenges for the pharmaceutical MSME sector in India, data integrity from an analytical laboratory perspective, an overview of data integrity non-conformances from regulators, data integrity as an essential part of quality, the regulatory perspective on data integrity and challenges, MHRA and US FDA requirements for data integrity in clinical studies, data integrity on the manufacturing floor, and other topics. Various experts from the pharmaceutical industry will speak in the different sessions.
Trends changed from Non compliance to RR --> Gap to RR --> Data Integrity --> DIB --> Smart Audit & Smart Data.
RR = Regulatory Requirements
DIB = Data Integrity Breach
Take a serious Note for Data Integrity whether you are small or big organization. Your Data is the Heart of your business. Regulatory bodies are highly conscious about such issues. For beginners in this path, my small note can help you a lot.
The document discusses FDA's expectations around data integrity and compliance with Good Manufacturing Practices (GMP). It provides clarification on key terms like data integrity, metadata, and audit trails. It also addresses FDA's expectations that firms implement strategies to manage data integrity risks in a flexible, risk-based manner. The document indicates that while electronic records and signatures are allowed, all CGMP data must be evaluated and maintained according to regulations. It concludes by answering questions to further clarify terminology.
This document discusses data integrity and its importance in the pharmaceutical industry. It defines data integrity as the extent to which all data is complete, consistent and accurate throughout its lifecycle. Regulatory agencies like the FDA and MHRA require data integrity to ensure patient safety. Lack of data integrity can result in warning letters or consent decrees from regulators. The document outlines principles like ALCOA+ to ensure data integrity. It discusses examples of data integrity issues found in warning letters and gives recommendations for proper implementation of data integrity controls and quality culture.
The document discusses data integrity and recent regulatory approaches. It defines data integrity as the completeness, consistency, and accuracy of data throughout its lifecycle. Regulatory agencies are increasingly focused on data integrity due to its importance in ensuring product quality and safety. Common data integrity issues found by agencies include fabricated, falsified, or missing records. Ensuring data integrity requires effective quality management systems, risk management, technology solutions, and governance.
Presentation on data integrity in Pharmaceutical IndustrySathish Vemula
Presentation on data integrity in Pharmaceutical Industry
Contents:
- Definition & Basics
- Criteria for integrity of laboratory data
- Regulatory Requirements
- Barriers to Complete Data
- Possible data integrity problems
- Previous observations
- FDA Warning Letters – 2013
- FDA Warning Letters – 2014
- FDA 483’s related to data integrity
- EU – Non compliance Reports
- WHO - Notice of Concern
- Summary of Data Integrity issues
- Consequences- Rebuilding Trust
- Conclusion
Data integrity, Pharmaceutical industry, Good Manufacturing Practice, GMP, Guidelines, Data management, DI and GMP Compliance, paper and electronic data, Archive and back up
Data integrity issues are regularly cited by global regulatory agencies in inspection reports. National cultures can influence compliance with data integrity standards due to differences in power distance, individualism, and time orientation. Regulators now specifically target data integrity during inspections and audit raw data to verify submitted information. Companies must consider cultural factors when ensuring global compliance and promote quality cultures through codes of conduct.
Data integrity - Regulatory Perspective and Challenges: santoshnarla
This document provides an agenda for a conference on ensuring product quality and patient safety. The agenda includes sessions on data integrity risk management, data integrity in clinical research, data quality management in clinical research, regulations impacting data integrity, creating a culture of quality for data integrity, data management perspectives and challenges for the pharmaceutical MSME sector in India, data integrity from an analytical laboratory perspective, an overview of data integrity non-conformances from regulators, data integrity as an essential part of quality, the regulatory perspective on data integrity and challenges, MHRA and US FDA requirements for data integrity in clinical studies, data integrity on the manufacturing floor, and other topics. Various experts from the pharmaceutical industry will speak in the different sessions.
CCK Discussion Forum held at ICCBS, University of Karachi, attended by over hundred of registered experienced pharmaceutical professionals participants belonging from dozen of pharmaceutical manufacturing facilities
FDA Data Integrity Issues - DMS hot fixesVidyasagar P
The document discusses data integrity, including popular causes of integrity issues, consequences, and fixes related to document management systems. It provides definitions of data integrity and discusses regulatory requirements around integrity from agencies like the FDA. Specifically, it summarizes the FDA's 21 CFR Part 11 regulation, which considers electronic records equivalent to paper if certain controls are in place. It also discusses application integrity policies and concludes that ensuring data integrity is important to rebuild regulatory trust if issues are found.
Data integrity is assuming greater importance in current Good Manufacturing Practices in FDA regulated industry with increased emphasis by other regulatory agencies like the EMA. Data integrity and security infractions are not only 21 Code of Federal Regulations (CFR) Part 11 issues but also severe CGMP violations. As FDA increases its focus on data integrity and reliability, inspectors are examining data based on multiple regulations and standards including CGMP, Good Laboratory Practices (GLP), Good Clinical Practices (GCP) and the Application Integrity Policy (AIP) in addition to FDA-recognized consensus standards.
This presentation discusses data integrity regulations and enforcement trends that have led to increased scrutiny of pharmaceutical laboratories by inspectors.
The document discusses regulatory guidance and enforcement actions around data integrity and management from USFDA, MHRA, and other agencies. It notes deficiencies seen such as shared passwords and lack of audit trails. It provides background on regulations and guidance documents around electronic records and data integrity. It discusses inspections and warning letters issued to various companies regarding data integrity issues. The document aims to help readers understand regulatory expectations around data integrity and management.
This document discusses data integrity in pharmaceutical quality systems. It defines data and explains its importance in decision making and continual improvement. It notes that the FDA and EMA have issued warning letters and non-compliance reports for data integrity issues. Examples are provided of warning letters issued to two companies for violations like unauthorized data manipulation, lack of audit trails, and insufficient investigations. The causes of data integrity breaches are discussed. It emphasizes establishing a culture of integrity, security protocols, and complying with cGMP guidelines. It provides details on how to properly manage system access, data storage, backups, and recording data according to ALCOA principles. The importance of audit trail software is also covered.
This presentation is based on the US FDA Workshop that I attended in Mumbai.
Pharmaceutical Industry is challenged for the Data Integrity. The reason for Data Integrity Fraud are obvious, but are overlooked. The importance of the genuine data must be accepted from the patient safety angle. There has to be a sincere attempt from the Top Management to eliminate this problem. It is trust that needs to be developed and maintained.
Data Integrity in a GxP-regulated Environment - Pauwels Consulting AcademyPauwels Consulting
On Tuesday, December 6, 2016, our colleague Angelo Rossi, Senior Regulatory Compliance Consultant, gave an interesting presentation about “Data Integrity in a GxP-regulated Environment” at the Brussels Office of Pauwels Consulting in Diegem.
In his presentation, Angelo covered definitions and concepts of data integrity, the change in regulatory focus, lessons learned from recent FDA warning letters, importants highlights of regulations and guidelines. Angelo also presented a practical example of data integrity for a computerized system.
Please contact us at contact@pauwelsconsulting.com or +32 9 324 70 80 if you have any further questions regarding our consulting services in this area.
The document discusses data integrity and provides guidance on ensuring data integrity through the ALCOA principles of Attributable, Legible, Contemporaneous, Original, and Accurate. It defines each of the ALCOA principles and provides examples of their application. Common data integrity issues found by the FDA during inspections are also summarized, including data manipulation, multiple sample runs, backdated documentation, unauthorized data access, logbook recording issues, and others.
Data integrity is critical throughout the CGMP data life cycle, including in the creation, modification, processing, maintenance, archival, retrieval, transmission, and disposition of data after the record’s retention period ends. It would be helpful for data management.
Data Integrity Issues in Pharmaceutical CompaniesPiyush Tripathi
Data integrity refers to maintaining and assuring the accuracy and consistency of data over its entire life-cycle, and is a critical aspect to the design, implementation and usage of any system which stores, processes, or retrieves data.
Data Integrity; Ensuring GMP Six Systems Compliance Pharma TrainingMarcep Inc.
This document outlines a two-day workshop on data integrity compliance to meet regulatory standards. The workshop will cover data integrity requirements from the FDA, EU, and other regulators; challenges in ensuring data integrity across paper, hybrid, and electronic systems; best practices for data generation, recording, transformation and reporting; and conducting risk assessments and monitoring metrics to ensure ongoing data integrity. Attendees will learn how to strengthen internal audits and compliance across their quality systems, facilities, materials management, and other areas to meet data integrity expectations.
This presentation is compiled by Drug Regulations, a nonprofit organization that provides online pharmaceutical resources. It discusses FDA guidance on data integrity and compliance with cGMP regulations. The guidance clarifies FDA's expectations around the creation and handling of data to ensure its reliability and accuracy according to cGMP standards.
Data integrity is a Fundamental in a pharmaceutical quality system. It ensures that medicines are of required quality. This presentation is based on MHRA Guidance and provides MHRA expectations. Guidance complements existing EU GMP relating to active substances and dosage forms. This guidance should be d in conjunction with national medicines legislation and the GMP standards published in Eudralex volume 4.
- The document discusses data integrity, which refers to maintaining accurate and consistent data over its entire lifecycle. This is important for the regulated healthcare industry as quality decisions are based on data.
- The FDA uses the ALCOA criteria (Attributable, Legible, Contemporaneous, Original, Accurate) to define expectations for electronic data. Regulatory agencies now focus heavily on data integrity due to instances of fabricated documents and errors.
- Common data integrity issues found by agencies include non-contemporaneous recording, backdating records, re-running samples until desired results are obtained, and data fabrication. Ensuring data integrity helps prevent regulatory actions like warning letters or import bans against companies.
This document discusses regulatory requirements and previous observations related to data integrity issues. It outlines criteria for integrity of laboratory data according to regulations. It also provides examples of possible data integrity problems that have been observed by regulators, such as altering raw data, manipulating test procedures to obtain passing results, and recording lab activities before they occur. FDA warning letters from 2013 are referenced that identified specific failures to record quality activities at the time they were performed.
This document discusses data integrity in the pharmaceutical industry. It emphasizes that data must be of known and documented quality, representative, comparable, complete, and defensible for its intended purpose. Regulations like 21CFR 58.130(e) establish standards for data quality. Maintaining integrity can be complex due to human factors like incentives, justifications, and opportunities that may compromise integrity over time. Thorough training, a culture of open reporting, and root cause analysis of issues are important to ensure integrity. Verification of data governance is also crucial throughout the supply chain.
This document discusses data integrity expectations from regulatory agencies like the TGA. It defines data integrity as ensuring data is complete, consistent and accurate throughout its lifecycle. Recent global cases of data integrity issues at drug manufacturers are presented, involving falsification of records, deletion of lab data, and lack of controls around electronic data changes. The ALCOA principles for attributable, legible, contemporaneous, original and accurate data are described. TGA expectations include manufacturers understanding their vulnerabilities, assessing data integrity risks, designing systems to prevent issues, training staff, and having ongoing review systems. Conclusions state existing quality systems should ensure data integrity and traceability, and manufacturers are responsible for preventing and detecting integrity issues.
Quick Overview: Pharmaceutical Data IntegrityPeter Dellva
Brief overview of the most important aspects of pharmaceutical data integrity. Slideshare includes pharmaceutical and biopharmaceutical industry key resources.
21CFR regulations & its applicability in the industry and FDA perspective on the same and FDA check points on 21CFR regulations during their inspection.
CCK Discussion Forum held at ICCBS, University of Karachi, attended by over hundred of registered experienced pharmaceutical professionals participants belonging from dozen of pharmaceutical manufacturing facilities
FDA Data Integrity Issues - DMS hot fixesVidyasagar P
The document discusses data integrity, including popular causes of integrity issues, consequences, and fixes related to document management systems. It provides definitions of data integrity and discusses regulatory requirements around integrity from agencies like the FDA. Specifically, it summarizes the FDA's 21 CFR Part 11 regulation, which considers electronic records equivalent to paper if certain controls are in place. It also discusses application integrity policies and concludes that ensuring data integrity is important to rebuild regulatory trust if issues are found.
Data integrity is assuming greater importance in current Good Manufacturing Practices in FDA regulated industry with increased emphasis by other regulatory agencies like the EMA. Data integrity and security infractions are not only 21 Code of Federal Regulations (CFR) Part 11 issues but also severe CGMP violations. As FDA increases its focus on data integrity and reliability, inspectors are examining data based on multiple regulations and standards including CGMP, Good Laboratory Practices (GLP), Good Clinical Practices (GCP) and the Application Integrity Policy (AIP) in addition to FDA-recognized consensus standards.
This presentation discusses data integrity regulations and enforcement trends that have led to increased scrutiny of pharmaceutical laboratories by inspectors.
The document discusses regulatory guidance and enforcement actions around data integrity and management from USFDA, MHRA, and other agencies. It notes deficiencies seen such as shared passwords and lack of audit trails. It provides background on regulations and guidance documents around electronic records and data integrity. It discusses inspections and warning letters issued to various companies regarding data integrity issues. The document aims to help readers understand regulatory expectations around data integrity and management.
This document discusses data integrity in pharmaceutical quality systems. It defines data and explains its importance in decision making and continual improvement. It notes that the FDA and EMA have issued warning letters and non-compliance reports for data integrity issues. Examples are provided of warning letters issued to two companies for violations like unauthorized data manipulation, lack of audit trails, and insufficient investigations. The causes of data integrity breaches are discussed. It emphasizes establishing a culture of integrity, security protocols, and complying with cGMP guidelines. It provides details on how to properly manage system access, data storage, backups, and recording data according to ALCOA principles. The importance of audit trail software is also covered.
This presentation is based on the US FDA Workshop that I attended in Mumbai.
Pharmaceutical Industry is challenged for the Data Integrity. The reason for Data Integrity Fraud are obvious, but are overlooked. The importance of the genuine data must be accepted from the patient safety angle. There has to be a sincere attempt from the Top Management to eliminate this problem. It is trust that needs to be developed and maintained.
Data Integrity in a GxP-regulated Environment - Pauwels Consulting AcademyPauwels Consulting
On Tuesday, December 6, 2016, our colleague Angelo Rossi, Senior Regulatory Compliance Consultant, gave an interesting presentation about “Data Integrity in a GxP-regulated Environment” at the Brussels Office of Pauwels Consulting in Diegem.
In his presentation, Angelo covered definitions and concepts of data integrity, the change in regulatory focus, lessons learned from recent FDA warning letters, importants highlights of regulations and guidelines. Angelo also presented a practical example of data integrity for a computerized system.
Please contact us at contact@pauwelsconsulting.com or +32 9 324 70 80 if you have any further questions regarding our consulting services in this area.
The document discusses data integrity and provides guidance on ensuring data integrity through the ALCOA principles of Attributable, Legible, Contemporaneous, Original, and Accurate. It defines each of the ALCOA principles and provides examples of their application. Common data integrity issues found by the FDA during inspections are also summarized, including data manipulation, multiple sample runs, backdated documentation, unauthorized data access, logbook recording issues, and others.
Data integrity is critical throughout the CGMP data life cycle, including in the creation, modification, processing, maintenance, archival, retrieval, transmission, and disposition of data after the record’s retention period ends. It would be helpful for data management.
Data Integrity Issues in Pharmaceutical CompaniesPiyush Tripathi
Data integrity refers to maintaining and assuring the accuracy and consistency of data over its entire life-cycle, and is a critical aspect to the design, implementation and usage of any system which stores, processes, or retrieves data.
Data Integrity; Ensuring GMP Six Systems Compliance Pharma TrainingMarcep Inc.
This document outlines a two-day workshop on data integrity compliance to meet regulatory standards. The workshop will cover data integrity requirements from the FDA, EU, and other regulators; challenges in ensuring data integrity across paper, hybrid, and electronic systems; best practices for data generation, recording, transformation and reporting; and conducting risk assessments and monitoring metrics to ensure ongoing data integrity. Attendees will learn how to strengthen internal audits and compliance across their quality systems, facilities, materials management, and other areas to meet data integrity expectations.
This presentation is compiled by Drug Regulations, a nonprofit organization that provides online pharmaceutical resources. It discusses FDA guidance on data integrity and compliance with cGMP regulations. The guidance clarifies FDA's expectations around the creation and handling of data to ensure its reliability and accuracy according to cGMP standards.
Data integrity is a Fundamental in a pharmaceutical quality system. It ensures that medicines are of required quality. This presentation is based on MHRA Guidance and provides MHRA expectations. Guidance complements existing EU GMP relating to active substances and dosage forms. This guidance should be d in conjunction with national medicines legislation and the GMP standards published in Eudralex volume 4.
- The document discusses data integrity, which refers to maintaining accurate and consistent data over its entire lifecycle. This is important for the regulated healthcare industry as quality decisions are based on data.
- The FDA uses the ALCOA criteria (Attributable, Legible, Contemporaneous, Original, Accurate) to define expectations for electronic data. Regulatory agencies now focus heavily on data integrity due to instances of fabricated documents and errors.
- Common data integrity issues found by agencies include non-contemporaneous recording, backdating records, re-running samples until desired results are obtained, and data fabrication. Ensuring data integrity helps prevent regulatory actions like warning letters or import bans against companies.
This document discusses regulatory requirements and previous observations related to data integrity issues. It outlines criteria for integrity of laboratory data according to regulations. It also provides examples of possible data integrity problems that have been observed by regulators, such as altering raw data, manipulating test procedures to obtain passing results, and recording lab activities before they occur. FDA warning letters from 2013 are referenced that identified specific failures to record quality activities at the time they were performed.
This document discusses data integrity in the pharmaceutical industry. It emphasizes that data must be of known and documented quality, representative, comparable, complete, and defensible for its intended purpose. Regulations like 21CFR 58.130(e) establish standards for data quality. Maintaining integrity can be complex due to human factors like incentives, justifications, and opportunities that may compromise integrity over time. Thorough training, a culture of open reporting, and root cause analysis of issues are important to ensure integrity. Verification of data governance is also crucial throughout the supply chain.
This document discusses data integrity expectations from regulatory agencies like the TGA. It defines data integrity as ensuring data is complete, consistent and accurate throughout its lifecycle. Recent global cases of data integrity issues at drug manufacturers are presented, involving falsification of records, deletion of lab data, and lack of controls around electronic data changes. The ALCOA principles for attributable, legible, contemporaneous, original and accurate data are described. TGA expectations include manufacturers understanding their vulnerabilities, assessing data integrity risks, designing systems to prevent issues, training staff, and having ongoing review systems. Conclusions state existing quality systems should ensure data integrity and traceability, and manufacturers are responsible for preventing and detecting integrity issues.
Quick Overview: Pharmaceutical Data IntegrityPeter Dellva
Brief overview of the most important aspects of pharmaceutical data integrity. Slideshare includes pharmaceutical and biopharmaceutical industry key resources.
21CFR regulations & its applicability in the industry and FDA perspective on the same and FDA check points on 21CFR regulations during their inspection.
The need for a transition from a traditional maintenance practices to a dependency around data that uses analytics to alter maintenance practices has the potential to add value while creating new rewards and challenges to the utility world.
This document outlines the agenda for a conference on obtaining FDA approval for AI-based medical devices. The agenda includes presentations on paving the path for FDA approval of AI devices, an open Q&A session with the FDA's Digital Health Center of Excellence, how to align product development with FDA regulations for AI, best pre-submission practices, and an update on the 510(k) program. There will also be breaks and a summary session. The presentations will provide guidance on navigating the FDA approval process for AI medical devices and obtaining feedback prior to formal submissions.
Xybion Webinar - Rumors, Risks and Realities of spreadsheet validationXybion Corporation
The document provides an overview of a webinar on spreadsheet validation presented by Xybion Corporation. The webinar discusses common rumors around spreadsheet validation requirements, clarifies the regulatory realities, and outlines the risks of not properly validating spreadsheets used for regulated activities. The presenter explains that while spreadsheets are widely used, regulations still require their validation for intended use to ensure business continuity and data accuracy. Not validating poses risks of regulatory compliance issues. Available software can help address typical spreadsheet deficiencies in security and audit trails.
Review of Quality Control Record and Analytical Data by Dr. A. AmsavelDr. Amsavel A
Review of Quality Control Record and Analytical Data
Objective and Requirement for Analytical data review
Role of Analyst and reviewer,
Procedure and checklist for review of records/data
Review of traceable /associated documents
Review of calibration, Reference standard record, sampling reports,
Review of Audit trail
Role of Analyst & Reviewer
Review of chromatograms& audit trail,
Data Integrity & Good Record Practice
FDA Citations
Data Integrity in pharmaceutical laboratories is a must, the attached ppt shall help the QC members to understand and develop an integral analytical culture
Waters: Reviewing Audit Trail Information in Empower Chromatography Data Soft...Waters Corporation
This presentation provides an overview of how to review audit trail information within Waters Empower Chromatography Data Software. (From Inform 2016, our annual software users meeting)
A Real-Time Information System For Multivariate Statistical Process ControlAngie Miller
This document describes the design and implementation of a real-time multivariate process control system that uses principal component analysis models to monitor a manufacturing process in real-time. The system analyzes process data, detects errors, and presents contributing factors through a graphical user interface for operators and engineers. It is intended to help identify improvement opportunities by better utilizing available process data and information within temporal bounds important for process control.
Scalable and Repeatable Machine Learning pipelines: A key requirement for you...All Things Open
This document discusses how Pachyderm helps data science teams overcome obstacles to effective data science by providing reproducibility, version control for data, and data provenance. It provides examples of how Pachyderm is used by AgBiome and General Fusion to build scalable data pipelines and comply with regulations like GDPR by enabling easy editing of data without disruption.
3 D's of test data management managing effectively the underlying challenges...Ajeet Singh, PMP, CSM
The document discusses the key challenges in managing the three processes - dispensation, deployment, and depersonalization (3Ds) of test data from production environments. These include identifying correct data owners for approval, assessing available space in test environments, maintaining data integrity, selecting relevant data for testing, complying with privacy policies during depersonalization, and ensuring coordination between various support groups. Proactive management of the interdependent 3D processes is important to avoid delays in testing schedules and cost overruns.
Use Custom Metadata Types for Easy ALM & Compliance for Your Custom AppsSalesforce Developers
The document discusses custom metadata types, which allow organizations to easily manage application-level metadata (ALM) and comply with IT controls. Custom metadata types can be deployed and retrieved via metadata APIs and packages, providing traceability of changes. They help reduce errors by validating changes before deployment to production and tracking all metadata changes in a single transaction.
Next-Generation Bioprocessing Monitoring to Enable Smart Data Management and ...Merck Life Sciences
Watch this webinar here: https://bit.ly/2ZpV3GU
Biopharmaceutical processes are complex and highly variable in nature. This can result in inconsistent and unpredictable process outcomes. To manage complexity and better understand causes of variability, in-depth knowledge and thorough understanding of the process is critical. Bio4C™ ProcessPad provides the data integration, analysis and sharing across the manufacturing network and end-to-end data management throughout the process lifecycle required for continued process verification, reporting, and analytics.
Bio4C™ ProcessPad is a data visualization, analytics, and process monitoring platform that enables bioprocess lifecycle management, reporting, investigations, and continued process verification (CPV). Intelligently combining process data from batches, Enterprise Resource Planning (ERP), Manufacturing Execution System (MES), Laboratory Information Management System (LIMS), Historian, process equipment, and manual sources into a single, validated data source, Bio4C™ ProcessPad ensures data is current, complete, and contextual throughout the product lifecycle.
In this webinar, you will learn:
• Introduction to Next Generation BioContinuum™ Digital Platform and Bio4C™ Software Suite
• Overview of Bioprocess lifecycle and present biomanufacturing data management challenges
• Introduction to the Bio4C™ ProcessPad digital platform and its modules and features
• Benefits of Bio4C™ ProcessPad in investigations, process monitoring, continued process verification (CPV) and CDMO operations
Next-Generation Bioprocessing Monitoring to Enable Smart Data Management and ...MilliporeSigma
Watch this webinar here: https://bit.ly/2ZpV3GU
Biopharmaceutical processes are complex and highly variable in nature. This can result in inconsistent and unpredictable process outcomes. To manage complexity and better understand causes of variability, in-depth knowledge and thorough understanding of the process is critical. Bio4C™ ProcessPad provides the data integration, analysis and sharing across the manufacturing network and end-to-end data management throughout the process lifecycle required for continued process verification, reporting, and analytics.
Bio4C™ ProcessPad is a data visualization, analytics, and process monitoring platform that enables bioprocess lifecycle management, reporting, investigations, and continued process verification (CPV). Intelligently combining process data from batches, Enterprise Resource Planning (ERP), Manufacturing Execution System (MES), Laboratory Information Management System (LIMS), Historian, process equipment, and manual sources into a single, validated data source, Bio4C™ ProcessPad ensures data is current, complete, and contextual throughout the product lifecycle.
In this webinar, you will learn:
• Introduction to Next Generation BioContinuum™ Digital Platform and Bio4C™ Software Suite
• Overview of Bioprocess lifecycle and present biomanufacturing data management challenges
• Introduction to the Bio4C™ ProcessPad digital platform and its modules and features
• Benefits of Bio4C™ ProcessPad in investigations, process monitoring, continued process verification (CPV) and CDMO operations
Study start up activities in clinical data managementsoumyapottola
Study start-up (SSU) is so much more than a one-time document management exercise. It’s a global, strategic operation that can get new drugs approved faster – and it’s ripe for innovation – from Site Selection to Site Activation and Site Training.
Many SSU tech solutions deployed by sponsors don’t deliver the results promised because they add burden without benefits to clinical research sites. The result? Site staff simply avoid using them.
When that happens, document exchange and tracking falls back to paper, email and Excel formats – with CRAs holding the processes together. The tools that were supposed to solve a problem become part of the problem – and consume preThe implementation and conduct of a study can be a complex process that involves a
team from various disciplines and multiple steps that are dependent on one another. This
document offers guidance for navigating the study start-up processcious clinical trial budget.
A successful clinical study start-up is a crucial first step and an important factor for the overall success of the trial. For this reason, SCRO has experienced study start-up teams, offering customized services depending on your needs, whether it be fuWhile the definition varies across companies, study startup typically includes the process of identifying and qualifying sites, collecting essential documents at the study and site level, and submitting these documents for ethics approval. Successful study startup requires coordination between sites, sponsors, and contract research organizations (CROs) to achieve critical milestones in a compliant manner.ll-service or single activities.
How to achieve better time management in EDC start up
Clinical data management requires strict time management processes, especially in study start up within an electronic data capture (EDC) system. Three steps that clinical data management teams can take to outline the planning and executing of each task that needs to be considered are as follows:
Make a List: Create a daily or weekly task list and schedule when each task will be completed. This strategy will assist you in maintaining focus and staying organized.
Set realist goals: Be realistic about what you can finish in the amount of time you have. When setting unrealistic goals, failure is almost certain to follow.
Explore time-saving techniques: Examples of techniques that could help save time include grouping similar tasks together or using a timer to stay focused.
To help get started, here is a list of EDC considerations for Study Start-Up deadlines:
Protocol finalization and study enrollment
Split go-live considerations
eCRF Specification meetings (this will ensure proper collaboration and minimize any back-and-forth communication)
EDC add-on modules (which will be required and need validation?)
ePRO/eCOA used with licensed questionnaires.
IRB requirements for add-on modules (eConsent/ePRO)
With data flowing from different mediums (RDBMS, SocialMedium, Legacy files),one of the efficacious mean for processing huge data is through Big Data, where Data Lake plays a critical role for storing Structured/Semi Structured and Unstructured Data. I have tried to give you a glimpse of , how testing of Data Lake is generally performed, what are the different types and approaches we follow.
The document discusses GE's Industrial Data Lake Platform. It notes that industrial data is growing rapidly in terms of both volume and variety. However, most industrial data is not analyzed due to challenges in gathering, preparing, and analyzing the data. GE's Industrial Data Lake is presented as a solution to address these challenges. It provides a single place to access both real-time and historical industrial data of all types. It also allows for more flexible and agile data models compared to traditional data warehouses. The data lake is optimized for industrial workloads and includes features like fast data ingestion, high performance analytics, and data governance capabilities.
In the last year or so the FDA and the EMA have issued new guidance/ draft guidance on "Process Validation".These align process validation activities with a product lifecycle concept and the International Conference on Harmonisation (ICH) guidances for industry, Q8(R2) Pharmaceutical Development, Q9 Quality Risk Management, and Q10 Pharmaceutical Quality System. The earlier guidelines were developed before the elaboration of the new ICH guidelines.With these new guidelines, additional opportunities are available to verify the control of the process by alternative means to the manufacture of traditional process validation batches. The main objective of process validation remains that a process design yields a product meeting its pre-defined quality criteria. ICH Q8, Q9 and Q10 provide a structured way to define product critical quality attributes, design space, the manufacturing process and the control strategy. ICH Q8 refers to an ‘enhanced’ approach to pharmaceutical development which includes an alternative to the traditional process validation.
Continuous process verification [see definition in ICH Q8(R2) glossary] can be utilised in process validation protocols for the initial commercial production and for manufacturing process changes for the continual improvement throughout the remainder of the product lifecycle.
There is now a new paradigm in process validation. This presentation has been prepared from material available from FDA , EMA and ICH for beginners to have an overview of the new paradigm.
Geoscientific Data Management PrinciplesNigelLaubsch
The document discusses 18 principles for best practice in geoscientific data management. These principles include having a centralized location for data storage, standardized legends and data models, direct digital data transfer, digital sample submission, automated assay loading, data approval workflows, and embedding IT specialists within exploration groups. Following these principles can help improve data quality, reduce errors, and maximize the value obtained from analysis of complete geological datasets.
8 Surprising Reasons To Meditate 40 Minutes A Day That Can Change Your Life.pptxHolistified Wellness
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Data integrity cGMP requirements
1. Copyright, GMP Scientific, Inc. 2018
Data Integrity and Compliance With GMP
FDA Guidance – April 2018
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2. Copyright, GMP Scientific, Inc. 2018
Legal Notice
The information displayed on these presentation slides is for the sole private use of
the attendees of the seminar at which these slides were presented. GMP Scientific,
Inc. (“GMP Scientific”) makes no representations or warranties of any kind, either
express or implied, with respect to the contents and information presented. All
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GMP Scientific protected under copyright and other intellectual property laws.
These presentation slides may not be displayed, distributed, reproduced, modified,
transmitted, used or reused, without the express written permission of GMP
Scientific.
3. Introduction
• Introduce the subject of the presentation.
• State how presentation will benefit audience.
• State presenter’s level of expertise in subject.
• Tip: Click and scroll in the notes pane below to see more instructions, or
to add your own speaker notes.
4. Introduction
• Clarify role of Data Integrity in cGMP
• Presents Agency’s current thinking on creation and handling of data
• Non-binding
• Relates to CFR 210, 211 and 212
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5. FDA Expectations
• FDA expects that data be reliable and accurate
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7. FDA Expectations
• CGMP regulations and guidance allow for flexible and risk-based
strategies to prevent and detect data integrity issues.
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8. Regulatory References
• Underlying premise in §§ 210.1 and 212.2 is that CGMP sets forth
minimum requirements.
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9. Regulatory References
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Exact & Complete
Inadvertent erasures
Loss
Alterations
§ 211.68
Backup data
10. Regulatory References
•§ 212.110(b) (requiring that data be
“stored to prevent deterioration or
loss”);
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11. Regulatory References
•“documented at the time of performance”
•“scientifically sound”
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12. Regulatory References
• “original records,” “true copies,” or other
•“accurate reproductions of the original
records”
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13. Regulatory References
•“complete information,”
•“complete data derived from all tests,”
•“complete record of all data,” and
•“complete records of all tests performed”
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14. Electronic Signatures
• Electronic signature and record-keeping requirements are laid out in 21
CFR part 11 and apply to certain records subject to records
requirements set forth in Agency regulations, including parts 210, 211,
and 212.
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15. Electronic Signatures
• For more information, see guidance for industry Part 11, Electronic
Records; Electronic Signatures — Scope and Application.
• The guidance outlines FDA’s current thinking regarding the narrow
scope and application of part 11 pending FDA’s reexamination of part 11
as it applies to all FDA-regulated products.
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20. Metadata
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Describes, Explains
Makes it easier to
Retrieve, Use or Manage Data
Structured Information
21. Question & Answers
b) What is Metadata?
• Metadata is the contextual information required to understand data.
• Metadata is often described as data about data. Metadata is structured
information that describes, explains, or otherwise makes it easier to
retrieve, use, or manage data.
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22. Question & Answers
b) What is Metadata?
• For example, the number “23” is meaningless without metadata, such
as an indication of the unit “mg.”
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23. Question & Answers
b) What is Metadata?
• Among other things, metadata for a particular piece of data could
include a date/time stamp for when the data were acquired, a user ID of
the person who conducted the test or analysis that generated the data,
the instrument ID used to acquire the data, audit trails, etc.
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24. Question & Answers
b) What is Metadata?
• Data should be maintained throughout the record’s retention period
with all associated metadata required to reconstruct the CGMP activity
(e.g., §§ 211.188 and 211.194).
• The relationships between data and their metadata should be preserved
in a secure and traceable manner.
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25. Question & Answers
c) What is an audit trail?
• For purposes of this guidance, an audit trail means a secure, computer-
generated, time-stamped electronic record that allows for
reconstruction of the course of events relating to the creation,
modification, or deletion of an electronic record.
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26. Question & Answers
c) What is an audit trail?
• Data should be maintained throughout the record’s retention period
with all associated metadata required to reconstruct the CGMP activity
(e.g., §§ 211.188 and 211.194).
• The relationships between data and their metadata should be preserved
in a secure and traceable manner.
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27. Question & Answers
c) What is an audit trail?
• An audit trail is a chronology of the “who, what, when, and why” of a
record. For example, the audit trail for a high performance liquid
chromatography (HPLC) run could include the user name, date/time of
the run, the integration parameters used, and details of a reprocessing,
if any, including change justification for the reprocessing.
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28. Question & Answers
c) What is an audit trail?
• Electronic audit trails include those that track creation, modification, or
deletion of data (such as processing parameters and results) and those
that track actions at the record or system level (such as attempts to
access the system or rename or delete a file).
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29. Question & Answers
c) What is an audit trail?
• CGMP-compliant record-keeping practices prevent data from being lost
or obscured (see §§ 211.160(a), 211.194, and 212.110(b)). Electronic
record-keeping systems, which include audit trails, can fulfill these
CGMP requirements.
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30. Question & Answers
d) How does FDA use the terms “static” and “dynamic” as they relate to
record formats?
• For the purposes of this guidance, static is used to indicate a fixed-data
document such as a paper record or an electronic image, and dynamic
means that the record format allows interaction between the user and
the record content
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31. Question & Answers
d) How does FDA use the terms “static” and “dynamic” as they relate to
record formats?
• For example, a dynamic chromatographic record may allow the user to
change the baseline and reprocess chromatographic data so that the
resulting peaks may appear smaller or larger. It also may allow the user
to modify formulas or entries in a spreadsheet used to compute test
results or other information such as calculated yield.
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32. Question & Answers
e) How does FDA use the term “backup” in § 211.68(b)?
• FDA uses the term backup in § 211.68(b) to refer to a true copy of the
original data that is maintained securely throughout the records
retention period (for example, § 211.180). The backup file should
contain the data (which includes associated metadata) and should be in
the original format or in a format compatible with the original format.
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33. Question & Answers
e) How does FDA use the term “backup” in § 211.68(b)?
• This should not be confused with backup copies that may be created
during normal computer use and temporarily maintained for disaster
recovery (e.g., in case of a computer crash or other interruption). Such
temporary backup copies would not satisfy the requirement in §
211.68(b) to maintain a backup file of data.
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34. Question & Answers
f) What are the “systems” in “computer or related systems” in § 211.68?
• The American National Standards Institute (ANSI) defines systems as
people, machines, and methods organized to accomplish a set of
specific functions.
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35. Question & Answers
f) What are the “systems” in “computer or related systems” in § 211.68?
• Computer or related systems can refer to computer hardware, software,
peripheral devices, networks, cloud infrastructure, operators, and
associated documents (e.g., user manuals and standard operating
procedures).
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36. Question & Answers
2. When is it permissible to exclude CGMP data from decision making?
• Any data created as part of a CGMP record must be evaluated by the
quality unit as part of release criteria (see §§ 211.22 and 212.70) and
maintained for CGMP purposes (e.g., § 211.180).
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37. Question & Answers
2. When is it permissible to exclude CGMP data from decision making?
• Electronic data generated to fulfill CGMP requirements should include
relevant metadata.
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38. Question & Answers
2. When is it permissible to exclude CGMP data from decision making?
• To exclude data from the release criteria decision-making process, there
must be a valid, documented, scientific justification for its exclusion (see
the guidance for industry Investigating Out-of-Specification (OOS) Test
Results for Pharmaceutical Production, and §§ 211.188, 211.192, and
212.71(b)).
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39. Question & Answers
2. When is it permissible to exclude CGMP data from decision making?
• The requirements for record retention and review do not differ
depending on the data format; paper-based and electronic data record-
keeping systems are subject to the same requirements.
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40. Question & Answers
3. Does each workflow on our computer system need to be validated?
• Yes, a workflow, such as creation of an electronic master production and
control record (MPCR), is an intended use of a computer system to be
checked through validation (see §§ 211.63, 211.68(b), and 211.110(a)).
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41. Question & Answers
3. Does each workflow on our computer system need to be validated?
• If you validate the computer system, but you do not validate it for its
intended use, you cannot know if your workflow runs correctly. For
example, qualifying the Manufacturing Execution System (MES)
platform, a computer system, ensures that it meets specifications;
however, it does not demonstrate that a given MPCR generated by the
MES contains the correct calculations.
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42. Question & Answers
3. Does each workflow on our computer system need to be validated?
• In this example, validating the workflow ensures that the intended
steps, specifications, and calculations in the MPCR are accurate. This is
similar to reviewing a paper MPCR and ensuring all supporting
procedures are in place before the MPCR is implemented in production
(see §§ 211.100, 211.186, and 212.50(b), and the guidance for industry
PET Drugs — Current Good Manufacturing Practice (CGMP)).
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43. Question & Answers
3. Does each workflow on our computer system need to be validated?
• FDA recommends you implement appropriate controls to manage risks
associated with each element of the system. Controls that are
appropriately designed to validate a system for its intended use address
software, hardware, personnel, and documentation.
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44. Question & Answers
4. How should access to CGMP computer systems be restricted?
• You must exercise appropriate controls to assure that changes to
computerized MPCRs, or other records, or input of laboratory data into
computerized records, can be made only by authorized personnel (§
211.68(b)).
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45. Question & Answers
4. How should access to CGMP computer systems be restricted?
• FDA recommends that you restrict the ability to alter specifications,
process parameters, or manufacturing or testing methods by technical
means where possible (for example, by limiting permissions to change
settings or data).
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46. Question & Answers
4. How should access to CGMP computer systems be restricted?
• FDA suggests that the system administrator role, including any rights to
alter files and settings, be assigned to personnel independent from
those responsible for the record content. To assist in controlling access,
FDA recommends maintaining a list of authorized individuals and their
access privileges for each CGMP computer system in use.
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47. Question & Answers
4. How should access to CGMP computer systems be restricted?
• If these independent security role assignments are not practical for
small operations or facilities with few employees, such as PET or
medical gas facilities, FDA recommends alternate control strategies be
implemented.
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48. Question & Answers
4. How should access to CGMP computer systems be restricted?
• For example, in the rare instance that the same person is required to
hold the system administrator role and to be responsible for the content
of the records, FDA suggests having a second person review settings and
content. If second-person review is not possible, the Agency
recommends that the person recheck settings and his or her own work.
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49. Question & Answers
5. Why is FDA concerned with the use of shared login accounts for computer
systems?
You must exercise appropriate controls to assure that only authorized personnel
make changes to computerized MPCRs, or other records, or input laboratory
data into computerized records, and you must implement documentation
controls that ensure actions are attributable to a specific individual (see §§
211.68(b), 211.188(b)(11), 211.194(a)(7) and (8), and 212.50(c)(10)). When
login credentials are shared, a unique individual cannot be identified through
the login and the system would thus not conform to the CGMP requirements in
parts 211 and 212. FDA requires that systems controls, including documentation
controls, be designed to follow CGMP to assure product quality (for example, §§
211.100 and 212.50).
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50. Question & Answers
6. How should blank forms be controlled?
There must be document controls in place to assure product quality (see
§§ 211.100, 211.160(a), 211.186, 212.20(d), and 212.60(g)). FDA
recommends that, if used, blank forms (including, but not limited to,
worksheets, laboratory notebooks, and MPCRs) be controlled by the
quality unit or by another document control method.
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51. Question & Answers
6. How should blank forms be controlled?
For example, numbered sets of blank forms may be issued as appropriate
and should be reconciled upon completion of all issued forms. Incomplete
or erroneous forms should be kept as part of the permanent record along
with written justification for their replacement (for example, see §§
211.192, 211.194, 212.50(a), and 212.70(f)(1)(vi)).
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52. Question & Answers
6. How should blank forms be controlled?
Similarly, bound paginated notebooks, stamped for official use by a
document control group, allow detection of unofficial notebooks as well as
of any gaps in notebook pages.
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53. Question & Answers
7. How often should audit trails be reviewed?
FDA recommends that audit trails that capture changes to critical data be
reviewed with each record and before final approval of the record. Audit
trails subject to regular review should include, but are not limited to, the
following: the change history of finished product test results, changes to
sample run sequences, changes to sample identification, and changes to
critical process parameters.
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54. Question & Answers
7. How often should audit trails be reviewed?
FDA recommends routine scheduled audit trail review based on the
complexity of the system and its intended use. See audit trail definition
1.c. above for further information on audit trails
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55. Question & Answers
8. Who should review audit trails?
Audit trails are considered part of the associated records. Personnel
responsible for record review under CGMP should review the audit trails
that capture changes to critical data associated with the record as they
review the rest of the record (for example, §§ 211.22(a), 211.101(c),
211.194(a)(8), and 212.20(d)). For example, all production and control
records, which includes audit trails, must be reviewed and approved by
the quality unit (§ 211.192). This is similar to the expectation that cross-
outs on paper be assessed when reviewing data.
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56. Question & Answers
9. Can electronic copies be used as accurate reproductions of paper or
electronic records?
Yes. Electronic copies can be used as true copies of paper or electronic
records, provided the copies preserve the content and meaning of the
original data, which includes associated metadata and the static or
dynamic nature of the original records
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57. Question & Answers
9. Can electronic copies be used as accurate reproductions of paper or
electronic records?
True copies of dynamic electronic records may be made and maintained in
the format of the original records or in a compatible format, provided that
the content and meaning of the original records are preserved and that a
suitable reader and copying equipment (for example, software and
hardware, including media readers) are readily available (§§ 211.180(d)
and 212.110).
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58. Question & Answers
10. Can electronic copies be used as accurate reproductions of paper or
electronic records? Is it acceptable to retain paper printouts or static
records instead of original electronic records from stand-alone
computerized laboratory instruments, such as an FT-IR instrument?
A paper printout or static record may satisfy retention requirements if it is
a complete copy of the original record (see §§ 211.68(b), 211.188,
211.194, and 212.60). For example, pH meters and balances may create a
paper printout or static image during data acquisition as the original
record. In this case, the paper printout or static image created during
acquisition, or a true copy, should be retained (§ 211.180).
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59. Question & Answers
10. Can electronic copies be used as accurate reproductions of paper or
electronic records? Is it acceptable to retain paper printouts or static records
instead of original electronic records from stand-alone computerized
laboratory instruments, such as an FT-IR instrument?
However, electronic records from certain types of laboratory instruments are
dynamic records, and a printout or a static record does not preserve the
dynamic format which is part of the complete original record. For example, the
spectral file created by FT-IR (Fourier transform infrared spectroscopy) can be
reprocessed, but a static record or printout is fixed, which would not satisfy
CGMP requirements to retain original records or true copies (§ 211.180(d)).
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60. Question & Answers
10. Can electronic copies be used as accurate reproductions of paper or
electronic records? Is it acceptable to retain paper printouts or static records
instead of original electronic records from stand-alone computerized
laboratory instruments, such as an FT-IR instrument?
Also, if the full spectrum is not displayed, contaminants may be excluded.
Control strategies must ensure that original laboratory records, including paper
and electronic records, are subject to second-person review (§ 211.194(a)(8)) to
make certain that all test results are appropriately reported. For PET drugs, see
the guidance for industry PET Drugs — Current Good Manufacturing Practice
(CGMP) for discussion of equipment and laboratory controls, including
regulatory requirements for records.
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61. Question & Answers
11. Can electronic signatures be used instead of handwritten signatures
for master production and control records?
Yes, electronic signatures with the appropriate controls can be used
instead of handwritten signatures or initials in any CGMP required record.
While § 211.186(a) specifies a “full signature, handwritten,” as explained
in the Federal Register on September 29, 1978 (43 FR 45069), part of the
intent of the full signature requirement is to be able to clearly identify the
individual responsible for signing the record.
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62. Question & Answers
11. Can electronic signatures be used instead of handwritten signatures
for master production and control records?
An electronic signature with the appropriate controls to securely link the
signature with the associated record fulfills this requirement. This
comports with part 11, which establishes criteria for when electronic
signatures are considered the legally binding equivalent of handwritten
signatures.
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63. Question & Answers
11. Can electronic signatures be used instead of handwritten signatures
for master production and control records?
Firms using electronic signatures should document the controls used to
ensure that they are able to identify the specific person who signed the
records electronically.
There is no requirement for a handwritten signature for the MPCR in the
PET CGMP regulations (21 CFR part 212).
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64. Question & Answers
12. When does electronic data become a cGMP record?
When generated to satisfy a CGMP requirement, all data become a CGMP
record. You must document, or save, the data at the time of performance
to create a record in compliance with CGMP requirements, including, but
not limited to, §§ 211.100(b) and 211.160(a). FDA expects processes to be
designed so that quality data required to be created and maintained
cannot be modified
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65. Question & Answers
12. When does electronic data become a cGMP record?
For example, chromatograms should be sent to long-term storage (archiving or a
permanent record) upon run completion instead of at the end of a day’s runs. It
is not acceptable to record data on pieces of paper that will be discarded after
the data are transcribed to a permanent laboratory notebook (see §§
211.100(b), 211.160(a), and 211.180(d)). Similarly, it is not acceptable to store
data electronically in temporary memory, in a manner that allows for
manipulation, before creating a permanent record. Electronic data that are
automatically saved into temporary memory do not meet CGMP documentation
or retention requirements.
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66. Question & Answers
12. When does electronic data become a cGMP record?
You may employ a combination of technical and procedural controls to
meet CGMP documentation practices for electronic systems. For example,
a computer system, such as a Laboratory Information Management System
(LIMS) or an Electronic Batch Record (EBR) system, can be designed to
automatically save after each separate entry.
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67. Question & Answers
12. When does electronic data become a cGMP record?
This would be similar to recording each entry contemporaneously on a
paper batch record to satisfy CGMP requirements. The computer system
could be combined with a procedure requiring data be entered
immediately when generated. For PET drugs, see the “Laboratory
Controls” section of the guidance for industry PET Drugs — Current Good
Manufacturing Practice (CGMP).
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68. Question & Answers
13. Why has the FDA cited use of actual samples during “system
suitability” or test, prep, or equilibration runs in warning letters?
FDA prohibits sampling and testing with the goal of achieving a specific
result or to overcome an unacceptable result (e.g., testing different
samples until the desired passing result is obtained). This practice, also
referred to as testing into compliance, is not consistent with CGMP (see
the guidance for industry Investigating Out-of-Specification(OOS) Test
Results for Pharmaceutical Production).
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69. Question & Answers
13. Why has the FDA cited use of actual samples during “system
suitability” or test, prep, or equilibration runs in warning letters?
In some situations, use of actual samples to perform system suitability
testing has been used as a means of testing into compliance. We would
consider it a violative practice to use an actual sample in test, prep, or
equilibration runs as a means of disguising testing into compliance.
Courtsey: GMP Scientific, Inc. Newtown, PA; www.gmpscientific.com
70. Question & Answers
13. Why has the FDA cited use of actual samples during “system
suitability” or test, prep, or equilibration runs in warning letters?
According to the United States Pharmacopeia (USP), system suitability
tests should include replicate injections of a standard preparation or other
standard solutions to determine if requirements for precision are satisfied
(see USP General Chapter <621> Chromatography).
Courtsey: GMP Scientific, Inc. Newtown, PA; www.gmpscientific.com
71. Question & Answers
13. Why has the FDA cited use of actual samples during “system
suitability” or test, prep, or equilibration runs in warning letters?
System suitability tests, including the identity of the preparation to be
injected and the rationale for its selection, should be performed according
to the firm’s established written procedures and the approved application
or applicable compendial monograph (§§ 211.160 and 212.60).
Courtsey: GMP Scientific, Inc. Newtown, PA; www.gmpscientific.com
72. Question & Answers
13. Why has the FDA cited use of actual samples during “system
suitability” or test, prep, or equilibration runs in warning letters?
If an actual sample is to be used for system suitability testing, it should be
a properly characterized secondary standard, written procedures should
be established and followed, and the sample should be from a different
batch than the sample(s) being tested (§§ 211.160, 211.165, and 212.60).
All data should be included in the record that is retained and subject to
review unless there is documented scientific justification for its exclusion.
For more information, see also the ICH guidance for industry Q2(R1)
Validation of Analytical Procedures: Text and Methodology
Courtsey: GMP Scientific, Inc. Newtown, PA; www.gmpscientific.com
73. Question & Answers
14. Is it acceptable to only save the final results from reprocessed
laboratory chromatography?
No. Analytical methods should be capable and stable. For most lab
analyses, reprocessing data should not be regularly needed. If
chromatography is reprocessed, written procedures must be established
and followed and each result retained for review (see §§ 211.160(a),
211.160(b), 211.165(c), 211.194(a)(4), and 212.60(a)). FDA requires
complete data in laboratory records, which includes raw data, graphs,
charts, and spectra from laboratory instruments (§§ 211.194(a) and
212.60(g)(3)
Courtsey: GMP Scientific, Inc. Newtown, PA; www.gmpscientific.com
74. Question & Answers
15. Can an internal tip regarding a quality issue, such as potential data
falsification, be handled informally outside of the documented CGMP quality
system?
No. Suspected or known falsification or alteration of records required
under parts 210, 211, and 212 must be fully investigated under the CGMP
quality system to determine the effect of the event on patient safety,
product quality, and data reliability; to determine the root cause; and to
ensure the necessary corrective actions are taken (see §§ 211.22(a),
211.125(c), 211.192, 211.198, 211.204, and 212.100).
Courtsey: GMP Scientific, Inc. Newtown, PA; www.gmpscientific.com
75. Question & Answers
15. Can an internal tip regarding a quality issue, such as potential data
falsification, be handled informally outside of the documented CGMP
quality system?
FDA invites individuals to report suspected data integrity issues that may affect
the safety, identity, strength, quality, or purity of drug products at
DrugInfo@fda.hhs.gov. “CGMP data integrity” should be included in the subject
line of the email.
See also Application Integrity Policy, available at 385
http://www.fda.gov/ICECI/EnforcementActions/ApplicationIntegrityPolicy/defau
lt.htm.
Courtsey: GMP Scientific, Inc. Newtown, PA; www.gmpscientific.com
76. Question & Answers
16. Should personnel be trained in detecting data integrity issues as part
of a routine CGMP training program?
Yes. Training personnel to detect data integrity issues is consistent with the
personnel requirements under §§ 211.25 and 212.10, which state that
personnel must have the education, training, and experience, or any
combination thereof, to perform their assigned duties.
Courtsey: GMP Scientific, Inc. Newtown, PA; www.gmpscientific.com
77. Question & Answers
17. Is the FDA investigator allowed to look at my electronic records?
Yes. All records required under CGMP are subject to FDA inspection. You
must allow authorized inspection, review, and copying of records, which
includes copying of electronic data (§§ 211.180(c) and 212.110(a) and (b)).
See also section 704 of the FD&C Act.
Courtsey: GMP Scientific, Inc. Newtown, PA; www.gmpscientific.com
78. Question & Answers
18. How does FDA recommend data integrity problems identified during
inspections, in warning letters, or in other regulatory actions be
addressed?
FDA encourages you to demonstrate that you have effectively remedied
your problems by: hiring a third party auditor, determining the scope of
the problem, implementing a corrective action plan (globally), and
removing at all levels individuals responsible for problems from CGMP
positions. FDA may conduct an inspection to decide whether CGMP
violations involving data integrity have been remedied.
Courtsey: GMP Scientific, Inc. Newtown, PA; www.gmpscientific.com
79. Question & Answers
18. How does FDA recommend data integrity problems identified during
inspections, in warning letters, or in other regulatory actions be
addressed?
These expectations mirror those developed for the Application Integrity
Policy. For more detailed guidance, see the “Points to Consider for Internal
Reviews and Corrective Action Operating Plans” public document
available on the FDA Web site, accessible at
http://www.fda.gov/ICECI/EnforcementActions/ApplicationIntegrityPolicy/
ucm134744.415 htm.
Courtsey: GMP Scientific, Inc. Newtown, PA; www.gmpscientific.com
80. Contact Info
• Sam Pandit
• Phone: (267) 334 5722,
• Email: spandit@gmpscientific.com
• www.gmpscientific.com
Editor's Notes
How presentation will benefit audience: Adult learners are more interested in a subject if they know how or why it is important to them.
Presenter’s level of expertise in the subject: Briefly state your credentials in this area, or explain why participants should listen to you.
Firms should implement meaningful and effective strategies to manage their data integrity risks based upon their process understanding and knowledge management of technologies and business models.
§§ 211.100 and 211.160 (requiring that certain activities be “documented at the time of performance” and that laboratory controls be “scientifically sound”);
§ 211.180 (requiring that records be retained as “original records,” “true copies,” or other “accurate reproductions of the original records”); and
§§ 211.188, 211.194, and 212.60(g) (requiring “complete information,” “complete data derived from all tests,” “complete record of all data,” and “complete records of all tests performed”).
Complete, consistent, and accurate data should be Attributable, Legible, Contemporaneously recorded, Original or a true copy, and Accurate (ALCOA).