Effective and compliant computer system data management is critical to organizations in the pharmaceutical, biologics, vaccines, tobacco, animal health, medical device, or other FDA-regulated industry. During the past 30 years, best practices have been developed to ensure computer systems used in these environments can be cost-effectively managed while meeting all aspects of FDA compliance. To take this a step further, we are now looking at ways to ensure the data that resides on these systems is also managed in a compliant manner and one that will provide the best results for operations at the lowest cost.
After attending this course, you will understand data governance as a quality control discipline for assessing, managing, using, improving, monitoring, maintaining, and protecting organizational information. It is a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, when, under what circumstances, and, finally, using what methods.
WHY SHOULD YOU ATTEND?
Anyone involved with activities related to data that is subject to inspection, audit, or review by, FDA should attend the webinar to learn how to do so in a way that ensures the integrity of the data is maintained throughout its entire life cycle. Currently, FDA trends in compliance and enforcement indicate a high percentage of data integrity issues in their typical audit and inspection findings. This is a key area that the FDA is focused on, and should be of interest to those who want to avoid negative findings during such an audit or inspection of their regulated activities. The attendees will have a good grasp of how to leverage the best practices across all systems by creating a standardized program for data governance.
AREA COVERED
This webinar will cover the following key areas:
- Define the meaning of data integrity and focus on the criteria necessary for FDA compliance
- Provide an overview of recent FDA compliance and enforcement trends that focus on data integrity issues identified during audit and inspection
- Establishing a data governance framework and program for data that is collected, analyzed, stored, or reported using a computer system subject to FDA regulations
- How to use a data governance framework as a logical structure for classifying, organizing, and communicating complex activities involved in making decisions about and taking action on enterprise data?
- How to ensure that data governed by FDA adheres to the principles of Computer System Validation (CSV), System Development Life Cycle (SDLC) Methodology, and Electronic Records and Signatures (21 CFR Part 11), as applicable?
- How to leverage industry best practices in developing an overall data governance framework and program?
- How to ensure your data is captured and stored with integrity, and is maintained as such throughout its entire life cycle?
- Q&A
LEARNING OBJECTIVES
Upon completion of this session, attendees will have an understanding of how to:
- Tie data governance activities and investments to corporate drivers, strategies, and compliance
- Establish data governance program objectives, decision-making organizational structures, and assigned roles and responsibilities that fit within the organizational culture
- Understand the role of data owners vs. data stewards
- Understand the criticality of data identity, trust, security, integrity, accessibility, reliability, and consistency
- Design data governance processes that encompass people, processes, and technology
- Understand the policies and procedures necessary to support the data governance framework
WHO WILL BENEFIT?
- Information Technology analysts
- Information Technology developers and testers
- QC/QA managers and analysts
- Analytical chemists
- Laboratory managers
- Automation analysts
- Manufacturing supervisors and other key personnel
- Warehouse and supply chain supervisors and other key personnel
- Computer System Validation (CSV) specialists
- GMP training specialists
- Business stakeholders/subject matter experts
- Business system/Application testers
- Clinical data managers and scientists
- Quality managers, chemists, and microbiologists
- Regulatory Affairs personnel
- Consultants in the life sciences and tobacco industries
Anyone who is involved in the development, testing, manufacturing, storage, handling, and distribution of products must understand and conform to FDA requirements for data quality and integrity. Finally, anyone who is developing and maintaining software used in these industries should be aware of the requirements for data integrity for their systems.
Anyone involved with activities related to data that is subject to inspection, audit, or review by, FDA should attend the webinar to learn how to do so in a way that ensures the integrity of the data is maintained throughout its entire life cycle. Currently, FDA trends in compliance and enforcement indicate a high percentage of data integrity issues in their typical audit and inspection findings. This is a key area that the FDA is focused on, and should be of interest to those who want to avoid negative findings during such an audit or inspection of their regulated activities. The attendees will have a good grasp of how to leverage the best practices across all systems by creating a standardized program for data governance.
This webinar will cover the following key areas:
- Define the meaning of data integrity and focus on the criteria necessary for FDA compliance
- Provide an overview of recent FDA compliance and enforcement trends that focus on data integrity issues identified during audit and inspection
- Establishing a data governance framework and program for data that is collected, analyzed, stored, or reported using a computer system subject to FDA regulations
- How to use a data governance framework as a logical structure for classifying, organizing, and communicating complex activities involved in making decisions about and taking action on enterprise data?
- How to ensure that data governed by FDA adheres to the principles of Computer System Validation (CSV), System Development Life Cycle (SDLC) Methodology, and Electronic Records and Signatures (21 CFR Part 11), as applicable?
- How to leverage industry best practices in developing an overall data governance framework and program?
- How to ensure your data is captured and stored with integrity, and is maintained as such throughout its entire life cycle?
- Q&A
Upon completion of this session, attendees will have an understanding of how to:
- Tie data governance activities and investments to corporate drivers, strategies, and compliance
- Establish data governance program objectives, decision-making organizational structures, and assigned roles and responsibilities that fit within the organizational culture
- Understand the role of data owners vs. data stewards
- Understand the criticality of data identity, trust, security, integrity, accessibility, reliability, and consistency
- Design data governance processes that encompass people, processes, and technology
- Understand the policies and procedures necessary to support the data governance framework
- Information Technology analysts
- Information Technology developers and testers
- QC/QA managers and analysts
- Analytical chemists
- Laboratory managers
- Automation analysts
- Manufacturing supervisors and other key personnel
- Warehouse and supply chain supervisors and other key personnel
- Computer System Validation (CSV) specialists
- GMP training specialists
- Business stakeholders/subject matter experts
- Business system/Application testers
- Clinical data managers and scientists
- Quality managers, chemists, and microbiologists
- Regulatory Affairs personnel
- Consultants in the life sciences and tobacco industries
Anyone who is involved in the development, testing, manufacturing, storage, handling, and distribution of products must understand and conform to FDA requirements for data quality and integrity. Finally, anyone who is developing and maintaining software used in these industries should be aware of the requirements for data integrity for their systems.
