CSV to CSA Transition: 21 CFR Part 11, Data Integrity, Data Privacy, & Use of AI in FDA-Regulated Systems

Description

We can begin using some of the CSA principles today, even outside of the intended focus for the final guidance. This is provided that for these other areas, we are able to adequately explain their use and defend the tie-in to Part 11, data integrity, the Quality Management System (QMS) and other relevant documents and programs.

In this seminar, we’ll provide an overview of the transition process in going from CSV to CSA. We’ll then dive into a step-by-step guide for the transition that can be done by any company. The transition steps, related documents and other artifacts, and the potential issues to watch out for will be laid out very carefully.

The seminar will include a Q&A session at the end of each day. There are Appendices at the end of the slide deck that provides references related to the content that can be reviewed at your leisure. There is also a series of questions with answers provided, along with a rationale for the correct choice. Again, this can be reviewed after the event to further support the learnings from this seminar.

Why Should You Attend

Providing safe and effective pharmaceuticals, medical devices, and other FDA-regulated products is in the best interests of all those involved in the development, manufacturing, testing, and distribution of these products, as well as the customers/patients. You will learn about FDA’s CSV and CSA approaches, where the latter will enable practitioners to take advantage of newer technologies and innovations, including cloud services and Software-as-a-Service (SaaS) solutions. CSA will provide a more practical approach to testing and verification of requirements based on potential risk, should they fail to operate properly. It’s no longer a “one-size-fits-all” testing approach, as taken with CSV. CSA is also focused on critical thinking and requires some organizational change management to fully effect it in your environment

In this seminar, you will learn just how to transition your validation work from classic Computer System Validation (CSV) to Computer Software Assurance (CSA), based on the 2022 draft guidance from FDA, and now the final guidance issued in September 2025 for medical device companies, specifically in the areas of manufacturing and quality testing. You can increase efficiency and effectiveness of software development life cycle (SDLC) activities, enabling the delivery and support of computer solutions and new innovative products that will drive industry over the coming years.

You will also learn about 21 CFR Part 11 (ER/ES), data integrity, data life cycle management, and data privacy, while following a CSA approach to validation.

Finally, we will cover trends in industry and FDA related to the use of Artificial Intelligence (AI), Machine Learning (ML), and Large Language Models (LLMs), such as ChatGPT, Copilot, and Gemini, to name a few. Both industry and FDA have begun work in this area, which is currently under review to determine the appropriate regulatory framework to apply to it.

This seminar is intended for those working in the FDA-regulated industries, focused specifically on medical device companies. However, CSA principles can be used for pharmaceutical, medical device software, and tobacco products if applied carefully to ensure you have documented evidence that is defensible.

You should attend this seminar if you are responsible for planning, executing or managing the development, implementation or validation of any system governed by FDA regulations, or if you are using, maintaining, or supporting such a system. Learn by reviewing industry best practices and knowing where to gather key information to help you move forward with CSA and newer technologies and approaches quickly and in compliance with FDA.

Area Covered

This seminar will cover the following key areas:

• Computer System Validation (CSV)
• GAMP®5 “V” Model
• System Development Life Cycle (SDLC) methodology
• Validation Planning
• Validation Requirements
• Validation Testing
• Validation Reporting
• Requirements Traceability Matrix (RTM)
• Computer Software Assurance (CSA)
• Critical Thinking
• GAMP®5, 2nd Edition and its alignment with CSA 
• Transition from CSV to CSA
• 21 CFR Part 11 Guidance (ER/ES)
• 21 CFR Part 11 Requirements and Controls
• Common 21 CFR Part 11 Deficiencies
• Data Integrity Guidance (ALCOA+++ Principles)
• Data Integrity Requirements and Controls
• Common Data Integrity Deficiencies
• Data Life Cycle Management
• Data Governance
• Data Privacy
• Commercial-Off-the-Shelf (COTS) solutions
• Cloud Services
• Software-as-a-Service (SaaS) Solutions 
• Platform-as-a-Service (PaaS) Solutions
• Infrastructure-as-a-Service (IaaS) Solutions
• Single-Sign-On (SSO)
• Vendor Audit
• Artificial Intelligence (AI)
• Machine Learning (ML)
• Large Language Models (LLMs), including ChatGPT
• Retrieval-Augmented Generation (RAG)
• Recursive Language Models (RLMs)
• FDA Regulatory Compliance
• Current FDA Regulatory Enforcement Trends
• FDA Inspection Types
• Internal Audit
• Industry Best Practices
• Q&A

Agenda

Day 01

Morning Session:

• Computer System Validation (CSV)
• GAMP®5 “V” Model
• System Development Life Cycle (SDLC) methodology
• Validation Planning

15-Minute Break

• Validation Requirements
• Validation Testing
• Validation Reporting
• Requirements Traceability Matrix (RTM)

1-Hour Lunch Break

Afternoon Session:

• Computer Software Assurance (CSA)
• Critical Thinking
• GAMP®5, 2nd Edition and its alignment with CSA 
• Transition from CSV to CSA

15-Minute Break

• 21 CFR Part 11 Guidance (ER/ES)
• 21 CFR Part 11 Requirements and Controls
• Common 21 CFR Part 11 Deficiencies

15-Minute Q&A

Day 02

Morning Session:

• Data Integrity Guidance (ALCOA+++ Principles)
• Data Integrity Requirements and Controls
• Common Data Integrity Deficiencies
• Data Life Cycle Management
• Data Governance

15-Minute Break

• Data Privacy
• Commercial-Off-the-Shelf (COTS) solutions
• Cloud Services
• Software-as-a-Service (SaaS) Solutions 
• Platform-as-a-Service (PaaS) Solutions
• Infrastructure-as-a-Service (IaaS) Solutions
• Single-Sign-On (SSO)
• Vendor Audit

1-Hour Lunch Break

Afternoon Session:

• Artificial Intelligence (AI)
• Machine Learning (ML)
• Large Language Models (LLMs), including ChatGPT
• Retrieval-Augmented Generation (RAG)
• Recursive Language Models (RLMs)

15-Minute Break

• FDA Regulatory Compliance
• Current FDA Regulatory Enforcement Trends
• FDA Inspection Types
• Internal Audit
• Industry Best Practices

15-Minute Q&A

Who Will Benefit

Personnel in the following roles will benefit:

• Information Technology Analysts
• Information Technology Developers and Testers
• Software Quality Assurance Professionals
• QC/QA Managers and Analysts
• Analytical Chemists
• Compliance and Audit Managers
• Laboratory Managers
• Automation Analysts
• Manufacturing Specialists and Managers
• Supply Chain Specialists and Managers
• Regulatory Affairs Specialists
• Regulatory Submissions Specialists
• Risk Management Professionals
• Clinical Data Analysts
• Clinical Data Managers
• Clinical Trial Sponsors
• Computer System Validation Specialists
• GMP Training Specialists

Background

The life science industries, including pharmaceutical, medical device, biotechnology, biological, tobacco, and tobacco-related products continue to embrace new technology to improve delivery of quality products in compliance with the Food & Drug Administration (FDA). Automation has been used since the late 1970s, and in 1983, FDA recognized the need to regulate such computer systems. This resulted in the FDA Guidance for Computer System Validation (CSV) in 1983. CSV is based on a System Life Cycle Development (SDLC) methodology, with prescribed activities and deliverables to be produced through the life of an FDA-regulated system.

By the early 1990s, industry was seeking a pathway to go “paperless,” using electronic record and electronic signature (ER/ES) capability. The 21 CFR Part 11 Guidance was issued in 1997 to provide the requirements for ER/ES.

In 2002, FDA recognized the need for a risk-based approach to validation, understanding they could not audit every computer system at every company, as they were increasing exponentially. The risk-based approach became standard when performing validation.

In 2018, FDA found an alarming rate of violations by life science companies related to CFR Parts 211 and 212. These rules had been in place for decades, but suddenly, industry was failing at meeting them. The 2018 Data Integrity Guidance was issued and did not include a single new requirement. Instead, it reiterated the need for industry to improve their compliance in these key areas. It was a wake-up call for management and quality to provide organizations with a culture of accountability and an appropriate level of quality oversight.

In September 2022, FDA issued a Draft Guidance for Computer Software Assurance (CSA), replacing the outdated CSV approach. CSV was document-centric and heavily manual, which required significant time and was prone to error. CSA offered a fresh approach based on critical thinking, an art that was lost over prior decades as automation took center stage and provided they had validated a system, practitioners accepted the computer output. They had, in essence, become the “robots.” The International Society for Pharmaceutical Engineering (ISPE) issued GAMP5, 2nd Edition in July 2022, aligning the recommended approach with CSA. CSA became a final guidance in September 2025, but only for manufacturing and quality operations in medical device companies. The expectation is that this will become the standard approach for all life science industries in the near term. Until then, other markets and operational areas must continue to follow the CSV approach, relying on the 2002 FDA guidance..

Since 2015, we’ve seen a trend toward making use of cloud services, Software-as-a-Service (SaaS) solutions, and other technical innovations such as use of Artificial Intelligence (AI), Machine Learning (ML) and Large Language Models (LLMs), such as ChatGPT that have more recently begun to be used more heavily in life science companies.

As the pace of technological innovation and evolution becomes more intense, there is a critical need for applying computer system validation, 21 CFR Part 11 (Electronic Records and Electronic Signatures) compliance, and data integrity assurance in environments where newer technologies are becoming prevalent.