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 webinar, 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.

FDA is currently trying to modernize their systems and use of data. FDA announced all agency’s centers must fully integrate generative AI into work by the end of June 2025. The intent is to reduce non-productive busy-work that has historically consumed the review process. Device submission review can often take many months, but there is an opportunity to reduce this timeframe and allow expert reviewers to focus on the more complex cases.

Medical devices using AI are designed to analyze vast amounts of data to generate clinical insights. This means that the company’s quality management system (QMS) must ensure consistent production and control of manufacturing and quality systems, and involves routine inspections and audits.

The Verifying Accurate Leading-Edge Development Act, or Valid Act is pending, and will codify the “firm-based” approach to regulation. FDA will oversee methods used for technology development and validate reliability rather than decoupling the AI product’s construction. By ensuring robust systems are in place, FDA can enhance overall safety and effectiveness of medical devices produced.

Rapid cycles of innovation inherent in products due to constant modification based on new information available pose challenges. ChatGPT from OpenAI has demonstrated substantial semantic medical knowledge and the ability to perform work that will accelerate the submission approval process.

Large Language Models (LLMs) trained on vast datasets embody the ultimate black box in the realm of FDA regulation. They are nonlinear and high-dimensional, making it difficult to trace specific inputs to outputs. A risk is they may return wrong answers when trained on unreliable datasets. Under a firm-based regulation approach by FDA, innovators can bring certain new products to market more efficiently.

LLMs will boost efficiency, but input data must be quality-checked. Industry must develop adequate standards and controls, evaluating AI algorithm models under the specific intended use of a device. Ultimately, industry will be able to identify new product candidates and plan, execute and analyze data from clinical trials.

In June 2025, FDA announced plans to use AI to speed new medical device and SaMD approvals. Elsa is a tool that may enhance FDA review of safety data, summarize reports and flag facilities needing inspection. Built within a high-security GovCloud environment, it offers a secure platform for FDA staff to access internal documents while ensuring information remains within the agency. Submission reviews could be considerably shortened.

Learn more about how FDA and life science companies are using AI and ChatGPT. This is expected to improve efficiency while enabling FDA and companies to run more smoothly. This is critical at a time when we are faced with a rising demand for healthcare and physician shortages. Leveraging comprehensive data systems will lead to greater efficiency in diagnosis and treatment planning. Getting these products through the FDA regulatory submission process more quickly and efficiently is the goal to put them in the hands of patients.

We’ll provide an overview of computer system validation when using AI, including the draft guidance from FDA on Computer Software Assurance (CSA), and the latest GAMP^®5, 2^nd Edition that aligns with CSA. We’ll walk you through the approach used by FDA during inspection to bring clarity to what FDA is looking for, primarily allowing companies to manage risks from changes, while enabling improvement of performance and advancing patient care.

Learning Objectives:-

During the webinar, we will discuss the following:

• Learn about “GxP” operational areas, systems, and data regulated by FDA
• Understand the basics of Computer System Validation (CSV), the traditional approach
• Learn about Computer Software Assurance (CSA) and how it compares with CSV
• Know how to transition from CSV to CSA for validation of FDA-regulated systems
• Understand the System Development Life Cycle (SDLC) Methodology for managing a system through all of its life phases
• Learn about the concepts introduced in ISPE’s GAMP^®5, 2^nd Edition, and how these align with CSA principles of risk assessment and critical thinking
• Review current trends in FDA 483s, Warning Letters, and Consent Decrees
• Learn about 21 CFR Part 11, FDA Guidance for Electronic Records and Electronic Signatures (ER/ES)
• Understand how Data Integrity (“ALCOA+” Principles) must be applied to FDA-regulated systems
• Learn about the industry Cost of Non-Compliance
• Understand the deliverables for a Validation effort, starting with a Validation Plan
• Know the key elements to include in an IT Vendor Audit
• Understand the advantages and key elements to consider when using Automated Testing
• Understand the importance of a Requirements Traceability Matrix (RTM)
• Understand the importance of a formal Change Control procedure
• Know the key elements required for Maintenance of a System in a Validated State
• Learn about Cloud-Based Services and the potential savings in ROI that can be generated
• Understand the concepts of Software-as-a-Service (SaaS)
• Understand the need for a cloud-based service provider to have SOC 2 Certification
• Learn about key concepts related to Artificial Intelligence (AI) and Machine Learning (ML)
• Understand how to use Large Language Models (LLMs) (e.g., ChatGPT, Gemini, Copilot)
• Learn about the FDA Directive to Leverage AI/ML Solutions in all agencies
• Know what is required to achieve FDA Inspection Readiness
• Learn about Current Trends in FDA Inspection and Enforcement
• Q&A

Areas Covered:-

During this webinar, the following areas will be covered:

• GxP Systems
• GMP, GLP, GCP
• Computer System Validation (CSV)
• Computer Software Assurance (CSA)
• CSV to CSA Transition
• GAMP^®5, 2^nd Edition
• 21 CFR Part 11, FDA Guidance for Electronic Records and Electronic Signatures (ER/ES)
• Data Integrity (“ALCOA+” Principles)
• Data Lifecycle
• Audit Trails and Audit Trail Review
• User Authentication, Access Control, and Monitoring
• Security Monitoring
• Cost of Non-Compliance
• Validation Plan
• Vendor Audit
• Vendor Contracts and Service Level Agreements (SLAs)
• Requirements Specification (RS)
• Risk Assessment and Mitigation
• Risk-Based Testing
• Critical Thinking
• Automated Testing
• Installation Qualification (IQ) Test Protocol and Test Summary Report
• Operational Qualification (OQ) Test Protocol, Test Scripts, and Test Summary Report
• Performance Qualification (PQ) Test Protocol, Test Scripts, and Test Summary Report
• Requirements Traceability Matrix (RTM)
• Validation Summary Report
• Change Control
• Maintenance of a System in a Validated State
• Cloud-Based Services
• Software-as-a-Service (SaaS)
• SOC 2 Certification
• Artificial Intelligence (AI) and Machine Learning (ML)
• Large Language Models (LLMs) (e.g., ChatGPT, Gemini, Copilot)
• FDA Directive to Leverage AI/ML Solutions in Agencies
• FDA Inspection Readiness
• Current Trends in FDA Inspection and Enforcement
• Industry Best Practices.

Background:-

In September 2025, FDA issued a draft guidance for Computer Software Assurance (CSA). A final guidance was issued by the Agency in September 2025, but only for medical device companies and in the manufacturing and quality testing areas. The remainder of the life sciences industries must still adhere to the traditional Computer System Validation (CSV) approach to validating computer systems in FDA-regulated operations. In either case, companies can take advantage of some of the efficiencies related to following CSA, including risk-based testing and use of critical thinking. We will discuss both CSV and CSA, comparing the two approaches, and will provide a pathway that can be taken to transition to CSA.

The life science industries, including pharmaceutical, medical device, biotechnology, biological, and tobacco and tobacco-related products continue to embrace new technology to improve delivery of quality products in compliance with FDA. In addition to some trends toward making use of cloud services, Software-as-a-Service (SaaS) solutions, and other technical innovations that have more recently begun to be used more heavily in life science companies.

Artificial Intelligence (AI) and Machine Learning (ML) are beginning to find a presence at these companies. While life science companies tend to lag behind other markets in using these technologies, they are catching up and we are seeing much more activity related to AI use in software applications used to develop, produce, test, and manage life science products.

As the pace of technological innovation and evolution becomes more intense, there is a critical need for computer system validation, 21 CFR Part 11 (Electronic Records and Electronic Signatures) compliance, and data integrity assurance to continue in environments where artificial intelligence (AI) and machine learning (ML) are becoming prevalent.

FDA became alarmed by the lack of compliance to meet data integrity and Part 11 requirements during the last decade. Out of compliance citations during this period, including Form 483s and Warning Letters have skyrocketed for these key areas of compliance. But why?

Based on discussions with clients and stakeholders at conferences and meetings, it has become obvious that most of the performers in industry are under management pressure to do more work with fewer resources and in less time. This continues to lead performers to seek faster and easier ways to get the work done, and opens the door to more conversation around the use of AI/ML and ChatGPT in software development, testing, and support.

It is time to embark on the AI/ML revolution and continue to deliver quality products in life sciences with compliance to meet the needs of the consumers by putting newer, more innovative, safer, and more effective products in their hands, all of which are key focus areas for FDA. We will discuss how FDA is using AI to provide a faster review of submissions and for some other purposes to support industry.

Why Should You Attend:-

Providing safe and effective medical device & SaMD products regulated by FDA is in the best interests of all those involved in the development, manufacturing, testing, and distribution of these products. You will learn about projects going on in industry and at FDA that take advantage of Artificial Intelligence (AI), Machine Learning (ML) and Large Language Models (LLMs), such as ChatGPT.

With newer technologies such as AI in the mix, it means opportunity for greater efficiency and efficacy, but also poses more challenges for companies that develop, test, and support software applications in the life science industries.

In this webinar, you will learn just how AI, ML and LLMs, such as ChatGPT can increase efficiency and effectiveness of software development life cycle (SDLC) activities, enabling the delivery and support of computer solutions and new innovative medical device & SaMD products that will drive industry over the coming years.

You will also learn about the challenges posed by the introduction of AI into operational areas regulated by FDA. AI can hallucinate, show bias, and exhibit performance drift. There needs to be a human guardrail around the AI to ensure that all outputs are reviewed by an expert in the loop who applies critical thinking skills. Better output means better decisions, better quality, integrity, patient safety, and even ROI. The expert must have both foundational and human skills which we will cover during this session.

You should attend this webinar if you are responsible for planning, executing or managing the development, testing, implementation, validation, or use of any system governed by FDA regulations that uses AI technology, or if you are maintaining or supporting such a system.

You should also attend this webinar if you are responsible for developing, testing or supporting software used in medical device or SaMD products.

We will discuss current FDA trends in compliance and enforcement, highlighting the key areas of the agency’s focus.

Learn by reviewing industry best practices and knowing where to gather key information to help you move forward with these technologies quickly and in compliance with FDA.

Who Should Attend:-

This webinar is intended for those involved in planning, execution and support of computer system validation activities, working in the FDA-regulated industries, including pharmaceutical, medical device, biologics, tobacco and tobacco-related products (e-liquids, e-cigarettes, pouch tobacco, cigars, etc.). Functions that are applicable include research and development, manufacturing, Quality Control, distribution, clinical testing and management, sample labeling, adverse events management and post-marketing surveillance.

Personnel in the following roles will benefit:

• Information Technology (IT) Analysts
• IT Software Developers & Testers
• IT Support Staff
• IT Security Staff
• QC/QA Managers and Analysts
• Production Managers and Supervisors
• Supply Chain Managers and Supervisors
• Clinical Trial Data Managers and Scientists
• Compliance Managers and Auditors
• Lab Managers and Analysts
• Computer System Validation Specialists
• GMP, GLP, GCP Training Specialists
• Business Stakeholders using Computer Systems regulated by FDA
• Regulatory Affairs and Submissions Personnel
• Consultants in the Life Sciences and Tobacco Industries
• Interns working at the companies listed above
• College students attending schools and studying computer system validation, regulatory affairs/matters (related to FDA) or any other discipline that involves adherence to FDA regulatory requirements.