Validation of FDA-Regulated Systems with AI, ML & LLMs (ChatGPT)

Overview:

Life science industries — including pharmaceutical, medical device, biotechnology, biological, and tobacco-related products — continue to embrace new technologies to improve product quality while staying compliant with FDA requirements. Alongside growing adoption of cloud services, SaaS platforms, and advanced digital tools, the next wave of innovation is being driven by Artificial Intelligence (AI), Machine Learning (ML), and Large Language Models (LLMs) such as ChatGPT.

While these technologies are already transforming other industries, FDA-regulated companies have historically lagged behind. That gap is closing quickly. Today, AI applications are emerging across the product lifecycle: from research, development, and testing to manufacturing, labeling, surveillance, and post-market monitoring. This trend brings both unprecedented opportunities for efficiency and a host of compliance challenges. How do you validate systems that evolve over time? How do you meet FDA’s strict requirements for 21 CFR Part 11, data integrity, and Computer System Validation (CSV) when algorithms function as high-dimensional “black boxes”?

The FDA has made clear that compliance remains non-negotiable. Citations related to data integrity and Part 11 skyrocketed over the past decade, and many firms continue to face pressure to do more with fewer resources. These pressures are driving interest in AI tools to accelerate workflows — but without proper oversight, they also open the door to errors, security vulnerabilities, and audit findings. The agency is also modernizing its own processes, requiring all centers to integrate generative AI into operations by mid-2025, and piloting tools such as Elsa to streamline safety data reviews and facility inspections.

Meanwhile, new regulatory frameworks are emerging. The pending VALID Act aims to codify a “firm-based” approach, shifting oversight from individual products to the methods used in development and validation. FDA’s draft Computer Software Assurance (CSA) guidance and the updated GAMP®5, 2nd Edition further align expectations around risk-based validation, transparency, and ongoing maintenance of systems. For companies deploying AI/ML and LLM-enabled tools, this means preparing policies and controls that can withstand deeper scrutiny while enabling innovation.

Practical applications of these technologies are already visible. ChatGPT and similar LLMs are being explored for summarizing drug labeling content, condensing clinical dialogue for telemedicine, and screening literature to accelerate toxicological research. AI-driven models are helping to identify adverse events in post-marketing surveillance, predict organ-specific toxicities, and support personalized medicine approaches. At the same time, these systems introduce risks: reliance on unreliable training data, potential for incorrect outputs, cyberthreat exposure, and lack of transparency in decision-making.

This webinar will explore how FDA and industry are approaching the integration of AI, ML, and LLMs. We will discuss current and pending regulations, validation expectations, quality management implications, and practical strategies for ensuring data integrity and compliance. Case studies and industry best practices will illustrate where organizations have succeeded — and where they have stumbled — when deploying these technologies.

By attending, you will gain the knowledge to evaluate AI applications in your organization, align them with FDA requirements, and develop validation strategies that balance innovation with compliance. You will also understand how to prepare for upcoming regulatory changes, build risk-based frameworks, and ensure that the benefits of AI-enabled systems outweigh their risks to patients and products.

Areas covered in the session:

• Learn about how AI increasing in use in the life sciences industries, and how companies are leading the way to delivering more effective, safer, and more beneficial products as a result.
• Learn about the potential risks and challenges related to AI, ML and LLMs, such as ChatGPT.
• Learn about the challenges and vulnerabilities facing industry today, and how these new technologies can provide steps forward.
• Learn about FDA’s considerations for adapting its review process for AI-enabled software used to manufacture drugs and medical devices that have the ability to evolve rapidly in response to new data, sometimes in ways difficult to foresee.
• Learn how and under what circumstances products relying on AI are regulated by FDA.
• Learn about the potential impact and risk threatening data, processes, products, and ultimately patients based on these.
• Understand how to ensure benefits of products outweigh risks.
• Learn what FDA is doing to confront the increase in cyberthreats posed with the advent of newer technologies and what further work may be done.
• Understand how FDA, Congress, technology developers, and health care industry must work together to forge this new path and lead to a deeper and broader application of AI in operational processes in today’s FDA-regulated companies.
• Understand current industry best practices and recommendations for improving compliance of products that leverage AI in operational processes.
• Learn about industry best practices for implementing, validating, meeting FDA Part 11 and data integrity requirements, as AI applications improve operational efficiency and effectiveness in the process.
• Q&A

Handouts Included:

• A Comprehensive FDA AI/ML Validation Guide (with citations and regulatory references).
• FDA AI/ML Validation Checklist

Why Should You Attend?

AI, ML, and LLMs like ChatGPT are no longer futuristic concepts — they are already being piloted across FDA-regulated industries to accelerate research, streamline clinical documentation, and modernize quality systems. But without proper oversight, these same technologies can expose companies to compliance gaps, audit findings, and data integrity risks. Understanding how to validate and control these systems is no longer optional; it is essential.

This webinar will give you clarity on FDA’s expectations for risk-based validation, data integrity, and 21 CFR Part 11 compliance in the era of adaptive algorithms. You’ll learn how to evaluate AI-enabled systems, document them in a way that withstands FDA scrutiny, and align your policies with emerging frameworks such as the VALID Act, FDA’s draft Computer Software Assurance (CSA) guidance, and the updated GAMP®5 standards.

By attending, you will walk away with actionable strategies to integrate AI responsibly, reduce regulatory risk, and strengthen your compliance posture — all while leveraging innovation to enhance product quality and patient safety. Whether you are in validation, quality, regulatory affairs, or IT, this session will help you prepare for a future where AI will be inseparable from FDA compliance.

What industries will benefit from your training:

Manufacturing, Testing, Packaging and Distribution companies in the following industries that are regulated by FDA are required to follow GxPs:

• Pharmaceutical (for drug products introduced using a medical device)
• Medical Device
• Biologicals (for biological products introduced using a medical device)
• Tobacco (based on the Tobacco Control Act of 2009)
• E-Liquid/Vapor (based on the “Deeming” Act of 2016)
• E-Cigarette (based on the “Deeming” Act of 2016)
• Cigar (based on the “Deeming” Act of 2016)
• Third-Party companies that support those in the above industries, including Contract Research Organizations (CROs)
• Colleges and Universities offering programs of study in Clinical Trial Management and Regulatory Affairs/Matters related to FDA

Who will benefit?

Personnel in the following roles will benefit:

• Information Technology (IT) developers, testers, support resources
• QC/QA Managers
• QC/QA Analysts
• Clinical Data Managers
• Clinical Data Scientists
• Analytical Chemists
• Compliance Managers
• Laboratory Managers
• Automation Analysts
• Manufacturing Managers
• Manufacturing Supervisors
• Supply Chain Specialists
• Computer System Validation Specialists
• GMP Training Specialists
• Business Stakeholders responsible for computer system validation planning, execution, reporting, compliance, maintenance and audit
• Consultants working in the life sciences industry who are involved in computer system implementation, validation and compliance
• Auditors engaged in internal inspection