Digital Quality Metrics and AI/ML Analytics: Building a Continuous-Improvement Framework that Aligns with Regulatory Expectations

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, we’ve seen 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), Machine Learning (ML) and Large Language Models (LLMs), such as ChatGPT 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 with quality and compliance.

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 more prevalent.

Companies continue to seek faster and easier ways to get the work done, and this opens the door to more conversation around the use of AI/ML in software development, testing, and support.

For example, using real-time digital quality signals for metrics will optimize efficiency, quality, and compliance. This means selecting the appropriate metrics using risk-based quality principles. AI/ML can be used to detect trends, deviations, anomalies, and drift early on in a process, enabling quicker action to mitigate potential risk.

Dashboards built for AI/ML tools support data integrity in metrics pipelines and aggregation layers. They also support Part 11 compliance and risk-based decision-making.

The analytics can ultimately plug into the SDLC and GAMP®5 (Second Edition) control strategy. We’ll discuss supplier-provided analytics and what you must verify to achieve FDA compliance. The digital quality metrics can also be used to support regulatory inspections and audits.

But rapid cycles of innovation inherent in products due to constant modification based on new information available pose challenges. LLMs, including ChatGPT 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. LLMs will boost efficiency, but input data must be quality-checked.

AI can hallucinate, and show bias and performance drift. AI solutions need human guardrails, the experts who can evaluate output, and based on broad and deep expertise can make the right judgment calls for better outcomes and quality decisions. Without this safeguard, we may never achieve the great potential in ensuring quality, compliance, and real ROI from these technological innovations.

It is time to embark on the AI/ML revolution and continue to deliver quality products 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.

Industry must develop adequate standards and controls, evaluating models under the specific intended use. Ultimately, FDA will need to provide clear guidance for regulations on these new technologies.

We’ll provide an overview of validation, including CSV and Computer Software Assurance (CSA), and the latest GAMP®5, 2nd Edition that aligns with CSA. We’ll walk you through the Software Validation and Maintenance approach that will bring clarity to what FDA is looking for in terms of compliance.

Why Should You Attend:

Providing safe and effective FDA-regulated products is in the best interests of all those involved in their development, manufacturing, testing, and distribution. 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. AI can hallucinate, and show bias and performance drift. The human expert must be able to critically assess the output and make the judgment calls for better decisions, quality, and compliance, and to optimize ROI.

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 products that will drive industry over the coming years.

In particular, you’ll learn about quality metrics enhanced through AI, and how these can further streamline activities and identify and mitigate risks before they are realized.

This webinar is intended for those working in the FDA-regulated industries, including pharmaceutical, medical device, biological, animal health, and tobacco.  Functions that are applicable include research and development, manufacturing, Quality Control testing, distribution, clinical trial management, adverse events management, and post-marketing surveillance.

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

Areas Covered in the Session :

• Moving from lagging metrics to real-time digital quality signals
• Identifying the right metrics for GxP systems using risk-based quality principles
• Using AI/ML to detect trends, deviations, anomalies, and drift early
• Building dashboards that support data integrity, electronic records, and risk-based decision-making
• How analytics plug into the SDLC & GAMP 5 (Second Edition) control strategy
• Ensuring data integrity in metrics pipelines and aggregation layers
• Supplier-provided analytics & what FDA expects you to verify
• Presenting digital quality metrics during regulatory inspections and audits
• Understanding AI potential for hallucination, bias, and performance drift
• Ensuring a human with deep and broad knowledge provides the necessary guardrail to critically assess the output and make better decisions

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 testing, distribution, clinical trial management, sample labeling, adverse events management, and post-marketing surveillance. Whether involved in software development, implementation, testing, validation, maintenance or use of AI-enabled solutions, you will find a wealth of knowledge to enhance your ability to use these technologies with maximum effectiveness. Those using these systems, in particular, must understand their role as the human guardrail of AI, critically assessing the outcomes, making intelligent judgment calls, and ensuring better decisions. It’s not just about using these AI solutions, it’s about using them effectively and by critically thinking about your role and accountability to ensure you optimize quality, compliance, and ROI.

Examples of who will benefit from this webinar include:

• Information Technology Analysts
• Information Technology Developers and Testers
• QC/QA Managers and Analysts
• Analytical Chemists
• Compliance and Audit Managers
• Laboratory Managers
• Automation Analysts and Managers
• Manufacturing Specialists and Managers
• Supply Chain Specialists and Managers
• Regulatory Affairs Specialists
• Regulatory Submissions Specialists
• Clinical Data Analysts
• Clinical Data Managers
• Clinical Trial Sponsors
• Computer System Validation Specialists
• GMP Training Specialists
• Business Stakeholders/Subject Matter Experts
• Business System/Application Testers
• 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

This webinar will also benefit any vendors and consultants working in the life sciences industry who are involved in computer system implementation, validation and compliance. It will also help those in software development companies who support the life science industries.

Course Director: CAROLYN TROIANO

Carolyn Troiano has more than 45 years of experience in computer system validation in the pharmaceutical, medical device, biotechnology, tobacco, and other FDA-regulated industries.  She is currently an independent consultant, advising companies on FDA compliance, Computer System Validation (CSV), and large-scale IT system implementation projects. Carolyn participated in the FDA/Industry Partnership to develop 21 CFR Part 11, the FDA’s Guidance for Electronic Records and Electronic Signatures. During her career she has provided training, including CSV, 21 CFR Part 11, Data Integrity, and many other related compliance topics of interest to the life science industries.