Learn how to harness real-time digital quality signals, AI/ML-driven analytics, and GAMP®5 control strategies to boost compliance, efficiency, and inspection readiness in FDA-regulated environments.
Includes live access & recording
The life science industries continue to embrace new technology to improve delivery of quality products in compliance with FDA. Trends toward cloud services, SaaS solutions, and emerging technologies are accelerating — and Artificial Intelligence (AI), Machine Learning (ML), and Large Language Models (LLMs) such as ChatGPT are increasingly finding a presence at pharmaceutical, medical device, and biotechnology companies.
Using real-time digital quality signals for metrics will optimize efficiency, quality, and compliance. AI/ML can detect trends, deviations, anomalies, and drift early in a process, enabling quicker action to mitigate potential risk. Dashboards built for AI/ML tools support data integrity in metrics pipelines and support 21 CFR Part 11 compliance and risk-based decision-making.
However, AI can hallucinate, and show bias and performance drift. LLMs trained on vast datasets embody the ultimate black box in FDA regulation — nonlinear and high-dimensional, making it difficult to trace specific inputs to outputs. AI solutions need human guardrails: experts who can evaluate output and make the right judgment calls for better outcomes and quality decisions.
This 90-minute session provides an overview of validation including CSV, Computer Software Assurance (CSA), and the latest GAMP®5 2nd Edition — walking you through the Software Validation and Maintenance approach that brings clarity to what FDA expects in terms of compliance.
With newer technologies such as AI in the mix, there is opportunity for greater efficiency and efficacy — but also more challenges for companies that develop, test, and support software in the life sciences. The human expert must be able to critically assess AI output and make the judgment calls for better decisions, quality, compliance, and ROI.
In this webinar you will learn how AI, ML, and LLMs can increase efficiency and effectiveness of SDLC activities — enabling delivery of computer solutions and innovative products that will drive industry over the coming years.
You will learn about quality metrics enhanced through AI, how they streamline activities, and how to identify and mitigate risks before they are realized. This session is essential for anyone responsible for planning, executing, or managing FDA-regulated systems that use AI and related technologies.
Four focused areas covering the full landscape of AI/ML quality analytics in FDA-regulated life science environments.
Move from lagging metrics to real-time AI/ML-driven quality monitoring — detecting trends, deviations, anomalies, and drift early to enable faster, risk-informed action.
Learn how analytics plug into SDLC, GAMP®5 (2nd Edition), and 21 CFR Part 11 compliance — including what FDA expects you to verify from supplier-provided analytics solutions.
Address hallucination, bias, and performance drift head-on. Understand the role of the human guardrail in critically assessing AI outputs and making defensible, quality-driven decisions.
Use digital quality metrics and AI/ML dashboards to support regulatory inspections, audits, and submissions — building a continuous-improvement framework that demonstrates compliance to investigators.
Ten practical topics covering the complete AI/ML quality metrics lifecycle — from real-time signals to regulatory inspection readiness.
Professionals across pharmaceutical, medical device, biologics, tobacco, and life sciences organizations involved in AI-enabled systems, computer system validation, quality operations, and regulatory compliance.
IT Analysts, Developers & 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 & Managers
Computer System Validation Specialists
GMP Training Specialists
Business Stakeholders & Subject Matter Experts
Consultants in Life Sciences CSV & Compliance
Internal Auditors
The life science industries have historically lagged behind other sectors in adopting emerging technologies — but that gap is closing rapidly. AI, ML, and LLMs are now embedded in software applications used to develop, produce, test, and manage life science products. As this adoption accelerates, the need for robust computer system validation, 21 CFR Part 11 compliance, and data integrity assurance has never been greater.
As the pace of technological innovation becomes more intense, there is a critical need for computer system validation, 21 CFR Part 11 compliance, and data integrity assurance to continue in environments where AI and ML are becoming more prevalent. Rapid cycles of innovation — driven by constant model updates, new training datasets, and evolving deployment environments — pose unique challenges that traditional validation frameworks were not designed to address.
FDA has made clear through its Digital Health Center of Excellence, AI/ML Action Plan, and evolving guidance that regulated companies are expected to ensure their AI-enabled systems are appropriately validated, monitored, and controlled throughout their lifecycle. Industry must develop adequate standards and controls, evaluating models under the specific intended use. The analytics framework explored in this session — integrating SDLC, GAMP®5 2nd Edition, CSA principles, and risk-based quality metrics — provides the structure organizations need to move forward with confidence, compliance, and maximum ROI from their AI investments.
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 — giving her a uniquely foundational perspective on the regulatory frameworks that govern digital systems in life sciences.
Throughout her career she has provided training across CSV, 21 CFR Part 11, Data Integrity, and many other compliance topics of interest to the life science industries. Her 45+ years of hands-on regulatory and technical experience make her one of the most authoritative voices on the intersection of AI/ML, computer system validation, and FDA compliance.
Join Carolyn Troiano for this 90-minute deep-dive into AI/ML quality analytics and build a continuous-improvement framework that keeps your organization FDA-compliant and inspection-ready.