In this day and age, almost everything involves artificial intelligence (AI). While AI is becoming more popular, human decision-making can sometimes be inconsistent and time consuming. This session focuses on how AI can be used in quality assurance (QA) for cellular therapy laboratories. 

In this session, speakers will begin with explaining basic concepts like machine learning and large language models, and also open vs. closed systems, and AI prompt writing. In addition, speakers will also highlight: how AI can be used as a support tool/assistant with human experts reviewing the output; comparing different AI tools based on how accurate, transparent, and useful they are for QA work; and discussing how AI can help with everyday QA tasks such as writing SOPs, creating forms, performing risk assessments, root cause analysis (RCA), CAPA planning, validation protocols, training materials, audit preparation, and literature reviews; addressing concerns like incorrect AI outputs (hallucinations), bias, and ethical risks; and managing risks, such as using approved platforms, involving subject matter experts (SMEs), and following institutional AI policies. 

Are you a QA professional? Register today and join the session to explore how you can make smarter and better data-driven decisions in the interest of strengthening quality systems while maintaining patient safety and regulatory compliance.

Key learning objectives:

• Discuss potential applications of artificial intelligence (AI) in cellular therapy laboratory (CTL) quality assurance (QA) operations.
• Compare and contrast different AI platforms.
• Provide a practical example of how to use and validate the AI workflow to improve the CTL’s quality management program.
• Describe the limitations and risks of using AI platforms and propose strategies for managing these limitations and risks.