Leveraging Generative AI for Audit and Regulatory Response Development
Complimentary
Learning Level: Advanced
Time: 1100 - 1200 ET
Session Length: 1 hour
Pharmaceutical companies operate in an environment of increasing regulatory scrutiny, where the quality, timeliness, and accuracy of responses to inspections and audits directly impact compliance status and business continuity. Traditional response development processes are often fragmented, highly manual, and inconsistent—resulting in weak root cause analysis, ineffective CAPAs, and missed timelines. These limitations create both operational and compliance risks. With the rapid advancement of Generative AI (GenAI) technologies, there is a unique opportunity to transform the audit and regulatory response process into a standardized, data-driven, and inspection-ready function. By embedding AI into these workflows, organizations can enhance efficiency, improve the quality of submissions, and strengthen regulatory confidence.
This session will explore the practical application of Generative AI—including Natural Language Processing (NLP), Retrieval-Augmented Generation (RAG), and prompt orchestration—to automate and standardize audit and regulatory response development. Participants will learn how AI can support critical steps such as defining scope, conducting root cause analysis, drafting CAPAs, and ensuring alignment with regulatory expectations. The presentation will outline a structured response framework, supported by real-world case studies (e.g., Microsoft Copilot, custom GPTs), and will highlight regulatory considerations, data integrity principles, and compliance guardrails.
Take-aways
Participants will leave with a clear, actionable framework for integrating GenAI into response development, enabling faster turnaround, improved quality and consistency, stronger CAPA design, and better cross-functional collaboration. They will also understand how this aligns with ISPE’s AI and GAMP initiatives, positioning their organizations for sustainable inspection readiness and future regulatory expectations.
Learning Objectives
- Understand the Role of Generative AI in Regulatory and Audit Response Development. Participants will learn how GenAI capabilities—such as Natural Language Processing (NLP), Retrieval-Augmented Generation (RAG), and prompt engineering—can be integrated into audit and regulatory response workflows to improve speed, quality, and consistency.
- Apply a Structured Framework for AI-Enabled Response Development. Participants will gain practical knowledge of a step-by-step framework (from debrief to final review) to embed AI in observation review, root cause analysis, CAPA drafting, and documentation standardization.
- Recognize the Benefits and Compliance Considerations of AI Integration
