Description: AI is broadly believed to provide benefits in regulatory document generation, but practical implementation and knowledge varies significantly across the industry. Many AI solutions fall short due to hallucinations, security vulnerabilities, and compliance gaps that regulatory professionals cannot afford.
In this expert panel, we share practical know-how on successfully deploying AI throughout the IND assembly process: organizing source data, extracting key outputs, writing sections, implementing quality control measures, and managing iterative updates. We present real-world case studies spanning small biotech to large pharma implementations, demonstrating measurable time savings while maintaining regulatory-grade quality.
Our panel brings together industry regulatory professionals, subject matter experts, and AI specialists who have navigated these challenges firsthand. We'll discuss what works, what doesn't, and how to securely cut IND assembly time to quality without compromising compliance standards.
This session focuses exclusively on proven, implemented solutions - no theoretical discussions, only battle-tested approaches that deliver results in regulated environments.
Learning Objectives:
Evaluate AI tools and platforms for IND assembly based on regulatory compliance, security requirements, and performance criteria to select appropriate solutions for their organization
Implement AI-assisted processes for organizing source data, extracting outputs, writing sections, and conducting quality control while maintaining regulatory traceability and avoiding common pitfalls
Assess the measurable time savings and quality improvements achieved through AI implementation using real-world metrics and case studies from small biotech to large pharma environments
