The AI Innovation Circle for Life Sciences | Episode 3

The Art of Meaning: Taxonomies, Ontologies & Semantic Foundations for Agentic AI

How should you organize and model enterprise knowledge for enterprise AI?

Join fellow Life Sciences, data and AI leaders for an interactive discussion on one of the most important questions in semantic AI: when should you use a taxonomy, ontology or controlled vocabulary? This workshop explores how semantic modeling decisions influence AI performance, information retrieval, reasoning and regulatory understanding, helping organizations select the right approach for the right business challenge.

Learn from real-world Life Sciences examples, including Medical Dictionary for Regulatory Activities (MedDRA), Clinical Data Interchange Standards Consortium (CDISC), National Cancer Institute Thesaurus (NCIt), Systematized Nomenclature of Medicine – Clinical Terms (SNOMED CT), Medical Subject Headings (MeSH) and other industry standards, while discussing the strengths and limitations of different semantic frameworks. Together, we'll examine how semantic choices impact data interoperability, knowledge discovery and AI-generated insights, creating a stronger foundation for trusted and explainable AI.

Browse All Episodes

Date: November 4, 2026

Time: 3:00 p.m. ET

Audience: Senior Leaders Across R&D, Clinical Development, Regulatory Affairs, Medical Affairs, Data & AI and Information Management

Key takeaways

Choose the Right Semantic Model for the Right Problem
Learn when a controlled vocabulary, taxonomy or ontology is the appropriate solution, and how the right choice improves usability, scalability and AI outcomes
Leverage Industry Standards More Effectively
Understand the strengths and limitations of Life Sciences standards such as MedDRA, CDISC, NCIt, SNOMED CT, MeSH and others, and how they support regulatory, clinical, research and operational use cases
Improve AI Accuracy, Retrieval and Reasoning
Discover how semantic modeling decisions directly impact search relevance, AI grounding, explainability, regulatory context and the ability of AI systems to deliver trusted and actionable insights

Episode 01 | July 14, 2026

The Foundational Workshop in an Enterprise AI Series

Join, Discuss & Learn

Join fellow Life Sciences, data and AI leaders for an interactive discussion on how semantic models shape the success of AI initiatives. This workshop explores when to use controlled vocabularies, taxonomies or ontologies, and how these foundational choices influence data interoperability, information discovery, regulatory understanding and AI performance across the enterprise.

Learn from real-world life science standards and frameworks such as MedDRA, CDISC, NCIt, SNOMED CT and MeSH while discussing practical approaches for selecting the right semantic model for the right challenge. Together, we'll examine how semantic design decisions improve retrieval, reasoning, explainability and the quality of AI-generated insights, creating a stronger foundation for trusted and governed AI.