September 6, 2026
Apply large language models (LLMs) in HEOR and real-world evidence
This course introduces large language models (LLMs) and their applications in real-world evidence (RWE) and HEOR, with a focus on practical use and responsible implementation.
Technical topics include:
- LLM architecture, embeddings, and context windows
- Hallucinations, risk frameworks, and model evaluation
This course includes tools and concepts that can be immediately applied, including:
- Hands-on prompt engineering techniques
- Use cases such as literature retrieval, PICO extraction, and data analysis
- An introduction to agentic AI
Participants will gain the skills to effectively and responsibly apply LLMs in HEOR contexts. To participate in practical exercises, attendees are required to bring a personal laptop and have access to a personal or corporate LLM account with file upload functionality.
PREREQUISITE: General knowledge of chat-based LLMs (GPT, Claude, etc) is important. This is an intermediate course, and students should have prior knowledge of AI and have used chat based LLMs in a professional/work setting.
This short course is offered in-person at the ISPOR Asia Pacific Summit 2026. Separate registration is required. Visit the ISPOR Asia Pacific Summit 2026 Program page to learn more.
 | LEVEL: Intermediate |
FACULTY MEMBERS
Schedule:
LENGTH: 4 Hours | Course runs 1 day
Sunday, 6 September 2026 | Course runs 1 Day
ISPOR short courses are designed to enhance knowledge and techniques in core health economics and outcomes research (HEOR) topics as well as emerging trends in the field. Short courses offer 4 or 8 hours of premium scientific education and an electronic course book. Active attendee participation combined with our expert faculty creates an immersive and impactful learning experience. Short courses are not recorded and are only available during the live course presentation.