STA Panel at ASA ANESTHESIOLOGY 2026

This panel examines how real-time, patient-specific physiological models can improve anesthetic precision and early risk detection. Speakers will cover the development of digital twins, the integration of multimodal data streams (ultrasound, EEG, EHR, wearables), and clinical case studies demonstrating adaptive monitoring, predictive dashboards, and key limitations to implementation.

Moderator:
Sean Jeffries, MSc, PhD(c)
McGill University Health Centre

Speakers:

"Clinical Impact and Limitations"
Sean Jeffries, MSc, PhD(c)
McGill University Health Centre

"Digital Twins in Medicine"
Christopher Connor, 
Brigham and Women's Hospital

"Integrating Multimodal Data Streams"
Patrick McCormick, MD, MEng
Memorial Sloane Kettering Cancer Center

Learning Objectives

• Identify key components of a patient-specific digital twin used
• Compare methods for integrating multimodal data streams (ultrasound, EEG, EHR, wearables) into predictive monitoring systems
• Recognize current limitations and implementation barriers in deploying predictive physiology tools in the operating room