Could a 'digital twin' help you get better health care? - Science Friday Recap

Podcast: Science Friday

Published: 2026-03-17

Duration: 18 min

Guests: Dr. Caroline Chung

Summary

Digital twins in healthcare are simulated models of individuals that use personal health data to predict treatment outcomes, aiming for personalized medicine. However, issues like data gaps, privacy, and model accuracy remain challenges.

What Happened

Digital twins, a concept borrowed from aerospace engineering, are now being explored in healthcare. These twins are digital models of individuals that use personal health data to predict how treatments might work, aiming for personalized medicine. Dr. Caroline Chung, a radiation oncologist at UTMD Anderson Cancer Center, explains that digital twins are not merely visual avatars but interactive models that evolve with continuous data input.

The idea originated in aerospace to avoid physical failures like a plane losing a wing. By creating digital replicas, engineers could test various scenarios in a virtual space. Applying this concept to biology is complex due to unknown molecular mechanisms, yet there are areas like heart function where digital twins are already viable.

Dr. Chung's work involves developing digital twins to optimize radiation therapy by predicting tumor resistance and adjusting treatment accordingly. This approach aims to enhance the effectiveness of cancer treatments while minimizing side effects.

In cardiology, digital twins could predict cardiac events like heart attacks by simulating blood flow and identifying risks. These models could also personalize screening schedules, reducing unnecessary tests and anxiety for patients.

One breakthrough in cancer treatment involves altering chemotherapy schedules based on digital twin simulations, potentially improving outcomes without additional drug costs. This illustrates the potential of digital twins to refine existing treatments rather than develop new ones.

Creating a comprehensive digital twin of an entire human body is a complex goal requiring global collaboration and significant investment. The purpose must be clear, whether for scientific discovery or specific clinical applications.

Privacy concerns are significant, as a complete digital twin containing all personal health data could be highly identifiable. Questions of data ownership and accessibility are yet to be resolved, complicating the widespread adoption of digital twins in healthcare.

Dr. Chung emphasizes the importance of balancing the human aspect of medicine with technological advancements. While digital twins offer new insights, clinicians must integrate these with personal and social factors in patient care decisions.

Key Insights