# How Digital Twins Could End Medical Guesswork

Page: https://stenobird.com/podcast/ai-and-healthcare-5049686/how-digital-twins-could-end-medical-guesswork
Text version: https://stenobird.com/podcast/ai-and-healthcare-5049686/how-digital-twins-could-end-medical-guesswork.md
Podcast: [AI and Healthcare](https://stenobird.com/podcast/ai-and-healthcare-5049686)
Published: 2025-12-18T16:58:50+00:00
Episode link: https://mtrudnak.podbean.com/e/how-digital-twins-could-end-medical-guesswork/
Audio file: https://mcdn.podbean.com/mf/web/efxw2wnu8v2qc4di/Episode_105_Audio7kd3w.mp3
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JSON: https://stenobird.com/v1/public/podcasts/ai-and-healthcare-5049686/episodes/how-digital-twins-could-end-medical-guesswork
Duration seconds: 3168

## Resource

Digital twins are moving from engineering into healthcare and the implications are profound. From oncology decision-making to clinical trials and personalized medicine, virtual human twins could reshape how clinicians predict outcomes, reduce toxicity, and tailor treatment. Dr. Sanjay Juneja and Dr. Doug Flora are joined by digital twin leaders Jim St. Clair and Professor James Fargason to explore how real-time data, AI, and system-level modeling can move medicine beyond population averages toward individualized care. This conversation unpacks what a true digital twin requires, why data quality and interoperability matter, and how digital twins may accelerate drug development, improve trial design, and reduce moral injury for clinicians.

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## Transcript

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