Most health-AI founders come from medicine or machine learning. Amir Hashmi came from gas turbines. For 13 years he ran operations across energy and heavy industry — a world where “explain exactly why, and trace it back to the manual” isn’t a nice-to-have, it’s how you avoid catastrophic failure. Then he pointed the same engine he built for a power plant at a hospital.
That engine is GENEXIX: one explainable digital-twin platform that runs a 400-megawatt plant in one configuration and, in another, models a patient’s physiology, predicts deterioration, and simulates drug trials for research. This week, Dr. Junaid Kalia — with Ed Marx and Dr. Harvey Castro — put both halves of the story in the room: the founder who built it, and Dr. Dania Amir, the physician deciding whether an industrial-grade digital twin belongs anywhere near a clinical decision
“A prediction you can’t explain has no business changing what a doctor does”
-Junaid, Ed & Harvey
00:00 What Is a Clinical Digital Twin? (One Engine, Two Worlds)
00:35 Meet the Guests: Amir Hashmi & Dr. Dania Amir
02:48 From Power Plants to Patients: an Engineer’s Crossover
04:49 Validating Medical AI: a Physician’s Role
05:59 Why Build a Digital Twin in Healthcare?
07:47 Modeling Patient Physiology With a Digital Twin
10:05 Explainable AI Architecture: No Black Box
11:05 Digital Twins in the ICU: Predicting Deterioration
14:19 Automation Bias & the AI Intelligence Layer
15:50 The Future of Clinical Digital Twins
Dr. Junaid Kalia, Neurocritical Care Specialist, Founder of Savelife.AI™
Dr. Harvey Castro, ER Physician, #DrGPT™
Edward Marx, CEO, Advisor
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