From Quantum Physics To Precision Medicine: The AI Search For Hidden Patterns | Dr. Joseph Geraci, Ph.D. - Co-Founder, Chief Technology Officer and Chief Scientific Officer, NetraMark
What if a promising drug fails a clinical trial not because the drug doesn't work, but because it works for a subset of patients whose response gets lost in the averages? What if AI could help us find those patients hidden inside the data? That's the challenge we're exploring today with mathematical scientist Dr. Joseph Geraci, Ph.D., co-founder and chief technology and science officer at NetraMark ( https://www.netramark.com/ ).
Today we're joined by someone whose career has taken a remarkable path from mathematical physics and quantum computation to one of the biggest challenges in modern medicine: understanding why the same disease - and even the same drug - can behave so differently from one patient to another.
Dr. Joseph Geraci, Ph.D. is a mathematician, mathematical physicist, medical scientist, machine-learning innovator and entrepreneur, and today he is Co-Founder, Chief Technology Officer and Chief Scientific Officer of NetraMark, where he has helped develop NetraAI, a mathematically augmented AI platform designed to uncover hidden patient subgroups within clinical-trial data.
But Dr. Geraci's journey began far from clinical trials. He studied mathematics, physics, neuroscience and philosophy at the University of Toronto, went on to earn advanced degrees in mathematics and mathematical physics, and pursued doctoral research in quantum algorithms and statistical physics at USC, with his work supported by DARPA and the U.S. Army's Disruptive Technology Office (now IARPA).
From there, Dr. Geraci's career moved progressively closer to biology and medicine - through mathematical oncology, bioinformatics, pharmacogenomics, neuroscience, depression research, machine learning and eventually the problem of patient heterogeneity in clinical trials.
Along the way, Dr. Geraci has worked with enormous and very different kinds of datasets, from millions of records in financial analytics to electronic health records, genomic and molecular data, imaging and clinical-trial datasets. He has also held academic appointments at Queen's University and has been affiliated with the Arthur C. Clarke Center for Human Imagination at UC San Diego, where his interests include quantum computation and neuroscience.
Today, Dr. Geraci's central question is deceptively simple: What if some clinical trials don't fail because the drug doesn't work - but because we're asking the wrong patients to participate in the same trial?
Dr. Geraci's work at NetraMark is aimed at finding those hidden patterns - using AI to identify clinically meaningful patient subgroups, generate hypotheses, and potentially redesign how we select patients for clinical trials.
And that brings us to a fascinating conversation about AI, mathematics, disease, drug development, and perhaps even the way we think about what a disease actually is.
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