BOSTON — Health data analytics company OM1 has announced a major breakthrough in artificial intelligence for healthcare, revealing that its PhenOM® Foundation Model has now been trained on more than one billion years’ worth of patient health histories. The achievement makes PhenOM the largest clinical AI model of its kind to date, positioning it at the forefront of real-world data-driven healthcare innovation.
PhenOM is a next-generation AI platform designed to identify patient phenotypes and predict clinical events and treatment outcomes at scale. Drawing on both structured and unstructured healthcare data, the platform’s API delivers real-time predictions for thousands of outcomes—including hospitalizations, heart attacks, and strokes—across a wide range of diseases and populations.
“Training AI models on real-world health data at this scale opens up unprecedented opportunities to improve how we predict, diagnose, and treat disease,” said Dr. Richard Gliklich, CEO of OM1. “PhenOM is not just a model—it’s an adaptive foundation built on billions of clinical events, powering intelligent applications across the healthcare ecosystem.”
Beyond risk prediction, PhenOM is designed to evaluate the effectiveness and safety of treatments for individual patients and subgroups, making it a valuable tool for advancing precision medicine. The model is already helping stakeholders identify undiagnosed or undertreated patients, improve clinical trial design, and enhance population health strategies.
OM1’s rapid growth in the AI healthcare space is backed by a robust and expanding intellectual property portfolio. The company holds eight U.S. patents, with a ninth set to be issued on May 20, further reinforcing its leadership in clinical AI and real-world evidence.
OM1 is currently partnering with healthcare systems, payers, life sciences companies, and software developers to embed PhenOM into programs supporting drug development, value-based care, and health equity initiatives. With its unprecedented scale and predictive capability, the model represents a major step toward more personalized, efficient, and data-driven healthcare delivery.
