Etiome Announces Publication of Patient Modeling for Early Disease Detection in JAMIA Open
Study validates that Etiome’s AI-driven patient profiling can use routine physiological health data to accurately reveal hidden signatures of disease and enable earlier disease detection
CAMBRIDGE, Mass., Feb. x, 2026 – Etiome, a Flagship Pioneering company redefining how to detect and preempt disease progression, today announced the publication of a prospective study validating its AI-based patient profiling approach in JAMIA Open. The study demonstrates that Etiome’s AI models can accurately identify and label individuals during clinically silent phases of disease and throughout disease progression using routinely collected electronic health record data. This capability, embedded in Etiome’s Temporal Biodynamics™ platform, positions the company to study how disease evolves over time and to discover stage-specific therapeutic targets and biomarkers that would otherwise remain hidden.
“Disrupting disease progression before it becomes debilitating and irreversible requires the ability to identify patients at the earliest, silent stages,” said Ad Rawcliffe, Chief Executive Officer of Etiome and CEO-Partner at Flagship Pioneering. “This peer reviewed study demonstrates that Etiome can do just that, revealing those individuals who have hidden signatures of disease using routinely collected data from their electronic health records. These now-validated models serve as a foundational technology underlying our Temporal Biodynamics™ platform which enables and accelerates our development of transformative, stage-specific medicines.”
The study evaluated Bioprofiles, Etiome’s AI-driven patient profiling approach that analyzes routinely collected physiological and clinical data to precisely stage disease progression and identify clinically silent disease states. In a prospective validation study aimed at estimating metabolic dysfunction-associated steatotic liver disease (MASLD) severity without imaging, Bioprofiles outperformed traditional clinical labels and risk scores in identifying individuals with underlying disease biology. Importantly, the approach reduced the number of patients that needed to be screened by approximately 50% compared to standard clinical methods, demonstrating its potential to improve disease characterization, enable research into disease biology across temporal progression, and accelerate the translation and delivery of stage-specific medicines.
Scott Lipnick, Ph.D., Co-Founder and President of Etiome, Origination Partner at Flagship Pioneering, and senior author on the paper, said, “This study underscores the power of our approach to characterizing patients along the disease continuum in a way that better reflects underlying biology rather than relying solely on clinical diagnoses. By aligning patients to underlying biological states that traditional clinical labels often miss, our technology enables more precise disease staging and deeper insight into disease progression. While demonstrated here in MASLD patients, we believe this approach has broad applicability across diseases.”
About Etiome
Etiome is redefining how we detect and preempt disease progression to build a healthier future for patients with chronic and progressive diseases. Its Temporal Biodynamics™ platform is the first end-to-end technology to characterize disease with increased resolution over time and accelerate the development of preemptive medicines that promise better health outcomes. By revealing the dynamic molecular programs that define each stage of disease evolution, the platform drives the discovery of temporally informed therapeutic targets and biomarkers. These insights guide the development of Biostaged Medicines designed to halt or reverse disease before it becomes debilitating and irreversible. Etiome was founded by Flagship Pioneering in 2021. For more information, visit www.etiome.bio or follow us on LinkedIn and X.