Imagine trying a bunch of different keys to open a door without knowing which one fits. Right now, doctors do that with blood pressure meds, but for over half of patients, it doesn't work. This project creates a biological 'cheat sheet' using AI to tell doctors exactly which drug will work for a specific person. It also helps spot hidden causes of high blood pressure that can actually be cured.
Over 50% of hypertension patients remain uncontrolled because doctors use a trial-and-error approach to prescribing drugs and often miss curable secondary causes like endocrine hypertension.
A set of multi-omics (MOMICS) stratification biomarkers and AI-driven prediction models validated through three clinical trials.
If you are a diagnostic company dealing with low adoption of generic tests — this project developed MOMICS biomarkers that act as companion diagnostics to guide drug prescription. This allows for a high-value product that predicts therapeutic response for primary hypertension.
If you are a pharma company dealing with high drug failure rates in clinical trials — this project developed a stratification method to identify patients most likely to respond to specific antihypertensive drugs. This improves the efficiency of treatment delivery and patient outcomes.
If you are a software provider dealing with a lack of validated clinical data for AI — this project developed machine learning models integrating genetic and metabolomic data. This provides a validated tool for clinicians to make accurate diagnostic predictions.
Based on available project data, the project will perform an economic evaluation to determine the cost-effectiveness of using MOMICS biomarkers in clinical practice.
The project is currently in the clinical trial phase (HT-PREDICT, HT-ENDO, HT-TREAT) to validate the biomarkers, meaning it is not yet at industrial scale.
Based on available project data, there is no specific mention of patents or licensing agreements, though the project aims to develop a plan for implementation as companion diagnostics.
The project is producing ethical and legal guidelines specifically for the use of artificial intelligence in the clinical setting.
The project period runs from 2023-03-01 to 2029-02-28, suggesting that full validation and implementation plans will be finalized by early 2029.
The consortium is heavily research-oriented, consisting of 14 partners across 7 countries. It is dominated by academic and research institutions (9 universities and 3 research centers), with only 1 industry partner (7% ratio). This indicates the project is currently focused on clinical validation and scientific proof-of-concept rather than immediate commercial manufacturing.
Contact the Institut National de la Santé et de la Recherche Médicale (INSERM) in France.
Contact us to identify potential licensing opportunities for MOMICS biomarkers.
