• Like cancer, CAD is a multifactor disease that current non-invasive tech fails to assess accurately
• Diagnostic uncertainty in intermediate lesions drives: → up to 60% of avoidable and sometimes dangerous invasive procedures → unnecessary stenting → procedural complications with increased healthcare costs → Poor and inefficient CAD screening and monitoring
• False positives lead to overtreatment. False negatives delay critical intervention. Physicians lack a reliable, fast, non-invasive tool for accurate patient CAD detection, decision and monitoring.

We are building the next generation of AI diagnostic software bringing precision medicine in cardiac imaging to resolve the grey zone in coronary heart disease and provide:

• High negative & positive predictive FFR values
• Visualizes plaque burden + vessel wall
• Accurate first-line test in stable chest pain
• Seamless integration in clinical workflows

BIOME developed a CCTA-driven FFR engine that merges data learning with physics through a unique AI architecture. 

This advanced non-invasive engine will resolve the intermediate lesions clinical “grey zone” in CAD, where diagnostic decisions are currently uncertain.

By combining in-house physics-based computational tools, experimental hemodynamic validation, and multi-factor clinical data, this hybrid model achieves very high accuracy compared to invasive wire-based FFR, offering physics-grade reliability at AI speed.

Physics-driven architecture does not simply look for correlations in imaging data, but models the patient-specific physiological factors in a unified framework.