Computational Modeling

• Early and preventive interventions

• Evidence-based risk stratification

• Data-driven decision-making in healthcare and public health systems

Leveraging multi-omics data and advanced computational modeling, we provide predictive insights, experimental validation, and translational applications to support clinical and research decisions.

Predictive Analysis

AI-driven models analyze genomic, proteomic, and clinical datasets to identify biomarkers and generate actionable risk assessments.

Health App & Pilot Studies

Our integrated digital platform supports clinicians and researchers by providing real-time decision support. Pilot studies are underway in public hospitals and private clinics to evaluate usability, clinical relevance, and workflow integration.

Experimental Validation & Polygenic Risk Assessment

Biomarkers are experimentally validated in collaboration with LifePlus, and academic laboratories. Concurrently, polygenic risk scores are calculated to assess individual susceptibility and inform precision medicine strategies.