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    Our Focus

    Understand immune responses before they unfold

    Building patient‑specific immune digital twins and AI pipelines for neoantigen discovery and presentation, T‑cell recognition, and therapy response prediction—enabling personalized, adaptive care.

    Our Vision

    Turning immune complexity into actionable intelligence

    Advancing precision medicine through digital immune system modeling, enabling personalized prediction, prevention, and treatment of cancer.

    Our Mission

    Digital twins for disease prediction and drug discovery.

    Developing AI-driven digital immune twin platform that transforms complex biological and clinical data into actionable insights, advancing precision diagnostics, therapeutic decision-making, disease prediction, and immune-focused drug discovery.

    A scientific intelligence that sees, understands, and predicts the immune system

    We build digital twins of the immune system to decode biology, predict therapeutic response, and accelerate breakthroughs in cancer and infectious diseases. Our platform unifies advanced AI with deep immunology to bring clarity, precision, and transformative insight to the future of medicine.

    Our Platform

    • End‑to‑end neoantigen discovery and presentation pipelines for cancer vaccines and T‑cell therapies, with advanced MHC/TCR models.
    • Predicts response and resistance to immunotherapies and identifies biomarkers for patient stratification.
    • Predictive response modeling and in silico “virtual trials”
    • Guided patient stratification,therapy selection, and sequencing of therapies in precision immunotherapy.

    Who We Serve

    • Oncology drug developers building neoantigen-targeted vaccines, T-cell therapies, and checkpoint inhibitors.
    • Precision medicine teams at academic medical centers
    • Cancer institutes needing patient-specific immune modeling
    • Clinical trial sponsors seeking biomarkers
    • Translational researchers integrating multi-omics to accelerate drug discovery

    From patient data to optimized therapy decisions.

    • Multi-omics Profiling

      Ingest genomics, transcriptomics, proteomics, immunopeptidomics, and tumor microenvironment data from blood, biopsies or liquid biopsies.

    • Neoantigen Identification

      Run AI-driven discovery and presentation pipelines with MHC/TCR binding predictions to prioritize therapeutically actionable targets.

    • Immune Digital Twin Construction

      Build patient-specific immune–tumor models simulating antigen presentation, T-cell recognition, and cytokine networks.

    • Therapy Simulation

      Predict response/resistance to vaccines, T-cell therapies, and checkpoint inhibitors via in silico virtual trials.

    From multi-omics data to neoantigen-driven therapeutics.

    Multi-omics Profiling

    Integrate genomics, transcriptomics, proteomics, immunopeptidomics, and tumor microenvironment data from patient cohorts or preclinical models.

    Neoantigen Discovery

    AI-powered identification of therapeutically actionable neoantigens for drug discovery and vaccine design, prioritizing high-affinity MHC/TCR targets.

    Immune Digital Twin Construction

    Build cohort- or patient-specific immune–tumor models simulating antigen presentation, T-cell recognition, and immune network dynamics.

    Therapy Simulation

    Predict immunogenicity, response, and resistance for neoantigen vaccines, T-cell therapies, and combinations via in silico screening.

    Optimization & Prioritization

    Rank candidates by predicted efficacy, identify biomarkers, and generate data packages for preclinical validation and IND-enabling studies.