Digital Twins forHematologic Oncology
Reproducible Functional State Modeling for Translational Decision-Making
Helomnix builds reusable, biology-grounded Digital Twin reference maps that structure multi-omics heterogeneity into interpretable functional disease states — supporting translational stratification, target prioritization, and structured reporting.
Built on curated multi-omics cohorts and proprietary in-vitro state models in collaboration with academic and clinical partners.
Structuring Disease Heterogeneity
Hematological cancers exhibit profound molecular and cellular heterogeneity that is only partially captured by mutation-based or outcome-driven models. Helomnix addresses this challenge by building reusable, state-based digital twins from multi-omics cohorts, providing a structured framework to analyze disease biology and support precision medicine programs.
Why Not Standard Risk Models?
Traditional Approaches Rely On
- Mutation-based genomic classification
- Outcome-trained risk scores
- Trial-specific feature models
These Methods
- Collapse multi-layer biology into single variables
- Cannot explain divergent disease trajectories within the same genomic class
- Cannot be reused across cohorts without retraining
- Do not encode mechanistic state identity
Helomnix Builds
- Outcome-agnostic disease manifolds
- Stable functional state definitions
- Projection-based assignment without retraining
- Structured, mechanism-aware outputs
From static labels to structured biological states.
Digital Twin Infrastructure vs Ad-Hoc Analytics
Biology-First Digital Twins
Built using unsupervised, outcome-agnostic modeling to capture intrinsic biological programs. Patients are represented as positions within a functional disease landscape rather than isolated feature vectors.
State-Based Patient Representation
Organizing patients into interpretable biological states enables consistent stratification across cohorts, supports comparison between studies, and facilitates mechanistic interpretation beyond single biomarkers.
Audit-Ready, Evidence-Traceable Outputs
The platform delivers state definitions, molecular signatures, pathway context, and evidence-traceable reports — designed to integrate into translational research and early drug development workflows.
What Helomnix Supports
All outputs are designed to support scientific decision-making, not to replace it.
Disease Focus
Helomnix focuses on hematological malignancies characterized by deep biological heterogeneity, providing a strong foundation for developing and validating functional, state-based disease models grounded in multi-omics data.
Acute Myeloid Leukemia
Cohort-scale functional state modeling grounded in multi-omics integration, supporting biomarker discovery, target context analysis, and drug opportunity mapping.
Multiple Myeloma
Tumor-microenvironment integration, plasma cell differentiation biology, and longitudinal cohort modeling.
Diffuse Large B-Cell Lymphoma
Image-omics integration, cell-of-origin classification, and spatial microenvironment analysis from digital pathology.
How the Platform Works
Multi-Omics Integration
Transcriptomic, genomic, and microenvironmental data are integrated at the cohort level.
Digital Twin Map
Unsupervised latent programs define a stable reference map of functional disease states.
Cohort Projection
New samples or cohorts are projected onto the reference map without retraining or outcome leakage.
Translational Readouts
State assignments, molecular signatures, and mechanistic annotations delivered through structured reports.
See a Digital Twin Report Example
Preview how structured state modeling translates into actionable translational insight.
Scientific Foundation
Helomnix is built at the interface of computational biology, clinical hematology, and translational research, with a strong emphasis on interpretability by design, reproducibility, leakage-aware modeling strategies, and evidence traceability.
Interpretability by Design
Reproducible Methods
Leakage-Aware Modeling
Evidence Traceability
Collaborative Partnerships
Helomnix collaborates with academic, clinical, and pharmaceutical partners. Each collaboration is structured to align scientific objectives, data governance, and translational impact.
Pilot Studies
Defined translational questions with structured, reportable outputs.
Co-Development
Joint state model development aligned with program strategy and shared scientific objectives.
Programmatic Collaborations
Reusable disease intelligence embedded across programs and disease areas.
Helomnix provides a structured, biologically grounded approach to understanding disease heterogeneity in hematological cancers. By combining multi-omics integration with reusable, interpretable digital twins, we deliver translational infrastructure — not consulting — for precision medicine programs that demand rigor, transparency, and scientific depth.
Explore a Scientific Engagement
Interested in discussing a translational application or analytical engagement? We welcome inquiries from pharmaceutical companies, research institutions, and clinical teams.
Initiate a Scientific Discussion