Disease Focus
Hematological cancers are among the most molecularly heterogeneous human malignancies. This heterogeneity — in differentiation state, clonal composition, immune context, and preclinical response profiles — is precisely what makes them suited for state-based digital twin modeling.
Why Functional Heterogeneity Matters
Traditional classification systems — based on single mutations, cytogenetic categories, or outcome-supervised models — capture only a fraction of disease complexity. Functional heterogeneity encompasses differentiation programs, immune interactions, metabolic states, and regulatory networks that collectively shape disease behavior and mechanistic context. State-based digital twins provide a structured framework for analyzing this complexity.
Translational Application Across Disease Areas
Designed to integrate into early and mid-stage translational programs, Helomnix Digital Twin models support structured development workflows across hematologic indications.
Cohort stratification in early-phase development
Mechanism-aware target prioritization
Retrospective analysis of trial datasets
Functional enrichment strategy design
Biomarker context mapping across disease states
Each disease model is built as a reusable reference framework — enabling cross-cohort comparability and program continuity.
Acute Myeloid Leukemia
AML
AML exhibits complex clonal architecture, differentiation hierarchies, and adaptive resistance programs. Helomnix structures this heterogeneity into reproducible functional states aligned with translational development needs.
Program Impact
- Stratification support in early-phase combination trials
- Resistance-context mapping for relapse-prone subsets
- Functional enrichment strategy design
- Cross-cohort comparability for longitudinal programs
Multiple Myeloma
MM
Multiple myeloma is shaped by plasma cell differentiation state, tumor–microenvironment interactions, and longitudinal treatment pressure. Helomnix organizes these dimensions into stable biological state frameworks.
Program Impact
- Microenvironment-aware target prioritization
- State-resolved biomarker context mapping
- Retrospective projection of legacy datasets
- Structured support for expansion cohorts
Diffuse Large B-Cell Lymphoma
DLBCL
DLBCL encompasses biologically distinct programs spanning cell-of-origin and spatial microenvironment variation. Helomnix integrates genomic, transcriptomic, and image-based data into structured state models.
Program Impact
- Biological stratification beyond cytogenetic labels
- Target context evaluation across subtype boundaries
- Cohort harmonization across multi-center datasets
- Support for indication expansion strategy
Cross-Indication Continuity
Disease-specific Digital Twin maps are built on a shared analytical backbone, enabling structured expansion from a lead indication into adjacent hematologic programs.
Reusable Disease-State Infrastructure
Disease-specific Digital Twin maps share a common analytical foundation, allowing program expansion across indications without methodological drift.
Helomnix disease models are available for structured translational collaboration.
Initiate a Scientific DiscussionHelomnix digital twins provide structured biological representations for research and translational support. They are not intended for clinical decision-making.