Decision Support for Radiologybuilt for Mongolia.
Ark Axiom Bio develops CPU-only geometric analysis software to support radiologists in detecting liver, kidney, and gastric cancer from routine CT and MRI data. The system is designed for hospital pilots without GPU infrastructure, cloud dependency, proprietary scanners, or replacement of clinical judgment. A separate discovery lane packages computational drug and peptide leads for partner-run validation sprints.
CPU-only analysis
JSON or PDF report
No cloud dependency
Final authority stays clinical
CPU
No GPU
DICOM
Native intake
LOCAL
No cloud
Decision-support pilot only. Not a replacement for radiologist judgment, regulatory clearance, pathology confirmation, or clinical signoff.
Current Clinical Status
A hospital pilot track for routine radiology workflows in Mongolia.
Ark Bio is a decision-support layer for liver, kidney, gastric, and related oncology imaging work. It is designed to support radiologists without replacing clinical judgment, changing scanner protocols, or requiring proprietary imaging hardware.
The proposed hospital pilot is tightly scoped: 100 anonymized CT/MRI studies, pathology confirmation where available, blind analysis, weekly metric reports, clinician review, and a six-week go/no-go decision.
Deployment constraint
Under 5 minutes per case, CPU-only execution, DICOM-native intake, JSON/PDF output, and on-premise processing so patient data stays inside the hospital.
Performance on Evaluated Cohorts
Current registry and pilot-track metrics from the hospital proposal deck. Prospective clinical validation and site-specific calibration remain ongoing.
The Diagnostic Engine
A structural interpretation layer clinicians can inspect.
Our engine evaluates tissue architecture across six core dimensions and produces a reproducible structural readout that clinicians can review, audit, and compare across cohorts.
Betti-0 Fragmentation Score
Counts disconnected tissue components and surfaces topological fragmentation in the lesion.
Betti-1 Loop / Void Count
Counts internal loops and void-like structures associated with necrotic or cavity patterns.
Geometric Manifold Index
Measures lesion-surface boundary regularity and lobulated morphology.
Sobolev Gradient Energy
Quantifies boundary-surface instability at the tissue interface.
Wasserstein Signal Drift
Measures intra-patient distance between reference tissue and pathological tissue.
Phase Coherence Index
Measures organizational coherence in tissue signal phase.
The output is not a black-box score alone; it is a structured readout of tissue architecture.
Why This Matters
Diagnostic software should fit the hospital infrastructure that actually exists.
Standard imaging AI often assumes GPUs, cloud connectivity, and specialized deployment support. Ark Axiom Bio was built for the opposite setting: routine imaging, local execution, and six interpretable structural readouts that a radiologist can challenge.
Mongolia is the validation market
The clinical need is concrete: among the world's highest liver and gastric cancer mortality burdens, late-stage presentation, and regional hospitals with limited advanced compute capacity.
The constraint shapes the product
The platform is built for CPU-only execution, local processing, and reviewable structural outputs rather than cloud-first GPU dependency.
The constraint is regional
The same deployment reality exists across Central Asia, Southeast Asia, and emerging market hospital networks in East Asia and beyond.
Mongolia is the starting point; the broader opportunity is clinical infrastructure that needs useful diagnostic support without specialized hardware.
Discovery Platform
Computational therapeutic prioritization, handed to partners for validation.
The same structural evidence discipline used in imaging also supports drug and peptide candidate selection. Ark Axiom Bio can package prioritized leads, stability evidence, and assay work orders; pharma partners, biotechs, or CROs run the experimental validation.
Computational prioritization only. No clinical efficacy, toxicity clearance, drug approval, diagnostic replacement, or wet-lab validation claim is made before partner-run assays.
KRAS G12D molecular glues
Macrocyclic peptide and chaperone-prioritized candidates packaged for partner-run binding, stability, and mechanism assays.
NAV-channel macrocycles
Non-opioid pain lead families prioritized for selectivity, structural retention, and CRO-ready electrophysiology validation planning.
mRNA stability and disease biology
TARDIGRADE, MASLD, fibrosis, and related programs framed as computational leads until external thermal, cellular, or biochemical assays clear.
Public wording
We describe the method publicly as geometry-first structural evidence and computational prioritization. Internal engine architecture, source mappings, and candidate-generation recipes remain trade-secret material reserved for NDA diligence.
Validation sprint
Engagement Model
Bounded validation before any commercial commitment.
The engagement structure is designed for accountability: hospital pilots keep radiologist review and on-premise processing central, while discovery sprints keep wet-lab validation with the partner or CRO before any asset claim is escalated.
Step 1
Bounded Evaluation
A hospital evaluates Ark Bio on anonymized imaging studies, or a pharma/CRO partner selects a computational discovery lane for a paid validation sprint.
Step 2
Partner-Run Validation
Radiologists review imaging outputs, while pharma partners or CROs run wet-lab assays on prioritized therapeutic candidates. Ark supplies the evidence packet and assay work order.
Step 3
Commercial Decision
After gate clearance, the relationship can expand into institutional licensing, a larger validation cohort, asset optioning, or a focused collaboration.