From blood draw to clinical insight in under 48 hours.

A three-step pipeline that fits into the annual physical — no prep, no sedation, no barrier to access.

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Step One

Non-Invasive Sample Collection

The patient provides a standard venous blood draw at any certified lab, physician office, or urgent care — no bowel prep, no sedation, no procedure room required. The entire interaction takes under 10 minutes and can be added to a routine annual physical.

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Any Certified Lab
Quest, LabCorp, or in-office phlebotomy
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10 Minutes
No prep, no recovery time needed
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Standard Draw
Same as routine CBC or metabolic panel
2
Step Two

AI Biomarker Analysis

We are developing a machine learning model that analyzes a targeted panel of circulating biomarkers including epigenetic cfDNA methylation patterns and inflammatory markers (CEA, CRP). We cross reference against a validated training dataset to generate a polyp risk score with a calculated confidence interval for each patient.

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cfDNA Methylation
Epigenetic signal from circulating cell-free DNA
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CEA & CRP Levels
Established inflammatory & tumor markers
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ML Risk Model
Ensemble classifier trained on clinical data
3
Step Three

Actionable Clinical Report

The physician receives a risk-stratified report within 24–48 hours through our HIPAA-compliant dashboard, designed to integrate with existing EHR workflows. High-risk patients are flagged for follow-up colonoscopy. Low-risk patients are reassured, reducing unnecessary procedures while staying compliant with screening guidelines.

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Risk Stratification
Low / Moderate / High with confidence scores
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HIPAA Compliant
End-to-end encrypted patient data
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EHR-Ready
Designed with future FHIR compatibility in mind for Epic and Cerner integration.

Built on validated science.

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Liquid Biopsy Science
We leverage advances in liquid biopsy — analyzing cell-free DNA shed by pre-cancerous cells into the bloodstream. This field has accelerated dramatically, with companies like Guardant Health and GRAIL validating the core approach for multiple cancer types.
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Ensemble ML Architecture
Our risk model combines gradient boosting, logistic regression, and a neural biomarker encoder to generate a calibrated probability score. Designed to minimize false negatives while controlling false positive rates that drive unnecessary follow-up colonoscopies.
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Clinical Validation Roadmap
Phase 1 is a retrospective study matching blood samples against confirmed diagnosis records. Phase 2 is a prospective cohort. We're designing toward FDA de novo classification as a Class II diagnostic device, following the pathway established by Exact Sciences' Cologuard.