Core Capability 1
VUS Resolution
Resolving Clinical Uncertainty
Our vision is to significantly reduce 'Variants of Uncertain Significance' in clinical practice. We transform VUS results, which create patient anxiety and clinical uncertainty, into definitive, actionable insights that enable confident clinical decision-making.
The VUS Challenge in Clinical Practice
A significant percentage of genetic tests—up to 40% in some hereditary cancer panels—return Variants of Uncertain Significance (VUS) results, creating challenges for patients and clinicians.
For the Patient
VUS results create anxiety and uncertainty. Patients have identified genetic variants but lack clear guidance on their clinical significance.
For the Clinician
VUS results limit clinical decision-making. Clinicians must rely on family history and population-level risk assessment rather than precise genetic information.
For the System
VUS results can lead to increased surveillance, unnecessary procedures, and healthcare costs due to uncertainty-driven medical decisions.
AI-Powered Variant Classification
We address VUS through advanced computational analysis and machine learning. Our approach evaluates every variant from first principles using comprehensive biological context rather than relying solely on existing variant databases.
Key Capabilities Deployed
- Advanced AI Models: Large-scale neural networks trained on genomic and functional data.
- Bioinformatic Analysis Engine: High-throughput computational analysis for variant assessment.
Tactical Breakdown
Our operational approach is a multi-stage process designed for maximum impact. Each step builds upon the last, creating a cascade of strategic advantage.
Initial Classification
Advanced AI Analysis
Clinical Classification
Target Audience & Value Proposition
Health Systems & Diagnostics Labs
We are your outsourced certainty engine. We take your most ambiguous cases and deliver the clear, actionable answers your clinicians and patients are desperate for. This is a high-margin service that closes your "actionability gap."