Define
We turn the objective into a clear plan: cohorts, endpoints, assumptions, and deliverables.
The AI-native biomedical data science company
Turn complex biomedical data into decision-ready evidence.
Vyona combines expert biomedical data scientists, specialized AI agents, and analytical review to deliver rigorous work faster—from raw data through validated analysis.
Clinical dataBiomarkersReal-world evidenceOmics
ANALYTICAL OBJECTIVE
Which biomarker trajectories are associated with improved clinical outcomes?
Analysis agentCohort definition complete · 2,418 participants
Biomarker response by cohortAdjusted for age · sex · baseline
High response n=684Moderate n=1,026Stable n=708
1.00.50
Baseline6 mo12 mo18 mo24 mo
High-response cohort shows sustained improvementp < 0.01
Separate review
Model assumptions checked. One sensitivity analysis flagged for inclusion.
EVIDENCE PACKAGEReady for final review
8/9Experience spanning
Programs & partners
INCEPTION
INCEPTIONStart here · 2–3 weeks
Biomedical Data Assessment.
We assess your data, investigate one defined priority question, identify analytical risks, and deliver a validated plan for the work ahead.
Need deeper execution? Continue with a defined analysis project or an ongoing data science partnership.
What you receive
01
Data readiness assessment
02
Initial analysis of one defined question
03
Analytical risks and limitations
04
Validated plan and recommended next steps
How we work
Humans set direction.
Agents accelerate.
Every conclusion stays connected to its data, methods, assumptions, and provenance.
Investigate
Scientists and specialized agents inspect data, execute analyses, and test alternatives.
Verify
A separate review process examines the methods, code, assumptions, sensitivity analyses, and interpretation.
Selected work
Longitudinal health platform
From health data to publication-ready evidence.
Evaluating clinical and biomarker trajectories to identify patterns associated with improved outcomes.
Reproducible analysis Sensitivity review Evidence package
What we are building
Building toward an autonomous biomedical data science department.
A system that can carry complex investigations from question to reviewed evidence—with human judgment where it matters.
Team
Biomedical expertise.
AI-native execution.
Built by scientists and engineers who know the work.
Co-Founder & CEO
Julie Vaughn
MIT-trained data scientist. Previously worked on clinical trial design at Loyal and biomedical AI for rare disease. Best Applied Paper at ML4H 2025. Emergent Ventures grantee and Co-director of Longevity Global NYC.
MITLoyalML4H
Co-Founder & AI Engineer
Jipeng “Matt” Di
AI systems engineer building agentic systems for biomedical analysis. Previously managed operations for a diabetes patient-management platform across 1,500 hospitals at OMRON Healthcare. Best Applied Paper at ML4H 2025.
OMRONAgentic AIML4H
Have a question worth answering?
Bring us the biomedical question that matters.
Get the biomedical data science capability you need—without months of hiring or assembling contractors.