Our Mission
Make convergent health evidence accessible to everyone
Genetic testing gives you one perspective. Blood tests give you another. But neither tells the full story alone. bioArc is built on a simple insight: when multiple independent analysis methods agree on a finding, you can trust it.
We call this evidence convergence. Our engine cross-references ClinVar pathogenic variants, genome-wide association studies, polygenic risk scores, gene interaction pathways, and actual blood biomarker values. When five methods point to the same conclusion, you have a finding worth acting on.
Most health platforms show you data. We show you where your data converges — and where it does not. Discordant findings (high genetic risk but normal blood values) are just as valuable: they show where your lifestyle is successfully managing your genetic predisposition.
The Science
Five analysis methods, one unified view
ClinVar Pathogenic Variants
We scan your VCF file against 705,000+ entries in the NCBI ClinVar database. Variants classified as pathogenic or likely pathogenic are flagged with their associated conditions, review status, and clinical significance.
Genome-Wide Association Studies
768,000+ trait-variant associations from the GWAS Catalog are cross-referenced with your genotype. Statistical associations between genetic variants and health outcomes provide population-level risk context.
Polygenic Risk Scores
For conditions with published PGS models (cardiovascular disease, breast cancer, prostate cancer, Alzheimer's, atrial fibrillation, colorectal cancer), we compute your polygenic risk score and place it in population percentile context.
Gene Interaction Pathways
14 biological pathways (methylation, DNA repair, lipid metabolism, inflammation, detoxification, and more) are analyzed for co-occurring variants that may have compounding effects beyond individual SNP risk.
Blood Biomarker Correlation
When blood test data is available, we cross-reference genetic findings with actual biomarker values. A genetic variant predicting elevated homocysteine paired with an actual elevated homocysteine blood test produces a concordant 5-method finding.
Data & Security
Your genetic data deserves serious protection
We understand that genetic data is among the most sensitive personal information that exists. Here is exactly how we handle it.
AES-256 Encryption
All genetic and health data is encrypted at rest using AES-256. Data in transit is protected by TLS 1.3.
Never Sold or Shared
Your data is never sold, shared, or transferred to third parties. Period. We generate revenue from subscriptions, not data brokerage.
Complete Deletion
Delete your account at any time from settings. All associated data — genetic files, blood tests, chat history — is permanently and irreversibly removed.
Isolated Storage
Each user's genetic analysis is stored in an isolated database. There is no shared table where genetic data from multiple users coexists.
Infrastructure Security
All services run on private internal networks with no public port exposure. Database connections are restricted to application-level access only.
Minimal Data Collection
We collect only what is necessary for the service to function. No tracking pixels, no third-party analytics, no advertising identifiers.
Our Data Sources
Built on peer-reviewed databases
We do not generate proprietary claims. Every finding is backed by publicly available, peer-reviewed research databases.
ClinVar (NCBI)
705,000+ variant entriesThe gold standard for clinical significance of human genetic variants. Maintained by the National Center for Biotechnology Information.
GWAS Catalog (NHGRI-EBI)
768,000+ trait associationsCurated collection of published genome-wide association studies. Joint effort of NHGRI and EMBL-EBI.
PGS Catalog
Polygenic score modelsPublished polygenic score models for computing composite genetic risk from multiple variants.
CPIC Guidelines
546 pharmacogenomic entriesClinical Pharmacogenetics Implementation Consortium guidelines for gene-drug interactions.
Who We Are
Built by health optimizers, for health optimizers
bioArc was born from a simple frustration: genetic testing and blood testing exist in separate silos. We built the convergence engine we wished existed — a platform that connects the dots between your DNA and your blood chemistry.
Nikola Alexandrov
Founder & Lead Developer
Software engineer with a background in bioinformatics and health optimization. Built the GeneScan analysis engine and the multi-method convergence framework that powers bioArc.
Get in touch
Questions about the platform, data security, or partnership opportunities? We are happy to help.
Ready to see what converges?
Upload your genetic data and blood tests. Get evidence-based insights backed by 1.4 million research entries.