The BioTwin platform
A virtual twin engine that integrates multi-modal health data
into personalized, predictive models.
What is a virtual twin?
A virtual twin is a computational model of an individual's health state, built from their unique biological, behavioral, and clinical data. Unlike static health records, virtual twins are dynamic: they update with new data and can simulate how different interventions might affect outcomes.
BioTwin's engine processes longitudinal data streams to create these personalized models, enabling healthcare organizations to move from reactive care to predictive, preventive medicine.
Data modalities
BioTwin integrates five primary data types to build comprehensive virtual twins.
Biomarkers
Blood panels, genetic markers, metabolomics, proteomics
- Lab results
- Genetic tests
- Metabolic panels
Biometrics
Vital signs, body composition, physiological measurements
- Blood pressure
- Heart rate
- BMI
- Body composition
Questionnaires
Patient-reported outcomes, lifestyle assessments, symptom tracking
- Health history
- Symptoms
- Quality of life
- Diet & exercise
Medical Records
EHR integration, diagnoses, medications, procedures
- Diagnoses
- Medications
- Procedures
- Clinical notes
Wearables
Continuous monitoring from consumer and clinical devices
- Activity
- Sleep
- Heart rate variability
- Glucose
What BioTwin delivers
From individual risk scores to population-level insights.
Risk Stratification
Clinical pilotsIdentify high-risk individuals across multiple disease domains using validated models.
Health Trajectories
Research validationProject future health states based on current data and intervention scenarios.
Cohort Insights
Clinical pilotsAggregate analysis across patient populations for pattern discovery and benchmarking.
Simulation Layer
Early researchModel intervention outcomes before implementation. What-if scenario testing.
Validation status indicates current evidence level. We are transparent about what has been clinically validated versus what is in research stages.
Security & governance
Built for healthcare compliance from day one.
Consent Management
Granular, auditable consent workflows with easy patient control over data sharing.
Privacy by Design
Data minimization, purpose limitation, and privacy-preserving computation techniques.
Flexible Hosting
Cloud (SOC 2 Type II), on-premise, or hybrid deployment options.
De-identification
Advanced de-identification for research datasets while preserving analytical utility.