Patient Digital Twin
Patient data is scattered across EHRs, claims, labs, genomics, and wearables. We unify it all into one living graph — so you finally see the complete patient journey and can analyze it as a whole.
Built for clinical research, pharma R&D, and healthcare analytics teams.
Patient data is everywhere — and nowhere
Duplicate Records
Average percentage of duplicate or near-duplicate patient records across enterprise healthcare systems. Each fragment tells part of the story.
Data Sources
Typical number of systems containing patient information: EHRs, claims, labs, imaging, pharmacy, genomics, wearables, and more.
Chart Review
Average time for manual chart abstraction per clinical trial cohort. Months of work that could be minutes with unified patient graphs.
Regulators demand explainability. Clinicians need complete pictures. Researchers need cohorts fast. But patient data remains trapped in silos, duplicated, and disconnected. You can't analyze what you can't see together.
One patient. Complete history. Full lineage.
The Patient Digital Twin resolves identities across all your data sources and builds a comprehensive, temporal graph for each patient.
Cross-Source Identity Resolution
ML-powered matching handles name variations, typos, and missing identifiers. Confidence scores for every match decision.
Temporal Patient Graph
Every encounter, diagnosis, treatment, and outcome connected with timestamps. Navigate patient history as a timeline.
Relationship Discovery
Automatically identify care teams, facilities, treatment protocols, and patient-to-patient connections (families, cohorts).
Full Provenance
Every data point traces to source record, source system, and timestamp. Meet FDA 21 CFR Part 11 and EMA requirements.
Connect every patient data source
EHR Systems
Epic, Cerner, Meditech, Allscripts — native FHIR and HL7 connectors with real-time sync.
Claims Data
Commercial, Medicare, Medicaid claims. Procedure codes, diagnoses, costs mapped to patient timeline.
Genomics
VCF files, lab results, biomarker panels. Link genetic variants to clinical outcomes.
Pharmacy
Prescription fills, medication adherence, drug interactions from PBMs and specialty pharmacies.
Wearables
Apple HealthKit, Fitbit, continuous glucose monitors. Patient-generated health data streams.
Lab Systems
LabCorp, Quest, hospital labs. Results normalized to LOINC codes with reference ranges.
What teams build with Patient Digital Twin
Cohort Discovery & Matching
Find eligible patients for trials in minutes, not months. Natural language queries across unified patient graphs identify candidates matching complex inclusion/exclusion criteria.
"Find patients with Stage III NSCLC, no prior immunotherapy, EGFR negative, treated at network facilities in last 6 months"
Treatment Pathway Analysis
Map actual treatment sequences across patient populations. Compare outcomes by pathway. Identify protocol deviations and their effects.
Risk Stratification
Score patients by readmission risk, disease progression, or medication adherence — with explanations clinicians can trust and act on.
Adverse Event Detection
Detect safety signals earlier by connecting patient graphs to drug exposure. Trace causality with evidence chains.
Health Equity Analysis
Identify disparities in care access and outcomes across patient segments. Graph structure reveals systemic patterns.
Built for regulated environments
Healthcare data requires the highest standards of privacy, security, and auditability. The Patient Digital Twin meets them all.
Full HIPAA compliance with BAA. PHI encryption at rest and in transit.
21 CFR Part 11 compliant audit trails. Electronic signatures supported.
Type II certified. Annual penetration testing and vulnerability assessments.
Right to erasure, data portability, and consent management built in.
See the Patient Digital Twin in action
Schedule a demo with our life sciences team. Bring your hardest patient data challenges.
Or email hello@xploreintelligence.co.uk