Patient Profile Curation

High-quality data labeling and clinical annotation for longitudinal patient journeys using healthcare claims, registry, and EHR/EMR data. Supporting AI, GenAI, and RWE development with accurate model training, validation, and explainability.

What We Label

Clinical phenotypes and disease states

Health outcomes and safety events

Treatment exposure, switching, and adherence

Lines of therapy

Comorbidities and risk factors

Procedures, diagnostics, laboratory results, and biomarkers

Temporal events and longitudinal patient journeys

Methodological Rigor

Clinician-led and expert-reviewed labeling

Standardized definitions aligned with regulatory and HTA expectations

Controlled vocabularies and common data models

Inter-annotator agreement and quality assurance workflows

Full documentation and audit-ready traceability

Use Cases

Supervised and semi-supervised AI / GenAI model training

Outcome validation and phenotyping for RWE studies

Comparative effectiveness and safety research

Signal detection, drug safety, and pharmacovigilance

Discuss Your Project With Us

Ready to get started? Our team of clinicians and researchers is here to help.

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