Lynx

LynxCare (lynx.care) provides electronic health record (EHR)-derived real-world data and real-world evidence services for clinical and medical research. Its approach rests on four stated pillars: federated analytics, in which patient data remains inside the hospital and the platform is deployed on-premises or in any Kubernetes-based cloud environment; a European hospital network with on-premises extraction where available, designed for multi-country studies; clinical NLP that enriches structured EHR data with outcomes, lines of therapy, adverse events and disease staging in an OMOP-ready form; and quality assurance consisting of five checks spanning completeness, accuracy, clinical validation, medical review and benchmark matching.

The company curates longitudinal EHR-extracted data assets in oncology, cardiology and mental health, including immuno-oncology, lung cancer, breast cancer, chronic lymphocytic leukemia, multiple myeloma, heart failure, transthyretin amyloid cardiomyopathy (aTTR-CM) and mental health, each described by estimated patient counts, numbers of endpoints and the share of endpoints enriched through NLP. It also offers Sentinel, an OMOP Common Data Model-based system intended to continuously measure, benchmark and improve EHR-derived datasets for regulatory compliance, collaborative studies and translational research. Prospective users can request a feasibility check or a product demonstration, and hospitals can join as data partners.

Business model

LynxCare works with hospitals as data partners, extracting and enriching EHR data on-premises, and makes the resulting data assets and analytics available to research users through feasibility checks, multi-center study support and its Sentinel data-quality system.

Traction

Published data assets cover estimated patient counts including 44,000+ for heart failure, 35,000+ for mental health, 20,000+ for breast cancer, 14,000+ for lung cancer, 5,000+ for immuno-oncology, 2,500+ each for chronic lymphocytic leukemia and multiple myeloma, and 1,500+ for aTTR-CM, with hundreds of endpoints per asset. Scientific output includes a publication on real-world characterization of major depressive disorder and treatment-resistant depression (MOOD project) and posters accepted for ESC Heart Failure 2026 and OHDSI Europe 2026.