Century Health launched an AI-enabled real-world evidence platform designed to convert fragmented electronic health records into research-ready datasets, following a $5 million oversubscribed seed round led by Origin Ventures. The company’s Century Health Abstraction & Retrieval Model (CHARM) ingests longitudinal clinical records and integrates claims data, with the company reporting 97% clinical-data abstraction accuracy compared with expert reviewers.
The platform focuses on specialty practices treating chronic conditions outside oncology, an area Century Health described as underrepresented in existing healthcare datasets. The company said CHARM supports disease-specific modeling, comparative-effectiveness analysis and downstream drug-safety research while helping life sciences partners access structured, high-fidelity clinical evidence. Funding will be used to expand the company’s data network, strengthen disease-focused AI capabilities and scale partnerships across the healthcare ecosystem.
For clinicians and biopharma companies, the platform offers deeper longitudinal insight into patient care and treatment outcomes across real-world settings. The effort reflects growing demand for AI-driven infrastructure that standardizes difficult-to-access community-practice data for research, model training and drug development.
Disease-Specific Data Platforms
Century Health Introduced Its CHARM Abstraction Platform
Trend Themes
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AI-enabled Real-world Evidence — Consolidated longitudinal clinical records increasing the fidelity of comparative-effectiveness models and post-market safety research.
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Disease-specific Data Standardization — Curated, condition-focused datasets that reduce variability across community practices and improve signal detection for niche therapeutic areas.
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Community-practice Longitudinal Datasets — Expanded capture of outpatient and specialty clinic care offering deeper real-world trajectories of chronic-disease management outside academic centers.
Industry Implications
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Biopharma Research — High-fidelity, disease-focused evidence streams that refine patient selection, comparative analyses, and downstream safety evaluations for drug development.
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Clinical Decision Support — Enhanced longitudinal data inputs that inform richer risk stratification and treatment-outcome prediction within specialty practice workflows.
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Health Data Infrastructure — Interoperable abstraction platforms that standardize fragmented EHR and claims sources into research-ready, model-training datasets.