Optimizing Biomedical Data Processing and Standardization to Accelerate Discovery and Innovation
Polly’s multi modal data model provides a unified platform for integrating diverse clinical data sources. By leveraging advanced engineering techniques and scalable ETL pipelines, and LLM-powered metadata extraction and enrichment we harmonize the data from various sources to a Proprietary Data Model.
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Leveraging structured data products from large-scale genomics, treatment, and observational datasets, we enable precise identification of relevant patient cohorts while mitigating confounding variables. AI-assisted cohort identification streamlines the selection of pertinent groups for specific use cases, utilizing complex, multi-modal data.
Elucidata’s proprietary data model facilitates the integration of EHR, genomics, and clinical trial data, enabling the mapping of patient molecular profiles to both approved treatments and investigational therapies in clinical trials.
Predictive modeling, custom visualizations, and AI-driven insights empower clinicians to identify high-risk patients, predict disease trajectories, and recommend personalized treatment plans. These tools also enable the monitoring of patient outcomes across cohorts, optimizing resource allocation.
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