Atlas

Atlas, part of the Polly platform by Elucidata, is a structured repository designed to consolidate, harmonize, and organize multi-modal biomedical data into an AI-ready format. It is built for biopharma R&D teams, clinical researchers, and precision diagnostics teams who need to break down fragmented data silos and accelerate time-to-insights across molecular and clinical datasets.

Biomedical R&D generates enormous volumes of data annually, yet much of it remains siloed, unstructured, and difficult to reuse. Managing longitudinal patient data, tracking clinical trials, and building patient-centric data systems requires multi-modal data harmonization that is both complex and resource-intensive. Atlas addresses these challenges by combining the flexibility of spreadsheets with the scale, data integrity, and queryability of relational databases — enabling teams to store, link, and retrieve datasets with less than 50 millisecond latency.

Core Capabilities

• Collections of tables with user-defined schemas: Atlas is structured as collections of tables that users can define according to their specific research needs, offering flexibility without sacrificing data integrity.
• Multi-modal data integration: Supports the combination of molecular and clinical data, enabling seamless linking of structured and unstructured datasets in a single repository.
• High-speed data retrieval: Datasets can be stored, linked, and retrieved with less than 50 millisecond latency, supporting real-time research workflows.
• Flattened data model: Atlases' flattened data model enables seamless exploration of complex clinical data, making it ideal for cohort creation and comparative analyses.
• HIPAA-compliant data navigation: Linked structured and unstructured data ensure intuitive navigation while adhering to HIPAA guidelines for real-world data use.

Key Workflow Features

• Access longitudinal patient data in one step: Organized tabular layers integrate metadata, treatments, outcomes, and healthcare delivery details such as claims and discharge summaries, making longitudinal patient data readily accessible.
• Streamlined cohort building: The flattened data model simplifies exploration of complex clinical datasets, enabling faster and more accurate cohort creation and comparative analyses.
• Patient-centric data exploration: Linked structured and unstructured data support intuitive navigation across patient records, ensuring compliance with real-world data regulations.
• Diagnostic use case support: Harmonized multi-site patient records are structured to support machine learning model training for predictive diagnostic and prognostic applications.

Harmonization Engine and Scale

• Over 30 ETL pipelines built specifically for multi-modality biological data.
• More than 2 million datasets processed and curated across projects.
• Over 1,500 samples per day processed and harmonized.
• LLM-powered harmonization delivers 10x faster processing speeds.
• More than 200 multi-modal data products, each exceeding 10,000 samples, developed over the last five years.
• Delivers 7x faster time to analysis and enables 75% faster matching of indications to targets.
• Over 1,000 hours of data wrangling saved across more than 20 curation projects.

Atlas is trusted by leading biopharma organizations worldwide and is available through the Polly platform, which supports solutions across discovery, clinical research, precision diagnostics, research informatics, and biologics data management. The platform is built with security and compliance at its core, making it suitable for sensitive biomedical and real-world data environments.