Imagine having all your essential data seamlessly consolidated—harmonized, organized, and AI-ready at your fingertips. That’s the power of Atlases on Polly!
Biomedical R&D generates large amount of data annually and stores them in siloed repositories.
Siloed data is often inaccessible, unstructured, disorganized, and difficult to reuse.
Managing longitudinal patient data and tracking clinical trials is challenging without an effective data management system.
Patient-centric data management systems are hard to build and maintain as it requires multi-modal data harmonization and integration.
An Atlas is a collections of tables with a user defined schema. Designed to combine the flexibility and UX of spreadsheets with the scale, data integrity and query-ability of relational databases. Store, link & retrieve datasets of molecular and clinical data with less than 50 milli-sec latency.
Streamline data prep and accelerate time-to-insights.
Organized tabular layers integrate metadata, treatments, outcomes, and healthcare delivery details like claims and discharge summaries.
Atlases' flattened data model enables seamless exploration of complex clinical data, perfect for cohort creation and comparative analyses.
Linked structured and unstructured data ensure intuitive navigation, adhering to HIPAA guidelines for real-world data use.
Harmonized multi-site patient records support ML model training for predictive diagnostic and prognostic applications.
Harmonization Engine has been utilized by trained experts over millions of datasets across R&D Projects.
multi-modal data products (>10k samples each) developed in last 5 years.
Faster time to
analysis.
Faster in matching indications to targets with access to the right data.
of data wrangling saved across 20+ curation projects.
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You define the criteria. Elucidata's experts run your search on Polly Scout. You review the shortlist.
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Once the knowledge graph is built on direction-graded evidence, your target selection has something to stand on.
Single cell RNA seq and proteomics from different studies become comparable in one query, not a multi-week project.
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Single cell RNA seq, spatial transcriptomics, bulk RNA-seq, and clinical data run through differential expression and cohort comparison on day one.
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Atlas supplies the pre-harmonized data that Cohorter queries. Cohort construction starts from clean, ontology-mapped records.
Atlas is the data and knowledge infrastructure that runs across two Elucidata service engagements, the harmonized, continuously updated foundation the KG is built on and the layer the program team queries.
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Atlas is the harmonized data foundation for spatial and GWAS programs. Single cell RNA seq, spatial transcriptomics, clinical phenotype, and GWAS data share one schema before cohort construction begins in Cohorter.
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Atlas is the data store that ETL pipeline engagements write to. Every harmonized record is queryable from the day the pipeline goes live.
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Atlas provides the ontology-mapped schema that makes cross-study cell annotation consistent across public and proprietary datasets.
We integrate Atlas into your program infrastructure in the model that matches your team's setup.
Web interface for KG exploration, target scoring dashboards, and evidence report generation via Polly Lens.
We wire Atlas into your pipelines via the Polly Atlas REST API, with harmonized data, schema retrieval, and full programmatic access.
The Atlas MCP Server connects your AI tooling directly to the Atlas data corpus. 7.15M PMC papers and 260k GEO datasets, queryable in plain language. In production as of Q2 2026.
Query-driven research interface that surfaces Atlas data alongside KG evidence for integrated Target ID workflows.
Full API documentation and integration guides available on request.
A data lake stores raw files. Atlas stores harmonized, ontology-mapped records with cross-study entity resolution and a unified schema for multimodal data integration queries.
25+ modalities: single cell RNA seq, spatial transcriptomics, bulk RNA-seq, proteomics, metabolomics, ATAC-seq, methylation, WES, WGS, and clinical phenotype. All go through the same data harmonization pipeline.
Spatial / GWAS / Patient Stratification (Translational), Data Flow Engineering & ETL Pipelines (Infrastructure), and Cell Annotation + Data Harmonization (Data). Atlas is the harmonized data layer those programs query or write to.
Both go through the same harmonization pipeline and live in the same schema after ingestion. Cross-modal queries mixing GEO data and proprietary data run without a separate alignment step.
Continuous ingestion across 30+ repositories. New GEO and PMC datasets processed automatically. Proprietary datasets integrate on the client's schedule.
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