Platform overview
The Biomedical Data Estate
48 intelligence context layers harmonized from 46 verified sources. One drug identity spine. Delivered into your cloud infrastructure.
From public source authorities to your cloud workspace
A three-layer operating model built for enterprise analytics teams.
46 Public Source Authorities
FDA, CMS, NIH, EMA, USPTO, NLM, EMBL-EBI, ChEMBL, UniProt, PubMed, ClinicalTrials.gov, and more.
The Data Developers Processing Layer
Ingestion, harmonization, entity resolution, type correction, join key validation, and lineage monitoring.
Your Analyst Workspace
Governed BigQuery or Snowflake context layers delivered query-ready, without portal exports or ETL handoffs.
One Canonical Identity. Every Drug. Every Source.
The foundation of every context layer is a unified drug identity spine — 567,000+ variant mappings connecting every drug name, identifier, and code across regulatory, clinical, safety, patent, and market data sources.
Hover or focus a node to highlight one of the identity bridges used across the data estate.
Intelligence Context Domains
Filter all 48 context layers by regulatory, clinical, safety, financial, scientific, identity, IP, literature, or ontology domain.
Showing 48 of 48 intelligence context layers.
Drug-target mechanism and bioactivity context
Scientific teams use this context to connect mechanism, target biology, chemistry, assays, and disease evidence.
- Coverage
- 2.5M compounds
- Refresh
- Quarterly
- System label
- Scientific layer • 2.5M compounds • Quarterly
Post-market adverse-event signals and safety reporting context
Regulatory teams use this context to reconstruct product history without parsing authority-specific files.
- Coverage
- 25M+ reports
- Refresh
- Quarterly
- System label
- Regulatory layer • 25M+ reports • Quarterly
Listed patent runway and challenge context
Portfolio and BD teams use this context to model protection runway, challenge pressure, and loss-of-exclusivity timing.
- Coverage
- 15K+ patents
- Refresh
- Monthly
- System label
- IP & Patent layer • 15K+ patents • Monthly
Human protein target biology context
Scientific teams use this context to connect mechanism, target biology, chemistry, assays, and disease evidence.
- Coverage
- 20,370 human proteins
- Refresh
- Quarterly
- System label
- Scientific layer • 20,370 human proteins • Quarterly
Active and historical trial landscape context
Clinical teams use this context to compare activity, geography, sponsors, interventions, and external evidence.
- Coverage
- 519K+ trials
- Refresh
- Weekly
- System label
- Clinical layer • 519K+ trials • Weekly
European authorization and dual-market context
Clinical teams use this context to compare activity, geography, sponsors, interventions, and external evidence.
- Coverage
- 1,500+ products
- Refresh
- Monthly
- System label
- Clinical layer • 1,500+ products • Monthly
Approval pathways, review history, and regulatory status
Regulatory teams use this context to reconstruct product history without parsing authority-specific files.
- Coverage
- 400K+
- Refresh
- Monthly
- System label
- Regulatory layer • 400K+ • Monthly
Label-change history and regulatory event timeline
Regulatory teams use this context to reconstruct product history without parsing authority-specific files.
- Coverage
- 140K+ versions
- Refresh
- Monthly
- System label
- Regulatory layer • 140K+ versions • Monthly
Regulatory exclusivity shield context
Portfolio and BD teams use this context to model protection runway, challenge pressure, and loss-of-exclusivity timing.
- Coverage
- 8K+ exclusivity entries
- Refresh
- Monthly
- System label
- IP & Patent layer • 8K+ exclusivity entries • Monthly
Risk-management requirements and safety-burden context
Regulatory teams use this context to reconstruct product history without parsing authority-specific files.
- Coverage
- 400+ programs
- Refresh
- Monthly
- System label
- Regulatory layer • 400+ programs • Monthly
Current prescribing context, warnings, indications, and dosing
Regulatory teams use this context to reconstruct product history without parsing authority-specific files.
- Coverage
- 54K+ active labels
- Refresh
- Weekly
- System label
- Regulatory layer • 54K+ active labels • Weekly
Medicare pharmacy-channel spend and exposure context
Market access teams use this context to quantify spend, exposure, pricing pressure, and reimbursement mechanics.
- Coverage
- 5K+ drugs
- Refresh
- Annual
- System label
- Financial & Market Access layer • 5K+ drugs • Annual
Research funding momentum and grant linkage context
Clinical teams use this context to compare activity, geography, sponsors, interventions, and external evidence.
- Coverage
- 1.27M grants
- Refresh
- Annual
- System label
- Clinical layer • 1.27M grants • Annual
Biomedical literature evidence context
Evidence teams use this context to connect publications, grants, authors, MeSH topics, and full-text source lineage.
- Coverage
- 10.2M papers
- Refresh
- Monthly
- System label
- Literature layer • 10.2M papers • Monthly
Retail-to-medical billing bridge context
Market access teams use this context to quantify spend, exposure, pricing pressure, and reimbursement mechanics.
- Coverage
- 35K+ crosswalk records
- Refresh
- Annual
- System label
- Financial & Market Access layer • 35K+ crosswalk records • Annual
Negotiated price, payment year, and IRA exposure context
Market access teams use this context to quantify spend, exposure, pricing pressure, and reimbursement mechanics.
- Coverage
- 25+ negotiated drugs
- Refresh
- Annual
- System label
- Financial & Market Access layer • 25+ negotiated drugs • Annual
Product labeling, clinical identity, and substance mappings
Regulatory teams use this context to reconstruct product history without parsing authority-specific files.
- Coverage
- 158K+ labels
- Refresh
- Weekly
- System label
- Regulatory layer • 158K+ labels • Weekly
Reporter, patient, and case-demographic safety context
Safety teams use this context to triage signals with case, reaction, outcome, and label coverage already joined.
- Coverage
- 25M+ cases
- Refresh
- Quarterly
- System label
- Safety & Pharmacovigilance layer • 25M+ cases • Quarterly
Drug-event disproportionality and label-coverage context
Safety teams use this context to triage signals with case, reaction, outcome, and label coverage already joined.
- Coverage
- 60M+ drug-reaction pairs
- Refresh
- Quarterly
- System label
- Safety & Pharmacovigilance layer • 60M+ drug-reaction pairs • Quarterly
Biologic competition, biosimilar status, and IRA timing
Regulatory teams use this context to reconstruct product history without parsing authority-specific files.
- Coverage
- 4K+ products
- Refresh
- Monthly
- System label
- Regulatory layer • 4K+ products • Monthly
Small-molecule approval, patent, exclusivity, and IRA timing
Regulatory teams use this context to reconstruct product history without parsing authority-specific files.
- Coverage
- 40K+ products
- Refresh
- Monthly
- System label
- Regulatory layer • 40K+ products • Monthly
Physician-administered drug spend and HCPCS exposure context
Market access teams use this context to quantify spend, exposure, pricing pressure, and reimbursement mechanics.
- Coverage
- 1K+ HCPCS codes
- Refresh
- Annual
- System label
- Financial & Market Access layer • 1K+ HCPCS codes • Annual
Disease topic hierarchy and synonym context
Strategy teams use this context to normalize indications, rare diseases, synonyms, and cross-ontology disease families.
- Coverage
- 31K descriptors
- Refresh
- Annual
- System label
- Disease & Ontology layer • 31K descriptors • Annual
Cross-ontology disease mapping context
Strategy teams use this context to normalize indications, rare diseases, synonyms, and cross-ontology disease families.
- Coverage
- 25K+ terms
- Refresh
- Quarterly
- System label
- Disease & Ontology layer • 25K+ terms • Quarterly
Longitudinal research funding history
Clinical teams use this context to compare activity, geography, sponsors, interventions, and external evidence.
- Coverage
- 1.1M grants
- Refresh
- Annual
- System label
- Clinical layer • 1.1M grants • Annual
Target-disease evidence and druggability context
Strategy teams use this context to normalize indications, rare diseases, synonyms, and cross-ontology disease families.
- Coverage
- 7.5M target-disease associations
- Refresh
- Quarterly
- System label
- Disease & Ontology layer • 7.5M target-disease associations • Quarterly
Physician-industry relationship and payment context
Market access teams use this context to quantify spend, exposure, pricing pressure, and reimbursement mechanics.
- Coverage
- 16M+ payment records
- Refresh
- Annual
- System label
- Financial & Market Access layer • 16M+ payment records • Annual
Research organization identity and hierarchy context
Data teams use this context as the controlled identity layer for joins across the estate.
- Coverage
- 135K+ organizations
- Refresh
- Annual
- System label
- Identity & Registry layer • 135K+ organizations • Annual
Patent family, assignee, and citation context
Portfolio and BD teams use this context to model protection runway, challenge pressure, and loss-of-exclusivity timing.
- Coverage
- 8M+ patents
- Refresh
- Quarterly
- System label
- IP & Patent layer • 8M+ patents • Quarterly
Outpatient payment policy and rate context
Market access teams use this context to quantify spend, exposure, pricing pressure, and reimbursement mechanics.
- Coverage
- Outpatient payment reference
- Refresh
- Annual
- System label
- Financial & Market Access layer • Outpatient payment reference • Annual
Disease classification and crosswalk context
Strategy teams use this context to normalize indications, rare diseases, synonyms, and cross-ontology disease families.
- Coverage
- 10K+ disease terms
- Refresh
- Annual
- System label
- Disease & Ontology layer • 10K+ disease terms • Annual
Packaged product identity and commercial code context
Regulatory teams use this context to reconstruct product history without parsing authority-specific files.
- Coverage
- 800K+ NDCs
- Refresh
- Monthly
- System label
- Regulatory layer • 800K+ NDCs • Monthly
Human gene identity and approved symbol context
Data teams use this context as the controlled identity layer for joins across the estate.
- Coverage
- 43K+ genes
- Refresh
- Monthly
- System label
- Identity & Registry layer • 43K+ genes • Monthly
State Medicaid spend and unit-cost context
Market access teams use this context to quantify spend, exposure, pricing pressure, and reimbursement mechanics.
- Coverage
- 3K+ drugs
- Refresh
- Annual
- System label
- Financial & Market Access layer • 3K+ drugs • Annual
Physician-administered pricing trend context
Market access teams use this context to quantify spend, exposure, pricing pressure, and reimbursement mechanics.
- Coverage
- Quarterly updates
- Refresh
- Quarterly
- System label
- Financial & Market Access layer • Quarterly updates • Quarterly
Chemical concept classification context
Strategy teams use this context to normalize indications, rare diseases, synonyms, and cross-ontology disease families.
- Coverage
- 900K+ chemicals
- Refresh
- Annual
- System label
- Disease & Ontology layer • 900K+ chemicals • Annual
Pharmacy acquisition cost and real-world price context
Market access teams use this context to quantify spend, exposure, pricing pressure, and reimbursement mechanics.
- Coverage
- Weekly pharmacy acquisition costs
- Refresh
- Weekly
- System label
- Financial & Market Access layer • Weekly pharmacy acquisition costs • Weekly
Provider identity, specialty, and organization context
Data teams use this context as the controlled identity layer for joins across the estate.
- Coverage
- 7M+ providers
- Refresh
- Monthly
- System label
- Identity & Registry layer • 7M+ providers • Monthly
Rare disease ontology and hierarchy context
Strategy teams use this context to normalize indications, rare diseases, synonyms, and cross-ontology disease families.
- Coverage
- 15K+ ontology terms
- Refresh
- Annual
- System label
- Disease & Ontology layer • 15K+ ontology terms • Annual
Curated rare disease gene association context
Strategy teams use this context to normalize indications, rare diseases, synonyms, and cross-ontology disease families.
- Coverage
- 8K+ gene associations
- Refresh
- Annual
- System label
- Disease & Ontology layer • 8K+ gene associations • Annual
Rare disease prevalence and gene-association context
Strategy teams use this context to normalize indications, rare diseases, synonyms, and cross-ontology disease families.
- Coverage
- 11K+ rare diseases
- Refresh
- Annual
- System label
- Disease & Ontology layer • 11K+ rare diseases • Annual
Protein interaction network context
Scientific teams use this context to connect mechanism, target biology, chemistry, assays, and disease evidence.
- Coverage
- 13M+ protein-protein interactions
- Refresh
- Quarterly
- System label
- Scientific layer • 13M+ protein-protein interactions • Quarterly
Assay outcome and target-validation context
Scientific teams use this context to connect mechanism, target biology, chemistry, assays, and disease evidence.
- Coverage
- 1M+ assays
- Refresh
- Quarterly
- System label
- Scientific layer • 1M+ assays • Quarterly
Chemical structure and compound identity context
Scientific teams use this context to connect mechanism, target biology, chemistry, assays, and disease evidence.
- Coverage
- 100M+ compounds
- Refresh
- Quarterly
- System label
- Scientific layer • 100M+ compounds • Quarterly
Full-text evidence and RAG-ready context
Evidence teams use this context to connect publications, grants, authors, MeSH topics, and full-text source lineage.
- Coverage
- 3.8M full-text papers
- Refresh
- Monthly
- System label
- Literature layer • 3.8M full-text papers • Monthly
Clinical drug naming and RxCUI identity context
Data teams use this context as the controlled identity layer for joins across the estate.
- Coverage
- 200K+ concepts
- Refresh
- Monthly
- System label
- Identity & Registry layer • 200K+ concepts • Monthly
Medical language and terminology crosswalk context
Data teams use this context as the controlled identity layer for joins across the estate.
- Coverage
- 3M+ concepts
- Refresh
- Annual
- System label
- Identity & Registry layer • 3M+ concepts • Annual
Chemical identity cross-reference context
Data teams use this context as the controlled identity layer for joins across the estate.
- Coverage
- 200M+ cross-references
- Refresh
- Monthly
- System label
- Identity & Registry layer • 200M+ cross-references • Monthly
Cloud-native delivery model
No portals, no downloads, no custom ingestion burden for your team.
BigQuery Native Sharing
No data movement. Governed datasets land directly in your GCP workspace.
Google Cloud MarketplaceSnowflake Data Sharing
Native share, no ETL required, with scoped product access and schema documentation.
Snowflake MarketplaceCustom Delivery
Other enterprise cloud environments, legal routing, and procurement paths on request.
Discuss delivery