Does this replace our EDC or CTMS systems?

No. Fluree creates a semantic layer over your existing clinical systems. Medidata Rave, Oracle Clinical One, Veeva Vault, Argus, your CTMS — they all stay in place. Fluree connects to them and creates the cross-study intelligence layer that no single platform provides.

How does cross-study entity resolution work?

Fluree Sense matches entities across studies using semantic matching, fuzzy matching, and governed rules. An investigator who appears in three studies resolves to one golden record; an adverse event coded slightly differently across programs resolves through MedDRA hierarchy. Every resolution includes confidence scores and is auditable.

Can this accelerate SDTM transformation?

Yes. Mapping decisions, variable classifications, and controlled terminology applications become reusable knowledge assets. When a new study begins, the system suggests mappings based on your historical patterns — subsequent studies in the same therapeutic area transform 40–60% faster.

How does this handle CDISC controlled terminology?

ITM manages CDISC CT alongside MedDRA, WHO Drug, SNOMED, and your organization’s custom terms — all in one governed system. When CDISC releases new terminology versions, ITM manages the transition with cross-vocabulary alignment, so historical data stays connected.

What about unstructured clinical content?

Fluree CAM extracts entities and relationships from clinical protocols, SAE narratives, investigator brochures, and other unstructured documents into the same knowledge graph — so a query can span structured trial data and unstructured clinical content together.

Clinical data that connects across studies.

Q: What is clinical data intelligence?

Clinical data intelligence connects fragmented trial data — from EDC, CTMS, safety databases, and lab platforms — into a governed semantic knowledge graph. It enables cross-study entity resolution, quality-aware data lineage, and reusable transformation assets that make every subsequent study faster and more reliable.

Q: Is the audit trail 21 CFR Part 11-ready?

Yes. Fluree Core’s immutable audit trail logs every data change with timestamps, user identity, and before/after state. Time-travel queries reconstruct any data point at any historical moment, with cryptographic provenance for data integrity.

Trial data, safety signals, operational metrics — scattered across EDC, CTMS, safety databases, and labs with no shared context. Fluree connects them into a governed clinical knowledge graph where entities resolve across studies, quality travels with the data, and institutional knowledge compounds instead of disappearing when the database locks.

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What Is Clinical Data Intelligence

Every study is an island. Every cross-study question is a project.

Clinical trials generate enormous volumes of structured and unstructured data: demographics, adverse events, lab results, concomitant meds, efficacy endpoints, site performance metrics, safety signals. Each study captures it with its own CRF design, coding conventions, and metadata — and when the database locks, that institutional knowledge disappears.

Fluree creates a clinical knowledge graph that connects trial, safety, and operational data across your entire portfolio — with governed vocabularies, cross-study entity resolution, and quality-aware lineage.

Every mapping decision, every entity resolution, every quality annotation compounds — so each subsequent study starts from accumulated knowledge, not a blank page.

How it works

Three steps.
One platform.

From a raw source to a governed knowledge graph — with answers that trace back to the row they came from.

Connect any source.

CSV, API, Postgres, Snowflake, Salesforce — Fluree ingests it as-is. No schema migration. No pipelines to maintain.

The graph builds itself.

Entities resolve, duplicates merge, and relationships infer in place — no modeling marathon, no manual ontology.

Answers, with receipts.

Ask in plain language. Every answer traces back to the exact row it came from — for humans, agents, and apps alike.

What Fluree Unlocks For Clinical Data

Six capabilities no single EDC, CTMS, or platform
gives you on its own.

Subjects, investigators, AEs — resolved across your entire portfolio

Dr. Chen runs sites in three of your trials. An adverse event is coded differently across programs. Fluree Sense resolves these to golden records automatically — with confidence scores and full lineage. Cross-study analysis goes from months of manual reconciliation to a query.

Subjects, sites, investigators, AEs, meds all resolve
Persist across studies — Phase I signals inform Phase III
Confidence scores + audit trail on every resolution

Reusable mapping assets, not from-scratch each study

SDTM mapping decisions from completed studies become templates for new ones. AI suggests variable-to-domain mappings from your historical patterns. Controlled terminology from ITM keeps coding consistent. Each new therapeutic-area study starts from accumulated knowledge, not a blank page.

Mappings accumulate as reusable knowledge assets
40–60% faster for subsequent studies in the same TA
Pinnacle 21 errors drop — same governed logic applies

Signals weak in one study, significant across three

The knowledge graph connects adverse events across your portfolio with resolved entities — same MedDRA term, same WHO Drug code, same patient population characteristics. Query hepatotoxicity signals across your oncology portfolio, normalized by exposure duration — the aggregate answer lands in seconds.

Aggregate analyses across the whole portfolio
Earlier signal detection than single-study analysis
Accelerates PBRER, PSUR, and signal detection workflows

MedDRA, WHO Drug, SNOMED, CDISC CT — one managed system

ITM governs clinical vocabularies alongside your organization’s custom therapeutic-area terms. When CDISC CT releases a new version, ITM manages the transition with cross-vocabulary alignment — historical data stays connected and legacy coded terms map forward cleanly.

MedDRA, WHO Drug, SNOMED, CDISC CT + custom terms
Changes propagate across studies, not per-study forks
Cross-vocabulary alignment for legacy term reconciliation

Immutable, source-to-submission, time-travel

Every data change logged with timestamps, user identity, and before/after state. Time-travel queries reconstruct any data point at any historical moment. Cryptographic provenance ensures integrity — quality annotations travel with the data, not in a separate audit spreadsheet.

Every change auditable; every data point traceable
Time-travel across any study state, any point in time
Quality annotations travel with the data itself

Semantic architecture that adapts with the standard

Clinical data stored as semantic triples with governed vocabularies maps naturally to evolving CDISC, eCTD, and FHIR standards. When SDTM IG v4.0 introduces Non-Standard Variables, the semantic model adapts — no data re-processing. FHIR interoperability is native because RDF and FHIR share the same linked-data principles.

W3C RDF / JSON-LD aligns with CDISC, eCTD, FHIR
Standards transitions = configuration, not migration
Ready for SDTM v4.0, eCTD v4.0, FHIR R5 today

Side by Side

Traditional clinical data management vs.
Fluree.

A direct comparison of siloed CDM approaches against a governed clinical knowledge graph — across the dimensions that drive submission quality and speed.

Capability	Traditional CDM & platforms	Fluree Clinical knowledge graph
Cross-study entity resolution	Manual, months of reconciliation	Automatic — golden records across every study
SDTM transformation	From scratch each study	Reusable assets — 40–60% faster in the same TA
Cross-study safety analysis	Manual aggregate, after the fact	Graph traversal across the whole portfolio
Vocabulary governance	Spreadsheets + per-study conventions	ITM — MedDRA, WHO Drug, SNOMED, CDISC CT in one system
Data lineage	Partial, platform-bound	Immutable, source-to-submission, time-travel
Unstructured clinical content	Not handled or limited	Protocols, SAEs, narratives extracted via CAM
Standards future-proofing	Manual rework per version change	Semantic architecture adapts natively
Data model	Proprietary formats and APIs	W3C (RDF / JSON-LD / SPARQL) + FHIR-ready

In Production

Global pharma teams — live on Fluree today.

We’ve seen faster time-to-market as the result of enabling data-driven collaboration — enabling us to capture upwards of $150M in opportunity cost per month saved.

Gabriel Aviles · Co-Founder, Vitality TechNet

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