Cut time to regulatory approval by 33.
Your CMC data is scattered across LIMS, ERP, MERS, and dozens of lab systems — each with different formats, terminology, and no shared vocabulary. Fluree unifies it into a reusable Drug Manufacturing Knowledge Asset that accelerates eCTD preparation from 9 months to 6 — and makes every subsequent submission faster.
What Is Regulatory Intelligence
Every drug starts from scratch. It doesn’t have to.
After Stage III clinical trials, the real bottleneck begins. Regulatory compliance teams must integrate thousands of pages of CMC evidence — test results, stability data, batch records, analytical methods, process controls — into one coherent submission. Fragmentation across LIMS, ERP, MERS, and lab systems means every drug starts the integration process over.
Fluree and Semantic Arts combine ontology expertise with knowledge graph technology to create a Drug Manufacturing Knowledge Asset: a unified, semantically structured view of compounds, tests, equipment, processes, batches, and recipes — mapped to the gist-Pharma ontology regulators understand.
Build it once. Reuse it for every drug. Every subsequent submission is faster, more consistent, and more defensible.
Connect any source.
CSV, API, Postgres, Snowflake, Salesforce — Fluree ingests it as-is. No schema migration. No pipelines to maintain.
Search 300+ sources… AVAILABLE SOURCES Salesforce App · OAuth Snowflake Data lake Postgres Database · replica customers.csv CSV · 1.24M rows 1.24M rows staged streaming to Fluree · CONNECTED
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 Regulatory Teams
Six capabilities no LIMS, ERP, or RIM platform gives you on its own.
Module 3 and 2.3 populate from connected data, not manual compilation
Your Drug Manufacturing Knowledge Asset pre-integrates CMC data from every source. Regulatory teams query the graph instead of compiling evidence by hand — Module 3 quality sections populate from verified, cross-referenced data, and the Quality Overall Summary drafts itself.
- Draft preparation: 9 months → 6 months
- Each drug in the same modality is faster than the last
- Every data point traces back to source
The regulatory-aligned foundation from Semantic Arts
gist-Pharma provides the foundational ontology for eCTD competency questions — the same concepts and relationships regulators use to evaluate submissions. Your terminology extends the standard; it doesn’t replace it.
- Regulator-aligned semantic framework
- Extends IDMP-O, Allotrope, and ISA88 standards
- Your terms + industry standards in one governed model
End redundant testing across your CMC working groups
Lab A’s stability study becomes Lab B’s reusable asset. 'Assay,' 'analytical test,' and 'analytical method' resolve to the same concept. Results stored in one standardized vocabulary are visible and reusable across the entire CMC organization.
- Unified CMC vocabulary across every lab and site
- Stability studies, methods, and equipment reuse
- Cut the 18-month CMC cycle to 12 months
When guidance changes, AI surfaces every affected submission
Build a queryable knowledge graph of your regulatory landscape — regulations, guidance, submission requirements, and their relationships. When FDA, EMA, or PMDA guidance updates, affected submissions, data elements, and sections surface automatically.
Answer reviewer questions in seconds, not weeks
Fluree Core logs every data point from source to submission immutably. Time-travel queries show what the data looked like at any moment. When a reviewer asks where a stability result came from — you answer with the full lineage in seconds.
| Capability | Traditional CMC + RIM workflows | Fluree DMKA + gist-Pharma |
|---|---|---|
| eCTD Module 3 preparation | Manual compilation, 9–12 months | Auto-populated from the knowledge asset — 33% faster |
| Terminology across labs | Inconsistent per-site conventions | Universal CMC vocabulary mapped to gist-Pharma |
| Cross-lab data sharing | Siloed, duplicated testing | One governed vocabulary — shared reuse across labs |
| Cross-modality reuse | Each modality starts from scratch | Knowledge asset extends across modalities |
| Regulatory change mgmt | Manual monitoring + spreadsheets | AI surfaces every affected submission automatically |
| Audit defense | Manual research, weeks to answer | Query — source, transformation, approval in seconds |
| Audit trail | Partial, per-system logs | Immutable, cryptographic, source-to-submission |
| Ontology alignment | Proprietary or per-project models | gist-Pharma extending IDMP-O, Allotrope, ISA88 |
| Global site integration | Requires centralized data | Virtual connection across firewalled global sites |
In Production
Live at a Tier 1 Global Pharmaceutical Organization.
We use Fluree to streamline data classification and integration across CMC workflows at a Tier 1 Global Pharmaceutical Organization. We’ve seen faster time-to-market as the result of enabling data-driven collaboration in CMC workflows and eCTD document prep, enabling us to capture upwards of $150M in opportunity cost per month saved.
Gabriel Aviles · Co-Founder, Vitality TechNet
90-day pilot — proof of concept for one modality.
Fluree and Semantic Arts deliver a working Drug Manufacturing Knowledge Asset in 90 days by integrating LIMS and ERP data against gist-Pharma — validated on eCTD competency questions for your chosen modality.
Week 1–4
Vocabulary design
Design your customized CMC vocabulary extending IDMP-O, Allotrope, and ISA88 — rooted in gist-Pharma.
Week 5–8
Data integration & classification
Connect LIMS and ERP systems. Auto-classify data elements against the universal vocabulary with AI.
Week 9–12
Knowledge asset & validation
Deliver a working Drug Manufacturing Knowledge Asset. Validate against eCTD competency questions and generate queryable evidence.
Outcome
A working proof of concept that demonstrates a 33% timeline reduction potential for your specific modality and data landscape — against real eCTD competency questions.
FAQ
- What is a Drug Manufacturing Knowledge Asset?
- What is gist-Pharma?
- Do we need to replace our LIMS or ERP systems?
- How does this handle different terminology across labs?
- What about eCTD v4.0 readiness?
- How long is the pilot?
- Can this work across global sites with firewalled networks?
- What’s the ROI?