Smart Medical Coding
Rank-1 model confidence — on real-world verbatims
"Stenosis Channel L4-L5" → Lumbar Spinal Stenosis (89%)
"Neck spasm" → Cervical Spasm (92%)
"Zyrtec (Cetirizine HCl)" → Correct WHODrug Entry (97%)
Automate medical coding. Code faster. Code consistently.
Smart Medical Coding (SMC) is Saama’s AI-powered, agentic coding solution that auto-codes MedDRA and WHODrug verbatim terms in seconds — with a multi-agent workflow, built-in peer review, a full audit trail, and continuous human-in-the-loop learning.
The Value
One source of truth for verbatim coding
SMC eliminates the manual, spreadsheet-driven workflows that slow clinical trials down. Agentic AI transforms error-prone coding — inconsistent verbatims, unscalable peer review, dictionary-upgrade rework — into an intelligent, self-governing, continuously improving system.
Auto-code in seconds, not minutes
Replace manual dictionary lookups with NLP-powered ranked predictions for MedDRA and WHODrug. Coders pick from the top 5 matches instead of searching dictionaries by hand.
Code consistently across studies
Centralized synonym lists, unique-term detection, and cross-study consistency reports eliminate the verbatim-coded-three-different-ways problem.
Stay audit- and submission-ready
Built-in peer review, role-based access, and a 21 CFR Part 11–compliant audit trail keep every coding decision inspection-ready.
Get smarter with every coder action
A human-in-the-loop learning loop captures every approval and rejection, retraining models so accuracy and auto-code rates improve continuously.
The Architecture
A multi-agent coding system, with humans in command
A specialized AI agent handles each phase of the coding workflow — with human oversight at every escalation point.
Parses each eCRF entry into AE and CM verbatims and extracts context — indication, country.
Auto-code AEs to the correct Preferred Term and medications to the correct WHODrug entry, logging the full reasoning chain.
Validates codes against study conventions, checks cross-study consistency, and flags anomalies for review.
Manages dictionary versions, browsing, and up-versioning impact analysis.
Updates the EDC and safety database, logs every decision in the audit trail, and manages human-in-the-loop escalations.
The Workflow
Three roles. One audit trail. Zero spreadsheets.
From verbatim entry to approved code, every term moves through clearly owned roles — with the AI doing the heavy lifting in between.
Verbatim terms flow in from your EDC or via file upload. The manager assigns terms individually or in bulk and tracks status on a live dashboard.
SMC returns the top 5 MedDRA or WHODrug matches with confidence scores. The coder confirms, picks from the ranked list, or runs a manual search and submits for approval.
A peer reviewer approves the code or sends it back with a reason. Approved codes flow to the EDC and safety database, with every decision in the audit trail.
The Platform
Everything coding teams need, built in
The Difference
The only coder that learns from every action
SMC is the only solution in the category with a true human-in-the-loop learning loop that retrains models on every coder action — combined with EDC-agnostic integration and unified query management.
| Capability | Saama SMC | Medidata Rave | Veeva Vault Coder | Oracle Central Coding |
|---|---|---|---|---|
| NLP & Machine-Learning Coding Suggestions | ✓ | ✓ | — | — |
| Human-in-the-Loop Feedback Learning | ✓ | — | — | — |
| Integration with Any EDC System | ✓ | Partial | ✓ | Partial |
| All Historic MedDRA / WHODrug Versions | ✓ | ✓ | ✓ | ✓ |
| Consolidated Query Management | ✓ | ✓ | ✓ | ✓ |
| Export Coded Data (ASCII / XML) | ✓ | ✓ | — | — |
