A multi-agent AI streamlines MedDRA and WHODrug workflows with built-in peer reviews, full audit trails, and continuous human-in-the-loop precision.
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.
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.
Centralized synonym lists, unique-term detection, and cross-study consistency reports eliminate the verbatim-coded-three-different-ways problem.
Built-in peer review, role-based access, and a 21 CFR Part 11–compliant audit trail keep every coding decision inspection-ready.
A human-in-the-loop learning loop captures every approval and rejection, retraining models so accuracy and auto-code rates improve continuously.
A specialized AI agent handles each phase of the coding workflow — with human oversight at every escalation point.
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.
And the model keeps learning.
And the model keeps learning. Every approval and rejection becomes labeled training data — so SMC gets more confident on your sponsor-specific verbatims, indication terminology, and unseen drug names, without retraining from scratch.
High-confidence terms code automatically; lower-confidence terms route to review — always with top-5 ranked predictions. No blind auto-coding.
Any current or historic version, managed centrally, with up-versioning impact analysis that flags terms needing re-coding.
Search terms and visualize coding hierarchy, including SMQ and SDG groupings, directly in the UI.
Code drugs to the ATC level for precise submissions; configure terms that bypass auto-coding and trigger automatic queries.
The full coder-to-approver chain captured on every term, with re-coding of previously approved terms supported.
Four query categories — Clarify, Split, Move, Multiple — with ten pre-built query text templates. Replaces spreadsheet-based review.
Inbound/outbound APIs, EDC connectors, and token-based authentication. ASCII / XML export to your safety database.
Every action timestamped and attributable; validation packages support regulatory inspections.
Real-time auto-code rates, pending queues, reviewer throughput — plus coding consistency reports for medical monitors.
Every approval and rejection retrains the models, raising accuracy with every term reviewed.
Delivered on Saama's Life Science Analytics Cloud. Provision per study or portfolio — no on-premise install.
High-confidence terms code automatically; lower-confidence terms route to review — always with top-5 ranked predictions. No blind auto-coding.
Any current or historic version, managed centrally, with up-versioning impact analysis that flags terms needing re-coding.
Search terms and visualize coding hierarchy, including SMQ and SDG groupings, directly in the UI.
Code drugs to the ATC level for precise submissions; configure terms that bypass auto-coding and trigger automatic queries.
The full coder-to-approver chain captured on every term, with re-coding of previously approved terms supported.
Four query categories — Clarify, Split, Move, Multiple — with ten pre-built query text templates. Replaces spreadsheet-based review.
Reuse unique verbatim mappings and build a synonym library that raises auto-code rates study over study.
Inbound/outbound APIs, EDC connectors, and token-based authentication. ASCII / XML export to your safety database.
Every action timestamped and attributable; validation packages support regulatory inspections.
Real-time auto-code rates, pending queues, reviewer throughput — plus coding consistency reports for medical monitors.
Every approval and rejection retrains the models, raising accuracy with every term reviewed.
Delivered on Saama's Life Science Analytics Cloud. Provision per study or portfolio — no on-premise install.
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 Coder | 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) | ✓ | ✓ | — | — |
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