H1ST-AI-MON-003 · Task 2.3
The signal no single site can see
A signal you catch between reviews protects patients; one that waits for the next manual roll-up doesn't. The Safety Signal Detection Agent applies signal-detection algorithms over data aggregated from your safety database across all sites, surfaces reportable events early, and suggests medical coding — so your reviewers move from detection to assessment without the aggregation lag, cutting signal-to-review time by up to half.
The grind you know
The signal that matters most is the one no single site can see — it only appears when events across all your sites are put together. But manual aggregation happens periodically, coding backs up, and a pattern that should have triggered a review can sit quietly undetected in the gap between one safety data review and the next. That gap is exactly where you don't want to be blind.
Part of the Risk-Based Monitoring family
Risk-based monitoring & safety oversight.
A signal you catch between reviews protects patients; one that waits for the next manual roll-up doesn't. The Safety Signal Detection Agent applies signal-detection algorithms over data aggregated from your safety database across all sites, surfaces reportable events early, and suggests medical coding — so your reviewers move from detection to assessment without the aggregation lag, cutting signal-to-review time by up to half.
The agent pulls and aggregates events across all sites from the connected safety database.
Signal-detection algorithms surface disproportionate patterns and reportable-event candidates study-wide.
It proposes medical coding for each event and routes reportable candidates to safety reviewers with the supporting evidence.
Capabilities
Applies disproportionality and pattern-based signal-detection methods to identify events occurring more than expected across the study population.
Integrates with the safety database to aggregate events across all sites, so patterns invisible at a single site become visible study-wide.
Suggests MedDRA-style coding for reported events, giving safety reviewers a starting point that speeds coding and consistency.
Flags events meeting reportability criteria as they aggregate, reducing the lag between an event and a safety review decision.
In practice
Where the agent shows up in the day-to-day of a live trial — the moments the grind usually lives in.
An event rate that looks like normal variation at any one site is a real signal once the sites are combined. The agent aggregates events across all sites from the safety database and applies signal-detection algorithms, so the study-wide pattern becomes visible.
Reported events pile up waiting to be coded before anyone can assess them. The agent suggests MedDRA-style coding for each detected event, giving reviewers a consistent starting point that moves them from detection to assessment faster.
A pattern that should trigger a review can sit undetected between periodic manual roll-ups. The agent flags reportable-event candidates with supporting evidence as they aggregate, shrinking the blind gap between one safety data review and the next.
Proof
Figures shown are pre-launch targets based on internal benchmarks, not guaranteed outcomes.
Medidata Rave
EDC
Gemini / Anthropic LLM
LLM
Who it's for
Recognizes symptoms and adverse events in clinical notes and prompts the right assessment before they're missed.
Learn moreReads source documents with OCR and clinical NLP to surface review findings, each with a confidence score.
Learn moreRuns configurable monitoring rules and Key Risk Indicators, surfacing findings on a severity-ranked dashboard.
Learn morePeace of mind
Every output is generated inside a validated, audit-ready platform, kept under human-in-the-loop control, and mapped to the regulatory and CDISC standards this agent supports.
Walk through it on your own workflow with a clinical-trials expert — no pressure, no obligation, and honest answers, including on the limits.
