The signal that almost went unnoticed.

Three adverse event reports over two months. Different countries. Different reporters. Similar symptoms. In a spreadsheet-based system, nobody connected them. The fourth report—a fatality—triggered the investigation that found what the first three should have revealed.

Pharmacovigilance isn't about compliance checkboxes. It's about detecting patterns before patients are harmed. Every day of delay is a day patients are exposed to unknown risks.

Case intake that captures everything

A physician calls your medical information line. A patient emails. A sales rep hears something at a conference. A literature search finds a case report. Every intake channel flows into the same system.

Seal captures the complete case: patient demographics, suspect products, concomitant medications, event description, outcomes, reporter information. MedDRA coding happens as you enter—suggested terms, hierarchical coding, consistency checks.

The case is open and documented in minutes, not days.

Causality assessment with full context

Is this drug-related or coincidence? Causality assessment requires context: the patient's medical history, other medications, temporal relationship, dechallenge/rechallenge data, mechanism plausibility.

Seal presents all relevant information for assessment. The physician reviewer sees the complete picture—not a summary someone typed, but the actual data. Algorithm-assisted causality (Naranjo, WHO-UMC) calculates automatically. The reviewer applies judgment with evidence at hand.

Expedited reporting that never misses deadlines

Serious adverse events have reporting deadlines. Fatal or life-threatening: 7 days to FDA, EMA. Serious unexpected: 15 days. Miss a deadline and regulators notice.

Seal calculates reporting deadlines automatically based on case seriousness, expectedness, and regulatory requirements by market. Dashboard shows what's due when. Automated reminders before deadlines. When you submit, the system generates the correct format—MedWatch 3500A, CIOMS I, E2B(R3)—and logs transmission.

Zero missed deadlines because the system won't let you miss them.

Signal detection across your portfolio

One case is an event. Three similar cases might be a signal. But "similar" isn't obvious—different verbatim terms, different products in a class, different patient populations.

Seal's signal detection looks across your entire safety database. Statistical algorithms (PRR, ROR, EBGM) identify disproportionate reporting. MedDRA hierarchy lets you detect signals at preferred term or grouped term level. Temporal analysis shows if reporting rates are increasing.

The signal that took four fatalities to notice? The system would have flagged it after two.

Aggregate reporting without data assembly

PSURs, PBRERs, DSURs, PADERs—periodic reports that summarize safety data over time. In most organizations, someone spends weeks pulling data from the safety database, formatting tables, writing narratives.

Seal generates aggregate reports from structured data. The line listings are queries. The summary tables are calculations. The safety scientist writes analysis and interpretation—the data assembly is automatic.

A PBRER that took three weeks takes three days. And it's accurate because it's not manually assembled.

Benefit-risk that evolves with data

Every product has a benefit-risk profile. New safety data changes that profile. Seal maintains living benefit-risk assessments that update as new data accumulates.

When a new signal is detected, the benefit-risk assessment shows the impact. When you're preparing for an advisory committee or responding to regulatory questions, the current state is always available—not a document from last year that's already outdated.

Integration with quality and complaints

An adverse event often starts as a product complaint. A quality issue might have safety implications. In siloed systems, these connections are manual—someone has to notice and create links.

Seal connects pharmacovigilance to quality systems natively. A complaint with adverse event information automatically generates a PV case. A quality deviation that might affect safety triggers review. Product quality data is available during causality assessment.

Safety and quality are two views of the same underlying concern for patient welfare.