From Signal Detection to Signal Evaluation Report: Why Workflow Control Matters

It's easy to treat signal detection as the goal. Compute disproportionality, flag the drug–event combinations, done. But in pharmacovigilance, a statistical flag is the beginning of the work, not the end of it.

Detection is a question, not an answer

PRR, ROR, and Bayesian measures like EBGM and IC tell you where to look. They don't tell you what a signal means. The reviewer journey — output to interpretation to evidence to documentation to sign-off — is where the real value and the real risk live.

The steps that need to stay connected

• ▹Interpretation: placing a flagged DEC in MedDRA context, including SOC roll-up and SMQ grouping.
• ▹Evidence: gathering internal case context plus external sources (FAERS, EU data, literature) alongside the signal.
• ▹Comparison: looking across historical runs to understand re-signalling and trend movement.
• ▹Documentation: drafting a Signal Evaluation Report that reflects the evidence and the reviewer's reasoning.
• ▹Sign-off: a clear, recorded decision with accountability.

Why control beats automation here

Automation that draws its own causality conclusions creates risk no PV team wants to own. The safer model is human-in-the-loop: surface the structure and evidence, keep every step traceable, and let qualified reviewers decide. Drafting support should be evidence-bound — tied to what was actually gathered — and always under reviewer control.

That's the difference between a tool that produces output and a platform that supports a defensible review: detection, evidence, and documentation stay connected, and the people remain accountable for the judgement.