Quantitative signal detection across the lifecycle
Run established disproportionality methods over your full safety database, manage masking, stratification and thresholds, and move every signal of disproportionate reporting through a configurable, fully audit-trailed review workflow — aligned to GVP Module IX.
Every method starts from one 2×2 contingency table
Disproportionality analysis compares the observed reporting of a drug–event pair against what would be expected if there were no association. PVgenix computes all four established statistics from the same counts, so reviewers see a consistent, cross-checked read on each pair.
Reports in the database, cross-tabulated by drug and event. Cell a — reports naming both — drives the signal.
Case volume shapes statistical signal detection
Disproportionality methods compare observed reporting against expected patterns, so their results are most meaningful where case volume supports them. PVgenix surfaces strength and stability together, and applies masking and subgroup analysis so genuine signals are not hidden by high-volume reporters.
Identify drug–event pairs whose disproportionality is suppressed by a dominant co-reported product, and re-run the analysis with the masking term removed.
Stratify by age, sex, region, seriousness and reporting period to control confounding and expose signals concentrated in a subpopulation.
Set the signalling rules per method — PRR ≥ 2 with χ² ≥ 4 and N ≥ 3, EB05 ≥ 2, IC025 > 0 — tuned per product family and reviewed on a fixed cadence.
From statistical flag to documented disposition
A quantitative flag is the start, not the conclusion. Every signal moves through a structured, role-gated workflow where qualified personnel validate, prioritize, assess, and decide — with a complete audit trail from detection to closure, aligned to GVP Module IX.
Detection
Disproportionality runs across the safety database, with masking and subgroup analysis surfacing candidate pairs.
PRR · ROR · EBGMValidation
Confirm the flag is genuine — check data quality, duplicates, confounding and known associations before escalating.
de-duplicationPrioritization
Triage by seriousness, strength, novelty and public-health impact to focus review on what matters most.
risk-rankedAssessment
Medical evaluation of causality, biological plausibility, literature and mechanism, captured as a structured record.
medical reviewRecommendation
Decide and record the action — label change, RMP update, further analysis or no action — with rationale.
action linkageTracking
Signals carry a status through their lifecycle with a clear audit trail from detection to documented resolution.
full audit trailMethods & thresholds
Masking & stratification
Review workflow
You set the rules — the platform runs them, every cycle
Detection criteria are configuration, not code. Tune the signalling rule for each method, decide which subgroups to stratify by, switch masking on for high-volume databases, and define how often the analysis re-runs — all per product family and all version-controlled.
Different thresholds for vaccines, biologics and small molecules — each method tuned independently and stored as a versioned configuration.
Analyses re-run on a fixed cadence against the latest data, so emerging signals are caught between aggregate reporting cycles.
Every threshold change, run and disposition is captured for inspection — who changed what, when, and why.
Signal-detection statistics are screening tools, not proof of causality — they prioritize where qualified review is needed. Scope and thresholds are defined per client agreement.
See quantitative signal detection in action
Request a demo to see disproportionality methods, configurable thresholds, masking, and workflow-driven signal management running on your safety data.