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Case studies / Signal management

Illustrative case study · Signal management

Bringing signal detection, evidence and decisions into one record

How a biotech company used vGenix Ai signal management, from baseline to results.

OrganisationBiotech company
RegionEU and US
Portfolio40 marketed products
ScopeSignal management

Illustrative case study. This is a composite example scenario built to show how vGenix Ai is used. It is not a named client result.

Results at a glance

What changed

Quarterly → monthlyDetection frequencyYour thresholds per product
100%Signals linked to evidenceBy design
100%Evaluations recordedBy design
ContinuousData to first reviewAs per clients SOP
The challenge

Where they started

  • Signal detection run quarterly from spreadsheets
  • Evidence gathered by hand for every potential signal
  • Decisions recorded in meeting minutes
  • Signal sections of PBRERs rebuilt each cycle
The solution

What they deployed

  • Monthly disproportionality analysis with thresholds from SOPs
  • Cluster analysis to find patterns across related terms
  • Supporting cases and literature linked automatically
  • Signal log feeding aggregate reports directly
Implementation

How it was rolled out

Month 1

Scope and methods

Methods, thresholds and workflow agreed from SOPs.

Month 2

Configure and validate

Detection and workflow configured and tested.

Month 3

Parallel cycle

One detection cycle run alongside the old process.

Month 4 onward

Steady state

Monthly detection and committee reviews on the platform.

Before and after

Measured against the agreed baseline

MeasureBefore (baseline)After
Detection frequencyQuarterlyMonthly
Evidence gathering per signal10 hours Few minutes
Decisions with recorded rationalePartialAll
PBRER signal section preparationFew daysFew hours

Illustrative figures. In a real engagement, baselines are agreed before go-live and results measured from platform data.

Next step

Get results like these on your data

We agree the baseline with you, run a pilot on your own data, and report the results.

Recommended

6-week pilot on literature monitoring

  • Baselines agreed up front
  • Configured to your SOPs
  • Measured on your own data
  • Validation evidence from day one
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