Platform / Signal management
Detect signals early, decide with evidence
Statistical detection, validation and prioritisation across cases, literature and external data, with a complete record of every evaluation and decision.
Set by your thresholds
Every evaluation recorded
Everything signal management needs, in one place
Statistical detection
Disproportionality analysis runs across your safety data at the frequency you choose, using established methods such as PRR, ROR and EBGM.
- PRR, ROR and EBGM, with confidence intervals
- Run on your data at your chosen frequency
- Product–event combinations ranked for review
- Method and parameters recorded with each result
| Product–event | Cases | PRR | ROR (lower CI) | EB05 |
|---|---|---|---|---|
| Product [A] · Pancreatitis | 12 | 3.4 | 2.1 | 2.0 |
| Product [A] · Headache | 48 | 1.1 | 0.9 | 0.8 |
| Product [B] · Rash | 9 | 2.6 | 1.5 | 1.4 |
Example values. Highlighted rows exceed your thresholds.
Cluster analysis
Disproportionality looks at one product and one term at a time. Cluster analysis groups similar cases together, by combinations of symptoms, timing, patient characteristics and batch, so emerging syndromes and patterns stand out even when they are spread across many terms.
- Cases grouped by similar combinations of events
- Clusters by time to onset, age, sex, region and batch
- Related terms brought together into one picture
- Each cluster opened as a potential signal with its cases attached
Example clusters. Clustering methods and thresholds are configured with you.
Safety insights
Dashboards show how each product’s safety profile is developing: case trends, emerging terms, population and regional differences, and the status of every signal, so safety committees spend their time on decisions, not data gathering.
- Case volume and seriousness trends over time
- Emerging terms and fastest-growing events
- Views by region, population and product
- Signal pipeline status for safety committees
| Measure | This quarter | Change |
|---|---|---|
| Cases received | [__] | ▲ [__]% |
| Serious cases | [__] | ▲ [__]% |
| Fastest-growing term | [Term] | New |
| Open signals | [__] | 2 due this month |
Example layout.
Your thresholds
Which methods to use, what counts as a signal and how signals are prioritised all come from your signal management procedures.
- Methods and thresholds per product
- Minimum case counts and statistical criteria
- Priority rules for serious and designated medical events
- Changes approved and versioned
Example rule set based on commonly used criteria.
Connected evidence
Each potential signal comes with its evidence already gathered: the supporting cases, relevant literature and any other data your procedures call for.
- Supporting cases linked and summarised
- Relevant literature from the literature module
- Other data sources added as your SOPs require
- Evidence kept together through the whole evaluation
Explainable scoring
Every potential signal shows why it was raised: the method, the numbers, the threshold it crossed and the cases behind it.
- Method, result and threshold shown together
- Contributing cases one click away
- Clinical context highlighted for the reviewer
- No unexplained scores
Team workflow
Signals move through validation, prioritisation and assessment with clear owners, deadlines and escalation, in line with your procedures.
- Assignment to the right reviewer
- Deadlines from your SOP timelines
- Escalation to safety committees
- Decisions and actions recorded
Full history
Every evaluation, decision and rationale is kept, so the signal sections of your periodic reports and your inspection answers come from one record.
- Every evaluation and decision recorded
- Rationale kept alongside each decision
- Feeds signal sections of aggregate reports
- Searchable for inspections
| Signal | Opened | Status | Decision |
|---|---|---|---|
| Product [A] · Pancreatitis | [date] | Assessed | Label update proposed |
| Product [B] · Rash | [date] | Validated | Under assessment |
| Product [A] · Fatigue | [date] | Closed | Not confirmed |
Four steps, one continuous flow
Detect
Statistical methods on all your data
Validate
Evidence gathered and linked
Prioritise
Your thresholds and risk rules
Decide
Expert assessment and action
AI does the work. Your experts decide.
- Running disproportionality analysis
- Linking supporting cases
- Gathering literature evidence
- Prioritising by your rules
- Drafting evaluation summaries
- Tracking signal status
in the
loop
- Validating signals
- Clinical assessment
- Benefit–risk interpretation
- Deciding on actions
- Communicating with authorities
- Approving closure
vGenix Ai vs other approaches
How signal management works today in most teams, with point tools, and with vGenix Ai.
| Area | Manual process | Point-tool automation | vGenix Ai |
|---|---|---|---|
| Detection | Periodic manual review of listings | Standalone statistics tool | PRR, ROR and EBGM on your data at your frequency |
| Thresholds | Applied inconsistently | Fixed vendor defaults | Your methods and thresholds, per product |
| Evidence | Gathered by hand for each signal | Exported from several systems | Cases and literature linked automatically |
| Explanation | In the reviewer’s notes | Scores without context | Method, threshold and cases shown together |
| Workflow | Email and spreadsheets | Separate tracking tool | Assignment, deadlines and escalation built in |
| Link to reports | Copied into PSURs by hand | Exported manually | Signal log feeds aggregate reports directly |
| History | Scattered documents | Partial records | Every evaluation and decision in one record |
“Point-tool automation” describes separate tools that each automate one step. It does not refer to any named vendor.
What changes, and how we measure it
Every engagement starts with your baseline. These are the measures we track for signal management.
- Time from data to signal review
- Signals reviewed on schedule
- Evaluation cycle time
- Completeness of evaluation records
- Reviewer hours per signal
Part of one platform
Signal management shares its data model, rules and audit trail with every other module, so nothing is re-keyed between them.
Intelligent safety should be one connected operation
Automate the work. Keep the decisions with your experts. Keep the evidence traceable. See it on your own data in six weeks.
6-week pilot on literature monitoring
- Baselines agreed up front
- Configured to your SOPs
- Measured on your own data
- Validation evidence from day one