Case studies / Literature monitoring
Illustrative case study · Literature monitoring
Clearing a literature backlog and cutting screening effort by 65%
How a specialty pharma company used vGenix Ai literature monitoring, from baseline to results.
OrganisationSpecialty pharma company
RegionGlobal, 20+ markets
Portfolio40 marketed products
ScopeLiterature monitoring
Results at a glance
What changed
−70%Screening effort120 → 42 hours a week
ZeroScreening backlogEvery article screened on schedule
100%Screening decisions explainedReason shown for every article
1 dayPublication to caseAs per clients SOP
The challenge
Where they started
- 120 hours a week spent screening abstracts
- A growing backlog of unscreened articles
- Search strings maintained by hand for every product
- Local journal obligations hard to evidence
The solution
What they deployed
- Auto-Query Builder generating and versioning search strategies
- AI screening with the reason for every decision
- Safety extraction and duplicate checks against existing cases
- Direct hand-off of reportable articles to case processing
Implementation
How it was rolled out
Week 1
Scope and baseline
Measured weekly screening hours, backlog and publication-to-case time.
Week 2
Configure
Search strategies generated, reviewed and approved.
Week 3
Validate
Recall tested against known relevant articles.
Weeks 4–6
Run on live data
Run in parallel with the existing process, then reported against baseline.
Before and after
Measured against the agreed baseline
| Measure | Before (baseline) | After |
|---|---|---|
| Weekly screening effort | 120 hours | 42 hours |
| Backlog of unscreened articles | 2,500 | 0 |
| Search strategies under version control | Partial | All |
| Publication to valid case | 30 days | 7 days |
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