HEOR / Real-World Evidence (RWE) Shops
Illustrative scenario

From a 20-Week PSUR Sprint to a Continuous Safety Signal Process

Every PSUR cycle, your HEOR team faces the same crunch: manually querying Truveta, reconciling real-world findings with EudraVigilance spontaneous reports, and building a safety signal narrative from scratch — all on a timeline that consistently runs 16 to 20 weeks. For a VP of Pharmacovigilance Sciences at a large European pharma under EMA GVP Module VII obligations, that cycle length isn't just an efficiency problem. It means your benefit-risk evaluation is always looking backward, assembled under pressure, with limited capacity to spot emerging signals before they become regulatory issues.

Up and running in ~8 wkFor: VP Pharmacovigilance Sciences
Estimate your payback
~4 mo
Payback period
$2.6M
Est. savings / year
+$1.8M
Year-1 net

Rough estimate — change the numbers to match your business. We scope the real figures with you on a call.

Why PSUR Safety Analysis Takes This Long

The core problem isn't data availability — Truveta and EudraVigilance both hold substantial signal data. The problem is the reconciliation and narrative layer that sits between raw queries and a regulator-ready benefit-risk section. Your HEOR team writes bespoke queries for each cycle, manually aligns RWE cohort findings with spontaneous ArisGlobal case data, and then builds the signal detection narrative from a blank document. That process is inherently sequential: the Truveta analysis has to complete before EudraVigilance reconciliation begins, and the narrative can't be drafted until both are done. Under GVP Module VII timelines, the result is a team perpetually behind, submitting sections that reflect data from months earlier rather than the most current signal picture.

A Continuous Signal Process Built on Your Existing Analytical Logic

An AI Labor Company agent extracts the signal detection logic already embedded in your Truveta query histories and EudraVigilance reconciliation patterns — the therapeutic area-specific criteria, the cohort definitions, the reconciliation rules your HEOR team applies each cycle. It deploys an agent that runs structured monthly RWE safety signal queries against Truveta, automatically reconciles findings with spontaneous report data in ArisGlobal LifeSphere, and maintains a rolling signal narrative that updates continuously rather than being rebuilt from scratch each period. What arrives in your quarterly review queue is a pre-populated PSUR benefit-risk section built from months of continuous signal monitoring, not a 16-to-20-week manual sprint. Teams operating this way typically see 55–75% reduction in PSUR safety analysis effort, with the process running live in roughly eight weeks.

The Business Case: Regulatory Position and Team Capacity

The value here operates on two levels. First, a continuous signal process means you're bringing current, well-documented benefit-risk evidence to each PSUR submission rather than a retrospective analysis assembled under time pressure — a stronger regulatory position with EMA reviewers and a reduced risk of agency questions about signal detection methodology. Second, freeing 55–75% of the HEOR team's PSUR analysis capacity creates real capacity to take on additional pharmacovigilance work: signal investigations, label update analyses, or additional product coverage without proportional headcount growth. For a pharmacovigilance organization at a $1B-$10B revenue pharma, that capacity recovery represents meaningful operational leverage across the product portfolio.

Works with
ArisGlobal LifeSphereTruvetaEudraVigilanceOracle Argus SafetySAS Analytics
Questions

Can the agent handle multiple therapeutic areas with different signal detection criteria?

Yes. The agent extracts therapeutic area-specific query logic and reconciliation rules from your existing Truveta and EudraVigilance workflows, so it can maintain separate signal monitoring processes for different products and indication areas simultaneously.

How does the agent handle signal cases that require clinical judgment — does it make benefit-risk conclusions?

The agent produces structured, evidence-based signal narratives and pre-populated benefit-risk sections, but does not make regulatory conclusions. Every section is queued for the pharmacovigilance VP's review before submission. The agent handles data assembly, reconciliation, and narrative structuring; clinical and regulatory judgment stays with your team.

What does the monthly cadence look like operationally — does it replace our quarterly PSUR review cycle?

The agent runs signal queries and updates the narrative monthly, but the formal PSUR review and submission cycle remains quarterly as required. What changes is that your quarterly review starts from a continuously maintained, current evidence base rather than a fresh 20-week build — compressing the review-to-submission sprint significantly.

Related use cases

Illustrative scenario for healthcare, pharma & life sciences. Figures are example ranges, not guarantees — we scope real numbers with you on a call.

Want this running in your business?

We'll scope an agent for this on a free 15-minute call.

Book a free call