Why More Pharmacovigilance Cases
Shouldn't Mean More Risk.

The pressure nobody needs explained.

If you lead a pharmacovigilance operation in 2026, you already know the numbers are moving against you.

The patent cliff has compressed development timelines. Products that once took years to reach the market are getting there faster, and more of them are arriving simultaneously. At the same time, geo-expansion into emerging markets and new commercial partnerships are multiplying on the sources and volume of adverse event reports landing on your desk.

Regulatory expectations are moving in only one direction. The EU’s evolving PV requirements through 2026 are tightening scrutiny around the collection, evaluation, and dissemination of both ICSRs and aggregate safety data. Meanwhile, public and media awareness of adverse event reporting grows, driving spontaneous reporting volumes higher each year.

Layer on the increasing complexity of clinical programs – first-in-class compounds, rare disease, advanced therapies – and you have a system under pressure from every angle. The cost of PV operations is rising faster than portfolio revenue for many companies. And the industry’s default response has been the same for over a decade: add or find cheaper headcount.

The industry is solving a 2026 problem with a 2010 playbook.

The intake bottleneck nobody talks about.

When volumes spike, the instinct is to treat it as a resourcing problem. More cases, more people. But the real vulnerability is not capacity. It’s where quality enters – or fails to enter – the system.

Case intake is the foundation of every safety decision your organization will make. The accuracy of signal detection, the defensibility of your benefit-risk assessments, the integrity of your PSUR narratives, the completeness of your regulatory submissions – all of it inherits whatever quality was established, or compromised, at the point of intake.

Yet across the industry, intake is still treated as the lowest-skill step in the value chain. It’s staffed as data entry. Structured and unstructured source documents are manually transcribed into safety databases under time pressure, and when volume increases, it’s consistency and accuracy that give way first. Not because people aren’t capable, but because the process itself is designed to break under load.

The organizations adding headcount to solve this aren’t actually solving it. They’re scaling a fragile process. And fragile processes don’t survive audits.

The decision not to scale the commodity way.

At Arriello, our differentiator has never been price. It’s been depth. We’ve built our reputation on understanding therapeutic areas, patient populations, and product behavior at a level that matters when safety decisions are on the line. That’s what has earned us the trust to manage complex, pivotal clinical safety programs – and it’s what all our clients rely on.

As our case management operations expanded – our European Centre of Excellence now complemented by delivery centers in India and China – we faced the same volume pressures as everyone else. The question was whether we’d respond the same way.

In 2025, we made a deliberate decision. Rather than simply scaling capacity, we stepped back and examined the end-to-end case management value chain to identify where modernization would have the greatest impact on both quality and throughput. This wasn’t a technology shopping exercise. It was a structured evaluation of where automation could genuinely strengthen the work our experts do, starting with the process that shapes everything downstream: case intake.

What made this more complex than a typical technology procurement is something that doesn’t get discussed enough – change management. As a service provider, our clients trust us with their safety data. Introducing new ways of working into that relationship requires more than a vendor selection. It requires preparing the organization, redefining processes, and ensuring our people understand not just what is changing, but why.

Why YEZA.ai, and why now?

We reviewed multiple partners. We sat through demos and worked in sandbox environments. We weren’t evaluating AI for the sake of adopting AI. We had a specific problem: ingesting structured and unstructured content at intake, including handwritten source files. We needed a solution that could meet the quality bar our experts and our clients expect.

We chose YEZA.ai because it addressed that problem directly. Not with broad promises about transforming pharmacovigilance, but with a focused capability: accelerating the high-volume, time-critical task of case intake and preliminary data entry that supports validation, verification, and ultimately drives reporting decisions across multiple stakeholders including regulators.