Insights from
UBC's Expert Voices

A 95% compliance rate sounds strong, until you calculate what it means at 100,000 cases a year. Here's what's actually hiding in that gap, and the four questions every sponsor should ask before signing with a PV vendor.

AI isn't replacing pharmacovigilance professionals. It's changing how they work. Learn why the centaur model, where humans direct AI rather than defer to it, is emerging as the standard for regulated safety operations.

AI savings numbers are easy to put in a proposal. What's harder to find is what happens when something goes wrong. Here's a framework for pricing in the risk that vendor pitches leave out, plus four questions worth asking before you switch.

From triage to causality assessment, AI is changing how case processing teams work. We break down five areas where automation is making an impact, and the human expertise that still has to anchor every decision.

Psychedelic-assisted therapies are emerging as a promising frontier for treatment-resistant mental health conditions. As the regulatory landscape evolves, robust risk management frameworks will be critical to bringing these therapies safely to patients. UBC explores the current landscape and what approval pathways may mean for sponsors.

Automation and AI get used interchangeably, but they're built for different jobs. Automation handles structured, rule-based tasks with the predictability regulated environments require. AI handles variable, interpretation-heavy work like conversational agents and call pattern analysis. This piece breaks down where each delivers value and how patient services teams can apply both without adding unnecessary complexity.

AI is everywhere in PV conversations, but far less mature in practice. Here's what stood out from Why Summit: Future of PV: validation bottlenecks, signal inflation, and why the real challenge isn't technology.

AI, standardization, and a shifting FDA landscape. Here's what the 2026 RIC Annual Meeting revealed about the future of REMS.

Canada's consent-driven data silos and the U.S.'s regulatory patchwork aren't just administrative hurdles — they're determinants of bias in real-world evidence.