Latest Articles

  • The Next Test for AI in Pharmacovigilance Is Trust, Not Accuracy

    An AI model can be right and still not be trusted. That’s what Bristol Myers Squibb (BMS) found six months into rolling out AI-powered adverse event processing: while F1 performance scores were tracking upward, the audit trail found reviewers still reopening cases the system had already cleared. read more

  • An Interview With Dave Miller, Ph.D.

    Early formulation decisions can make or break a program, yet they’re often made under significant data constraints. What are the most common mistakes sponsors make when they rush that decision, and what does it typically cost them downstream? read more

  • AI Technologies in Pharmacovigilance

    Leading pharmaceutical companies are predominantly applying AI to case intake and early case processing in PV, where rising Individual Case Safety Reports (ICSRs) volumes and diverse report formats have made manual handling increasingly unsustainable. AI is used to support data intake, extraction, and transformation up to the point where information can be integrated into the safety database, while downstream steps like case assessment and medical review largely remain human-led. read more

  • Beyond Case Management

    In large pharma, a staggering 40 to 50 percent of expert pharmacovigilance time is still consumed by tasks far removed from active, scientific PV - such as the mechanics of scheduling reports, tracking down contributors, and managing documents. read more