RxLogix has launched a new version of its PVOne.AI platform aimed at helping pharmaceutical companies automate pharmacovigilance workflows including adverse event monitoring, case processing and signal detection.

The US software company said the latest release adds agentic AI capabilities designed to support drug safety teams managing rising case volumes, increasing regulatory demands and pressure to improve review times.

Pharmacovigilance systems are used across the life sciences industry to identify, assess and report medicine safety issues once products are in clinical development and on the market. The area has become a growing target for artificial intelligence tools as companies look to reduce manual workloads and improve consistency.

RxLogix said PVOne.AI is built to work across case intake, literature surveillance, aggregate reporting, data analysis, risk management and safety review processes.

Raj More, chief architect and chief executive officer of RxLogix, said: “Artificial intelligence at RxLogix is not new. Our clients are already benefiting from AI capabilities operating in production today.”

He added: “PVOne.AI moves beyond task-level intelligence toward agentic orchestration across pharmacovigilance. This enables safety organizations to unlock significantly greater efficiency, sharper prioritization and signal detection, and stronger operational intelligence.”

The company said the platform uses domain-trained models, workflow automation, contextual reasoning and human review controls to support regulated environments.

RxLogix claimed the technology can reduce manual effort in case management operations by up to 80%, increase reviewer productivity by up to 75% and deliver up to 50% touchless workflows. It also said the system could reduce false positives in signal detection by up to 50%.

Those figures were released by the company and no external validation data were included in the announcement.

The company said the new platform is designed to integrate with its wider product suite covering case management, reporting, analytics and safety applications.

AI use in pharmacovigilance has accelerated as drug developers and service providers look to manage growing volumes of post-market safety data while meeting FDA and global regulatory reporting requirements. Automation is increasingly being used for triage, coding, literature screening and signal prioritisation, although human oversight remains central to compliance.

The launch highlights continued investment in specialised AI systems built for regulated pharmaceutical workflows rather than general-purpose enterprise tools.