Authenticx Updates AI to Automate Drug Safety Reporting Workflows

The updated solution builds upon the company’s 2024 detection technology, which flags potential safety issues within patient-service calls, chats, and bot interactions. By structuring relevant transcript metadata and pre-populating configurable forms, the platform aims to eliminate the administrative friction that typically delays human review. Manufacturers retain full oversight, with the ability to insert human checkpoints before records are pushed into established systems like Oracle Argus, Veeva, or Salesforce.

Eric Prugh, chief product officer at Authenticx, noted that the goal is not to replace clinical judgment but to remove the manual labor that keeps experts from their primary duties. "PV teams need to reduce the manual work that delays regulated workflows," Prugh said. "These capabilities carry relevant context into the systems they already use, so trained professionals can focus on case qualification and reporting decisions."

Efficiency gains have already been documented in large-scale deployments. In a case study involving a global pharmaceutical manufacturer, supervised AI analysis of over 372,000 interactions reduced manual review times by approximately 90 percent while maintaining 99 percent accuracy. These expanded features are available effective immediately for enterprise healthcare organizations looking to tighten compliance and improve data integrity.