Getting a drug-safety report to the right specialist can take hours at British drugmaker, GSK. Information arrives through emails, paper mail, faxes and data loggers, and someone must read it, assess its priority and decide where it belongs. As it moves between systems, the same details may be entered and reconciled repeatedly.
GSK wants to change how that information moves through pharmacovigilance, the collection and evaluation of data about medicines’ safety, so specialists can spend more time making decisions that require their expertise. Chiriseri discussed the work as part of the Seeking Value video series presented by Cognizant. She was joined by Mohammad Haque, global head of intelligent enterprise platforms and large deals at Cognizant.
Gabriel Snyder, Newsweek’s executive editor, enterprise, moderated the conversation. Cognizant has worked with GSK on automating drug-safety workflows. Haque said improving individual tasks has limited value when the next team still has to reconstruct or reenter the same information.
The companies are examining how a safety report progresses from its initial arrival through processing, evaluation, regulatory reporting and other responsibilities. Their goal is to preserve information as it moves through those activities while reducing the manual steps required to prepare it for review. GSK’s established safety systems remain a source of truth for much of the company’s information, Chiriseri said, but their existing capabilities should not determine how every workflow operates.
The company wants information to move more efficiently without necessarily replacing the underlying systems. Decisions about automation begin with identifying a problem and determining whether technology can address it reliably. Chiriseri said some tasks are repetitive and predictable, even when highly trained specialists currently perform them.
GSK uses both AI-based and conventional automation to classify incoming safety reports, establish priorities and direct information to the appropriate specialists. Structuring the data as it arrives also helps preserve the context needed for subsequent checks and reviews. Haque sees a larger role for specialized AI agents in connecting those activities across the pharmacovigilance process.
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