Cencora, one of the largest pharmaceutical distributors in the United States, is deploying artificial intelligence to tackle persistent compliance gaps under the Drug Supply Chain Security Act.
Gregg Gorniak, VP of manufacturer operations and data services at Cencora, is leading the company’s push to address incomplete traceability data from its vast network of manufacturing partners.
Cencora is currently connected to and able to receive data from almost all of its approximately 500 manufacturing partners, representing a significant operational achievement in pharmaceutical logistics.
Despite that broad connectivity, Gorniak has highlighted a stubborn problem: around 25% of shipments from manufacturers sending data are still arriving with missing or incomplete information.
That data gap is not a minor inconvenience, as incomplete records under DSCSA rules could legally prevent Cencora from accepting those products into its distribution network.
Gorniak has drawn a clear distinction between manufacturers that send no data at all and those sending data that is incomplete, describing the latter as a situation demanding rigorous exceptions management.
Between 80% and 95% of purchase orders currently carry the required data, but the remaining share represents a substantial volume of product movement that remains at risk of disruption.
The DSCSA framework, which requires full electronic traceability of prescription drugs across the US supply chain, has put enormous pressure on distributors and manufacturers to maintain accurate serialisation records.
AI tools aligned to GS1 EPCIS standards are emerging as a practical solution, capable of classifying exception types, identifying root causes, and triggering proactive workflows including partner outreach and escalations.
These intelligent systems can automate process tracking, reduce compliance noise, and protect drug access by ensuring that data errors are caught and corrected before they cause shipment failures.
By building what amounts to an intelligent compliance layer, Cencora is working to ensure that exceptions are resolved quickly rather than allowed to cascade into supply disruptions affecting patients and healthcare providers.
The approach reflects a broader industry recognition that human-led exceptions management alone cannot keep pace with the volume and complexity of data flowing through modern pharmaceutical supply chains.
Regulatory governance remains a core priority throughout, with AI deployments designed to support rather than override the compliance structures mandated under federal law.
Cencora’s strategy positions the company to maintain product flow while simultaneously meeting the strict traceability requirements that underpin the integrity of the US drug supply chain.