How AI and Analytics are Reshaping Pharma Track and Trace
Pharma track and trace systems were built to answer one question: did this product move through the supply chain correctly? For years, that was enough. Generate the serial number, record the aggregation, send the EPCIS event, confirm receipt at the portal. Compliance achieved. But the data those systems generate every single day is capable of answering far more important questions, if anyone bothers to ask them.
Understanding where the data lives
Level 3: Site Operations is where the physical work happens. Packaging lines, batch records, label printing, barcode verification. The most granular data in the supply chain. Also the least analyzed.
Level 4: Enterprise T&T is where line-level data gets consolidated and prepared for regulatory reporting. EPCIS events, aggregation hierarchies, dispatch records. The complete picture of what left the facility and in what condition.
Level 5: Regulatory Layer is where data crosses into the regulatory domain. National portals, NMVOs, verification routers used by regulators, wholesalers, and pharmacies.
Most analytics efforts operate within a single level. The real value comes from connecting all three.
What AI enables across these levels
Diversion detection: A serial number verified in a market it was never shipped to is a red flag. Without AI, detecting it requires manual investigation. With AI, it becomes a real-time alert.
Predictive exception management: L3 data contains patterns that precede exceptions. AI models trained on historical production data can flag high-risk conditions before exceptions occur, not after.
Audit intelligence: Reconstructing a product's chain of custody from packaging line to point of dispense today is slow and manual. An AI layer across L3, L4, and L5 does it in seconds.
Why most deployments don't get here
Track and trace projects are scoped as compliance projects. Analytics is rarely in scope and even more rarely funded. The result: a fully operational system generating high-value data every day, with a reporting layer that extracts only the minimum required for submission.
The AI and analytics layer is not an add-on. It is the next maturity level for every organization that has already solved the compliance problem.
Prepared by: Ahmed Gamal | Engineering Director & Solutions Architect at Origin Technology