He continued, “We have access to more data today than ever before. The question is how to coordinate and leverage that data to identify the weak links in our processes before they become failures, so we’re ready to act the moment something goes wrong. A concrete example of this is what our organization experienced during COVID-19 vaccine development. We had to be ready to begin shipping product the moment approval came through. There was no time for gradual ramp-up or extended planning cycles — the process was fast-moving and required us to adapt quickly to changes as they happened. We were able to do that.”
He continued, explaining that the capacity for rapid adaptation is the specific thing that health authorities across the world are looking at. “The question they’re asking isn’t only whether your quality systems work under normal conditions,” he said. “It’s whether your organization can respond at pace when conditions change unexpectedly.”
Later on, when asked about emerging risks, Fahmi explained, “Operational dependencies are critical. Manufacturing may have the equipment and the materials, but it also depends on data and preparedness — including timely test results from quality and laboratory teams.”
She continued, “This is why communication between manufacturing and quality functions is so important. Testing in a microbiology or chemistry lab directly affects whether a batch or lot can be released from one stage to the next, and ultimately across the entire product lifecycle. That connection runs in both directions. If a change occurs in manufacturing, it can affect product testing — potentially requiring updates to test specifications, analytical methods, or the thresholds we test against, whether for temperature, pH, or other parameters. At the end of the day, those decisions have a direct impact on product quality and, by extension, on patient safety.”
According to her, communication is something that must happen continuously. “The connection between these teams is critical,” she said, “and data is what makes that connection work. We have access to significant amounts of data today, but the more important question is whether we have the right data connecting the right teams at the right time. That is a question organizations need to ask not only within individual functions, but across the broader collaborative framework that ties manufacturing, supply chain, and quality together.”
Both speakers agreed that the use of AI in the area has a lot of potential. However, the technology increases the need for data verification, both as its being fed into the models and then again when the models produce a result. They see it as a tool the primarily speeds up existing processes, which can allow for players in the industry to make decisions at a much faster rate. However, as is often the case, humans must remain in the loop to ensure accuracy.