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Written by Jim Lehane and David Staunton
7 September, 2023
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4 mins
The requirement for the biopharma industry to accelerate the pace of NPI to meet healthcare demands, has resulted in the industry having a newfound responsibility to launch treatments to patients faster than ever before. IT-OT convergence, advanced data analytics and AI technologies are giving manufacturers the insights to launch and make GMP compliant medicine at an accelerated pace.
Integrating IT-OT systems allows data connectivity across all stages of development including research and development, pilot, clinical and commercialization, through to market launch. By following a “connected by intent” mindset, manufacturers are able to create a seamless flow of data interconnectivity across all layers of business operations and manufacturing. Through this approach, vital information and insights are enhanced by providing contextualized, meaningful data in the moments that matter and to the people who need them.
GMP manufacturers with truly connected systems are finding they can drive productivity and business transformation while benefiting from manufacturing efficiencies, flexibility, agility and security. Shopfloor data flows through the technology stack to the historian and cloud. This blended two-platform approach leads to process transparency with real-time insight into batch and equipment performance to help prevent and reduce batch failures. More than that, manufacturers accelerate molecule to market, improve yield, capacity, cycle times and batch release times, as well as having the capability to reset the cost base for labor, materials and energy. This “connected by intent” mindset drives value for businesses with a focus on accelerated launch, sustainability and retaining a competitive advantage.
Meaningful, contextualized data flowing from the shopfloor, combined with data analytics, has the power to improve the manufacturing process, scheduling and yield. For example, leading life sciences manufacturers are using data from OT systems, such as PLC, DCS and MES, to build process data models that can be used as part of a digital twin to monitor manufacturing process in real time. Manufacturers are able to conduct equipment performance monitoring and process performance failure monitoring, in near real time, ultimately preventing and reducing batch failures.
Although data analytics sits mostly across IT platforms, connecting them to the OT layer brings benefits to the batch release process in terms of process insights and faster access to business-critical information, reducing downtime and system performance.
Access to real-time OT data also allows for real-time scheduling of the process. Historically, scheduled batches might have been paper-based, so the feedback on batch progress was slow. Connecting the IT to the OT systems to enable the data flow from the shop floor results in a more granular, near real-time visualization of what’s happening to the batch, operating at an hour-to-hour or minute-to-minute level. With near real-time information, insights required for NC investigations are available straight away. Connected digital systems optimize schedules, which has a big impact on the reduction of batch errors.
AI can be invaluable in enabling a deeper understanding of manufacturing processes by using multi-variate batch analytics and machine learning for preventative maintenance. By analyzing data from multiple sources, including sensors and devices, AI-powered systems can detect potential faults early on in the production process and predict when processes are deviating from the golden batch profile or when machines are likely to fail. This can help manufacturers improve their efficiency, reduce downtime and maintenance costs and ensure that their products continue to meet the highest quality standards.
Digital transformation is helping to shape the life sciences industry. Connected systems that enable meaningful, contextualized data to flow from the shopfloor to accelerate molecule launch from Phase I and II clinical manufacture in the lab environment, through to Phase III and into commercial manufacture in a GMP factory. During commercial GMP operations this data flow generates insight to drive business outcomes with measurable value for faster, better and leaner manufacturing.