(l-r) Christopher Darrel, Jack Prior, Leo Xu, Abdel Zamamiri, John Moehnke, Rodney Rietze , Patrick Hyett, Ned Winslow, Brett Duersch, Olav Lyngberg, Michele C D’Alessandro, Daniel Wasser, Gerald Leister, Susanne Stocker, Arne Zilian, Lori Pfahler, Paul Kolosick, Aaron Goerke, Thomas Amirault, Hal Baseman, George Skillin and Josh Eaton
Manufacturing is undergoing massive change due to increasing reliance on digital connectivity. Referred to as Industry 4.0 or the Internet of Things, this change is also impacting our segment of manufacturing as well.
At the same time, the information age has created mountains of data in every field. More data has been created in the past two years than in the entire history of the human race—and in our experience, manufacturing generates more data than any other sector. That being said, the proliferation of data itself is not the disruption. The disruption is the way the data is processed, made available, and ultimately, used to drive outcomes. This includes the ability to combine structured and unstructured data using modern data warehousing technology and advanced statistical modeling. Enhanced by a multitude of technology advances such as software robotics and machine learning, pharma manufacturers can leverage insights from data to optimize product development, quality control, process analytics and more.
To further the opportunities in this area, PDA and its Manufacturing Science and Operations ProgramSM (MSOP), an advisory body, formed a special task force to assist pharma manufacturers with the use of big data to improve regulated product manufacturing and supply chain management. This task force held its first ideation session on Oct. 19 at the Sanofi-Genzyme Research and Development facility in Cambridge, Mass. An ideation session is a specialized gathering where participants outline a problem and brainstorm potential solutions.
With more than 20 industry colleagues attending from a variety of leading bio/pharmaceutical companies, this ideation session provided an opportunity to share ideas, challenges and solutions for the development and implementation of big data strategies for managing manufacturing-related data. Three areas, in particular, were identified as critical to transforming the current state of manufacturing:
Manufacturing Information Model: Defining standards and structure to promote the ease of interoperability and exchange of information
Process Robustness: Efficient and effective validation approaches across unit operations, equipment and raw materials
Inexactitude versus Precision: Using data throughout its lifecycle for enhanced computerized system controls
Each of these areas will have its own work team comprised of industry stakeholders who will collaborate on developing documents on how success can be achieved in these areas. The ultimate goal of these collaboration efforts is to help ensure that the industry achieves levels of excellence in the area of manufacturing reliability leading to high levels of quality and compliance. While we are at the start of our task force efforts, much has already been done in individual areas. By sharing these practices and further capitalizing on common initiatives, we can drive the industry to significantly greater levels of product success. The task force is also looking for volunteers to assist in these three areas. If this interests you, please contact PDA’s Volunteer Coordinator.
These areas of focus will be further explored and advanced during a dedicated 2018 PDA Manufacturing Intelligence Workshop in March following the 2018 PDA Annual Meeting. This workshop will combine a broader introduction on topics such as big data, digital quality management, machine learning and information security with the latest information on the three areas specified above. This workshop, as well as the task force, is a great opportunity to be part of the industry’s efforts to advance the use of big data in manufacturing and supply chain management. Please join us by volunteering for one of the three task force topics above, participating in the workshop, or both!