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Process understanding through shared data
November 14, 2011
By: Geri Studebaker
Aegis Analytical Corp.
In the life sciences industry the use of CMOs helps get products to market faster at lower scale-up costs, and provides core competencies in specialized processes and equipment. CMOs increasingly are engaged to help in every stage — from drug development, to manufacturing to packaging and fulfillment — to supplement the internal facilities with additional capacity or as a sole source of drug production for today’s emerging virtual manufacturing organizations. Along with the benefits of outsourcing come challenges and risks to sponsor organizations, including ensuring timely efficient data exchange, managing multiple contacts, successful technology transfer, reliable and consistent product delivery, intellectual property exposure, and many more. Likewise, CMOs face an increased amount of quality control scrutiny both from sponsor organizations and regulatory agencies. The right technology enables sponsor organizations to gather and share data across the virtual manufacturing network for technology transfer and for improved process understanding, process improvement and analysis. Shared and timely access to data promotes effective collaboration between sponsors and their CMO partners, including ongoing training between parties. Challenges of Managing CMOs The increased use of CMOs in process manufacturing can be attributed to the flexibility, improved time to market and reduced scale-up costs they offer to sponsor organizations. This strategy also helps reduce costs from excess plant capacity, alleviate capacity constraints, reduce capital spending, avoid shortages, improve supply chain predictability and can exploit specialized manufacturing operations. But tech transfer, maintaining quality standards and managing process stability and improvement are challenging when a manufacturer works with outsourced sites around the world. Companies are busy managing their own sites, and hiring contractors with various manufacturing processes and disparate — or manual! — data systems adds layers of complexity. Pharmaceutical and other process manufacturing companies realize that extended supply chains in the manufacturing process — especially the widespread use of third-party manufacturers throughout the world — also exponentially increase the risk of quality issues. Life sciences manufacturing companies, for example, demand from CMOs the same level of quality and safety that the FDA, EMEA and other regulatory agencies require of them. For example, the FDA wants outsourced manufacturing to be integrated into the operations of the sponsor organization — with quality audits conducted by sponsors at CMO sites. One FDA director recently stated, “As a result of the undoubtable trend toward outsourcing, FDA is paying closer attention to contract relationships, and sponsors should expect to hear questions during inspections about how their companies are making sure that their CMOs are actually being monitored.”1 Processes and thus quality can vary from site to site — especially when factoring in external third-party manufacturers to the mix. To facilitate consistent quality, sponsor organizations need manufacturing analytics to better understand processes. They need to identify critical quality parameters (CPPs) and key performance indicators (KPIs), and employ real-time monitoring and controls across the virtual manufacturing network. Analytical tools can be part of a Quality by Design (QbD) program that spans the entire network. A common design space provides a single approach to assessing criticality for all aspects of the process. A consistent QbD system provides many benefits to both the sponsor organization and its CMOs. Primarily it ensures continuous improvement in process and product understanding resulting in a more robust commercial product. Secondly a QbD system can improve regulatory control, both in the initial filing and post-approval phases. Additionally it provides tools that allow the sponsor organization to use QbD in manufacturing alongside traditional quality manufacturing. Finally, continuous improvement is achieved through regular, coordinated trending using data from all manufacturing sites. As an example, a pharmaceutical company needed to better manage CMO relationships to ensure consistency in product quality and limit variability and liability. The first step involved putting in place a legal agreement that provided the sponsor organization with access to certain types of data. It is critical that CMOs and sponsor organizations put in place mutually agreed upon data requirements that will aid in process understanding and process improvement. Upfront discussions and planning pay off over the lifetime of the CMO relationship. The second step involved finding and putting in place a common data platform to provide a single view of process data to help mitigate risks and facilitate collaboration between the sponsor organization and its CMOs. Enterprise Manufacturing Intelligence (EMI) software can be used for technology transfer from a sponsor organization to its contractor. Similar CPP comparisons can be made to monitor performance and identify areas for further investigation. Specifically the pharmaceutical company in this scenario sought to:
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