Features

Managing CMO Networks

By Geri Studebaker | November 14, 2011

Process understanding through shared data

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:
  • Eliminate geography as a barrier to collaboration with CMOs,
  • Avoid process interruptions from lengthy sampling and testing durations,
  • Increase the predictability of quality and yield by identifying causes of process variability and atypical batches,
  • Reduce report preparation and distribution time,
  • Maintain a centralized repository of accurate paper-based data that comply with regulatory requirements and is scalable to accommodate future growth, and
  • Aggregate and contexualize continuous and discrete data from multiple sources to improve process understanding

Increased Collaboration Leads to Quality and Process Improvements

Increasingly EMI software is used for site-to-site and batch-to-batch comparisons that lead to improvements across geographically dispersed manufacturing plants, including operations outsourced to CMOs. This technology is particularly useful for tech transfer when a new plant or CMO is ramping up for production and can benefit from the lessons learned at an existing, more experienced manufacturing facility.

Accurate and rapid tech transfer is key to working with CMOs — from ramping up production of a new drug to making changes in the manufacturing process and for ongoing training. A critical success factor for reducing tech transfer risk is providing on-demand data access and aggregation capabilities directly to end users in a collaborative analytics, trending and reporting environment so that the multidisciplinary tech transfer team can collaborate productively. The most important requirements for this system are:
  • A practical user-centric interface to provide direct on-demand access to all the data from disparate sources,
  • Capture of data from paper records to make it easily available in electronic form,
  • The ability to work with continuous (on-line) and discrete data together,
  • Sharing data, analysis results and reports across disciplines, scales of operation, and geographically dispersed locations (e.g., CMO sites), and
  • Simplifying the preparation and distribution of descriptive (dashboard) and investigational (cause-and-effect) analysis results, as well as automated generation of periodic reviews and reports of batches and campaigns.

Take for example again the pharmaceutical company that needed to gather and share process data with CMOs while preventing the unauthorized disclosure of proprietary information. In this case, technology tools delivered such benefits as improved technology transfer, better visibility into processes and access to data, less time to correct deviations, easier and faster preparation of regulatory filings and records to support FDA inspections and reporting requirements, and fewer disruptions resulting from crises.

With access to data from the CMO, the sponsor organization could easily compare how its CMO was operating to results at its own site. The company was able to make business decisions about quantities manufactured at various locations, monitor quality data to assess product safety and efficacy, and gain insight about the value the CMO was providing. EMI software eliminates geographical barriers to data sharing. Using an enterprise server model (See Figure 1) allows the sponsor to view data hierarchies with information gathered from server locations around the globe.

Benefits to the Sponsor

The following are ways sponsor organizations can benefit from sharing data across the virtual manufacturing network:
  • Pre-empting of any negative impact on process performance by understanding and controlling sources of variability,
  • Faster incident resolution – from weeks to hours — and faster access to data,
  • Reduction in process risks and technology transfer time and costs,
  • Regulatory reports prepared in a fraction of the time usually taken,
  • Significantly lower overall costs of compliance,
  • Better records maintenance and control of intellectual property,
  • More efficient data management across virtual manufacturing networks,
  • Global data sharing and comparison across sites in order to implement best process practices at multiple sites,
  • Batch genealogy integrated with data to ensure correct results from analyses,
  • Better communication and collaboration, and
  • Current knowledge of recipes and processes better maintained

Promoting Successful CMO Relationships

Sponsor organizations can take several steps to ensure success in managing a virtual manufacturing network including CMOs:
  1. Include in legal agreements with CMOs that the sponsor organization will have access to certain types of data. Contracts should address the specific data to be exchanged as well as the frequency and specify the handling of proprietary information and intellectual property.
  2. Mutually agree upon the data to be exchanged. Types of data supported should include discrete and continuous as well as real-time data. (See Figure 2 for types of data required for collaboration.)
  3. Establish KPIs between the company and outsourced manufacturer.
  4. Identify KPIs measurement processes and associated reporting output tools.
  5. Ensure that Critical Quality Attributes (CQAs) are identified and controlled within the Design Space as part of a QbD program.
  6. Set up effective communication channels or teams to facilitate the exchange of information based on the data exchanged. This effort aids in establishing trust and ultimately better collaboration between organizations for process understanding.
  7. Use the system for continuous improvement and troubleshooting — not only for reactive data analysis — to reap the most benefits.

Some pharmaceutical companies may outsource all of their manufacturing to multiple CMOs. A sponsor company, for example, could put in place a QbD program to which its manufacturing partners must adhere. In this case the sponsor does the tech transfer to each of its CMOs and the design space specifications reside at the CMOs. This gives the CMOs the flexibility to incorporate the sponsor’s processes on their own equipment yet allows the sponsor organization to incorporate its control strategy and also allows for trending within the single CMO and across the distributed manufacturing network. An EMI platform is key in this collaborative approach, where data flows between sponsor and CMO for ongoing knowledge management and continuous improvement.

Life sciences companies face a new era of collaboration across the virtual manufacturing network. CMOs are a vital part of the supply chain network; thus sponsor companies working with CMOs must create an environment for effective communication and collaboration. Data sharing across sites and at all stages of development and manufacturing allows for greater process understanding. Technology tools enable better collaboration, reduce technology transfer risks and costs, lower the cost of compliance, create faster response times and overall provide more efficient data management across virtual manufacturing networks. For optimal process performance sponsor organizations and CMOs in partnership need to create a transparent window through which data becomes powerful, shared knowledge.

Reference
1    From International Pharmaceutical Quarterly

Geri Studebaker is vice president, customer operations for Aegis Analytical Corp., a provider of Enterprise Manufacturing Intelligence (EMI) software that provides on-demand access, contextualization, analysis and reporting for life sciences manufacturing, quality and process development data. She can be reached at gstudebaker@aegiscorp.com.