Events and context-based process data from other sources also should be available. Data storage must handle structured and unstructured information. Implementations can include existing data storage mechanisms, but these may need to be scaled and extended to new types of information. This data storage can be integral to the PAT software or it can be a part of a common data repository.
How do we get there from here?
Creating a PAT software standard will require committed suppliers and end-users working together. We anticipate that common functions will be identified first, and that products will then emerge. We also propose that end-users take advantage of standard PAT software when it’s available.
The first step is to standardize complex measurements. Spectroscopy methods are routinely adapted for PAT. Examples are near infra-red (NIR), Raman, UV-visible, fluorescence, and acoustic. Measurement technologies suitable for pharmaceutical needs must be identified. This will help suppliers meet implementation challenges and simplify deployment.
Presently, we spend a lot of time specifying a measurement for a process application. We would like to see standards created that will reduce required time, and make time commitments more predictable.
In the most advanced implementations, PAT systems are used for monitoring, control, and prediction. In these cases, data needs to be exchanged with systems that perform analysis, control, decision making, and reporting. A good first step for data exchange in advanced implementations is to create standard ways of trading data across existing systems.
Control system architecture impacts
We’ve heard about several efforts to build master plans for deploying innovative measurement technologies. Most are done in isolation without considering effects on control system architecture, existing applications and infrastructure needs. However, any master planning effort has to consider these impacts.
The master planning effort must align strategies and derive specific objectives for infrastructure, applications, integration, and PAT systems. To do this effectively, all functions must be mapped to domains. New functions, such as process optimization and process improvement, should be considered.
For each of these functions, impacts on level and approach to automation must be considered. This master planning exercise will help end users understand their business’ readiness to embrace continuous improvement outlined in the PAT framework.
We all have to deal with existing systems and infrastructure, even when creating PAT software standards. We’ll have to exchange data with existing systems for process control, enterprise resource planning, laboratory information management, and manufacturing execution. A unified schema is critical to facilitate data exchange among these platforms.
Several organizations have developed schemas focusing on standard data related to functions of relevance. These include Analytical information Markup Language (AniML), Batch Manufacturing Language (BatchML), and Business to Manufacturing Markup Language (B2MML). While these schemas have been around for awhile, corporate schemas must be developed to use them effectively. Schema validation services for the entire pharmaceutical industry also will be required to support new PAT software standards.
To facilitate pharmaceutical manufacturing process improvement and innovation, application architectures bow geared to corrective action must instead focus on continuous improvement. Current application architecture domain models must evolve to address continuous improvement.
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REASONS FOR IMPLEMENTING PAT
1. Reduce production cycle times
2. Increase uptime
3. Speed time to market for new products
4. Reduce rejects, scrap, and re-processing
5. Improve operator safety
6. Improve relationships with regulatory agencies
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For risk analysis and mitigation, the root cause of all deviations must be ascertained, so all deviations aren’t treated equally. For process design, it’s necessary to use measurements to determine what’s critical to quality using design of experiments and correlations.
Process understanding requires that knowledge about the process be available for easier analysis. These considerations require revisiting accepted application architectures that support only procedural compliance.
Velumani (Lou) A. Pillai is senior manager/team leader for Drug Product Integrated Automation Solutions with Pfizer Global Manufacturing -- IT. He is working on developing standards, and global IT programs to support widespread adoption of Pfizer’s Right First Time Initiative including Process Analytical Technologies. Martin Warman is senior manager/team leader with Pfizer Global Manufacturing’s Process Analytical Support Group, Global Technology. He leads the team responsible for developing and rolling out standardized PAT systems to support Pfizer’s Right First Time Initiative.
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