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Process Analytical Technology is a system for designing, analyzing, and controlling manufacturing through timely measurements (i.e., during processing) of critical quality and performance attributes of raw and in-process materials and processes with the goal of ensuring final product quality.

It is important to note that the term analytical in PAT is viewed broadly to include chemical, physical, microbiological, mathematical, and risk analysis conducted in an integrated manner.

Process Analytical Technology Tools
There are many current and new tools available that enable scientific, risk-managed pharmaceutical development, manufacture, and quality assurance. These tools, when used within a system can provide effective and efficient means for acquiring information to facilitate process understanding, develop risk-mitigation strategies, achieve continuous improvement, and share information and knowledge. In the PAT framework, these tools can be categorized as:

  • Multivariate data acquisition and analysis tools
  • Modern process analyzers or process analytical chemistry tools
  • Process and endpoint monitoring and control tools
  • Continuous improvement and knowledge management tools

An appropriate combination of some, or all, of these tools may be applicable to a single-unit operation, or to an entire manufacturing process and its quality assurance.

A desired goal of the PAT framework is to design and develop processes that can consistently ensure a predefined quality at the end of the manufacturing process. Such procedures would be consistent with the basic tenet of quality by design and could reduce risks to quality and regulatory concerns while improving efficiency. Gains in quality, safety and/or efficiency will vary depending on the product and are likely to come from:

  • Reducing production cycle times by using on-, in-, and/or at-line measurements and controls
  • Preventing rejects, scrap, and re-processing
  • Considering the possibility of real time release
  • Increasing automation to improve operator safety and reduce human error
  • Facilitating continuous processing to improve efficiency and manage variability
    • Using small-scale equipment (to eliminate certain scale-up issues) and dedicated manufacturing facilities
    • Improving energy and material use and increasing capacity.
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