More than a decade ago, the U.S. Food and Drug Administration published, Guidance for Industry PAT — A Framework for Innovative Pharmaceutical Development, Manufacturing, and Quality Assurance. In this document, the FDA explained:
The scientific, risk-based framework outlined in this guidance, Process Analytical Technology or PAT, is intended to support innovation and efficiency in pharmaceutical development, manufacturing, and quality assurance.
Since its publication, pharmaceutical and biotech manufacturers have been trying many ways to implement PAT into their production and quality processes.
In an Intech magazine article, Process analytical technology—It’s not rocket science, but it is science, math, control, and IT, Emerson’s Jonathan Lustri highlights the importance of careful planning, organizational commitment, and the right resources in successful implementations.
He opens describing the traditional approach to quality is:
…to perform post-quality-control (QC) testing to verify the batch has met critical quality specifications. If quality specifications are not met, the batch is scrapped. Manufacturers are moving away from this approach toward a quality-by-design approach by combining a higher level of process understanding with more sophisticated real-time monitoring and control.
Fixed process control strategies do not always produce repeatable results.
Variability in raw materials, equipment, and processing conditions are unavoidable and will cause variability in product quality. A more robust strategy is to develop processes with measurement and control capabilities that compensate for process variability and to foster a culture of continuous process improvements.
Jonathan describes the concepts of critical quality attributes (CQAs) and critical process parameters (CPPs). CQAs define what is required to achieve a drug’s health benefit. CPPs are what affect the CQAs. These relationships are typically established:
…through a design of experiments, ultimately developing a multivariate model that defines how variability of the CPPs affects the CQAs and the boundaries where the CPPs can operate and produce quality product. The multivariate model that defines the boundaries where the process can operate is known as the design space. It represents a significant component of process understanding.
He describes some of the specialized tools to implement PAT-based measurement and control including analytical instruments, chemometric modeling tools and software for PAT method development, data management and systems integration. Example analytical instruments include:
near-infrared spectroscopy Raman spectroscopy mass spectroscopy Fourier-transform infrared spectroscopy focused-beam reflectance measurement
Read the article for Jonathan’s analysis of the implementation challenges, lessons learned and best practices. He concludes:
Deploying PAT as a strategy to increase quality and improve financial performance of drug product and drug substance manufacturing is proven. Many papers are available highlighting successful implementations and the benefits realized. The FDA and other regulatory agencies promote the adoption of new technologies, and the industry is being encouraged to move forward with PAT and other advanced methods for process monitoring and control. As companies decide to adopt these technologies, they should take care to execute investments as part of a strategic initiative and have a realistic understanding of the challenges. Although this is not rocket science, it is chemical science. Obtaining overall organizational commitment and applying good planning and resources are the keys to success.
You can connect and interact with other pharmaceutical and biopharmaceutical experts in the Life Sciences group in the Emerson Exchange 365 community.
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