A Practical & Structured Approach To Deploying Process Analytical Technology In a Manufacturing Environment
Letís redefine PAT as the Practical Application of Technology
By Martin Gadsby, Director, Optimal Industrial Automation Ltd
Despite the many operational and cost saving benefits provided by Process Analytical Technology (PAT), its adoption in the Life Sciences sector has been slow. There are many reasons for this: natural resistance to change, perceived cost, complexity, risk, regulatory concerns, depth and length of commitment required, and deployment methodology, which is not clear to all. This has meant that PAT deployments may take too long. The purpose of this paper is to address these issues and propose a practical structure for the implementation of PAT. We would ‘coin’ our structured approach as the ‘Practical Application of Technology’.
PAT has been defined, by the USA’s Food and Drug Administration (FDA), ‘as a mechanism to design analyse and control pharmaceutical manufacturing processes through the measurement of Critical Process Parameters (CPP) that affect Critical Quality Attributes (CQA)’. The implementation of PAT requires a fundamental change in pharmaceutical manufacturing methodology to a more dynamic approach delivering substantial reductions in WIP, cost and time to market together with improvements in quality for manufacturers.
The long term goals for PAT can be quantified as follows:
- increase process understanding
- reduce development and scale up time
- reduce production cycle times
- enable use of alternative (less expensive) raw materials
- reduce wastage during production
- prevent rejection of batches
- improvement in quality and consistency of quality
- enable real time release of product
- improve energy and material use
- facilitate continuous processing
- release the capability of automation to improve the production process
The challenges facing PAT implementations are many. First, legacy practices: people generally do not like change. Second, human resources: the perception that the implementation of PAT may adversely affect roles and responsibilities. Third, regulatory: regulatory requirements still have to be met at a time of great change; but the FDA has created opportunities for streamlined registration of such changes. Fourth, skilled resources: PAT deployment calls for a wide range of skill sets.
Fifth, pragmatism: a detailed yet pragmatic & risk based approach is required. Sixth, technology for deployment: correct & appropriate PAT technologies are essential for project success. This paper concentrates on these last 2 challenges.
Necessary Technologies for PAT Deployment
The Necessary Technologies for PAT deployment is a two phase process. Phase 1 is concerned with process model & knowledge building – control is seldom of concern at this stage. For this phase the requirements are typically a univariate data acquisition system, spectral instruments, an MVA package, and a PAT data management system. Phase 2 deals with control model building and control with PAT. For this phase all the items listed in Phase 1 are required, plus a control system.
Step 1: Target Product Identification
PAT Implementation Strategy is all about knowing where to start, and what questions to ask. If the project is going to be related to a new product application, typical questions would be: Can I produce without PAT? What are the benefits of using PAT, and how do I quantify them? Do I apply PAT at the R&D, PD or production phase?
For an existing product application the questions are fundamentally different. Typically, they include: How do I work with the regulator on an existing process? What are the potential financial, quality and timing gains?
What are the risks and how do I mitigate them? An often unspoken concern also relates to answering the question - what happens if the PAT process reveals that my existing quality isn’t to the standard that I always thought that it was?
Step 2: Unit Operation Identification
Of even more importance is the question of which process to start with. Should the easiest or most complex be targeted? Or should it be the one that is the most stable or most problematic? Alternatively, what about the process with the highest potential financial or quality gains? Or should it be the process that is likely to be the fastest to deploy? The outcome of this targeting strategy is critical because of the high level of interest that is likely to be within the business in the outcome of the PAT trials on the 1st unit operation.