What Is Process Analytical Technology?

Pharmaceutical scientific female researcher in protective uniform working with dissolution tester at pharmacy industry manufacture factory laboratory Process analytical technology
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Process analytical technology (PAT) is succinctly defined as:-

‘Systems for analysis and control of manufacturing processes based on timely measurements of critical quality parameters and performance attributes of raw and in-process materials’.

It has also been formally defined by the United States Food and Drug Administration (FDA) as a ‘mechanism to design, analyze, and control pharmaceutical manufacturing processes through the measurement of Critical Process Parameters (CPP) which affect Critical Quality Attributes (CQA).

Critical Quality Attributes (CQA)

Critical Quality Attributes (CQA) are chemical, physical, biological and microbiological attributes that can be defined, measured, and continually monitored to ensure final product outputs remain within acceptable quality limits. CQA are an essential aspect of a manufacturing control strategy and should be identified in stage 1 of Process Validation: Process design. During this stage acceptable limits, baselines, and data collection and measurement protocols should be established. Data from the design process and data collected during production should be kept by the manufacturer and used to evaluated product quality and process control. Historical data can also help manufacturers better understand operational process and input variables as well as better identify true deviations from quality standards compared to false positives. Should a serious product quality issue arise, historical data would be essential in identifying the sources of errors and implementing corrective measures.

Process Parameters

A process parameter is one whose variability impacts on a critical quality attribute. It must be monitored or controlled to ensure the process generates the desired quality (Q8R2).

Critical Process Parameters

Critical process parameters (CPP) in pharmaceutical manufacturing are key variables affecting the production process. They are summed up as operating parameters that are essential for maintaining product output within specified quality target guidelines.

CPPs have a direct impact on CQAs.

CPPs are attributes that are monitored to detect deviations in standardized production operations and product output quality or changes in Critical Quality Attributes.

 

Critical Process Parameters: The Relation To Critical Quality Attributes

Those attributes with a higher impact on CQAs should be prioritized and held in a stricter state of control. The manufacturer should conduct tests to set acceptable range limits of the determined CPPs and define acceptable process variable variability. Operational conditions within this range are considered acceptable operational standards. Any deviation from the acceptable range will be indicative of issues within the process and the subsequent production of substandard products. Data relating to CPP should be recorded, stored, and analyzed by the manufacturer. CPP variables and ranges should be reevaluated after careful analysis of historical CPP data. Identifying CPPs is done in stage one of Process Validation: Process design are an essential part of a manufacturing control strategy.

One method of defining CPPs is to look at the effect of certain production processes on critical quality attributes. Those production parameters which have a measurable effect on those qualit

The concept actually aims at understanding the processes by defining their CPPs, and accordingly monitoring them in a timely manner (preferably in-line or on-line) and thus being more efficient in testing while at the same time reducing over-processing, enhancing consistency and minimizing rejects.

PAT can provide better process control and result in better process understanding. It may also alter the approach to setting in-process specifications, e.g. measuring constant purity instead of yield. Although it is not likely to eliminate validation, the effort spent to incorporate PAT, especially for a new product or for a process change, can enhance manufacturing consistency and reduce failed batches—providing an economic advantage.

The FDA has outlined a regulatory framework for PAT implementation. With this framework, according to Hinz, the FDA tries to motivate the pharmaceutical industry to improve the production process. Because of the tight regulatory requirements and the long development time for a new drug, the production technology is “frozen” at the time of conducting phase-2 clinical trials.

Generally, the PAT initiative from FDA is only one topic within the broader initiative of “Pharmaceutical cGMPs for the 21st century – A risk based approach”.

The Basics Of Process Analytical Technology

PAT is a term used for describing a broader change in pharmaceutical manufacturing from static batch manufacturing to a more dynamic approach.

The desired state of pharmaceutical manufacturing as defined in the PAT guidance is as follows:

  • Product quality and performance are ensured through the design of effective and efficient manufacturing processes.
  • Product and process specifications are based on a mechanistic understanding of how formulation and process factors affect product performance.

  • Continuous real-time QA is done throughout the process.

  • Risk-based regulatory approaches recognize the level of scientific understanding of how formulation and manufacturing process factors affect product quality and performance and the capability of process control strategies to prevent or mitigate the risk of producing a poor-quality product.

PAT requires defining the Critical Process Parameters (CPPs) of the equipment used to make the product, which affect the Critical Quality Attributes (CQAs) of the product and then controlling these CPPs within defined limits. This allows manufacturers to produce products with consistent quality and also helps to reduce waste & overall costs.

This mechanism for producing consistent product quality & reducing waste presents a good case for utilising continuous manufacturing technologies. The control of a steady state process when you understand the upstream & downstream effects is an easier task as common cause variability is easier to define and monitor.

Variables In Process Analytical Technology (PAT)

It would be acceptable to consider that raw materials used to manufacture pharmaceutical products can vary in their attributes e.g. moisture content, crystal structure etc. It would also be acceptable to consider that manufacturing equipment does not always operate in exactly the same fashion due to the inherent tolerance of the equipment and its components. It is therefore logical to say that variability in raw materials married with a static batch process with inherent variability in process equipment produces variable product. This is on the basis that a static batch process produces product by following a fixed recipe with fixed set-points.

With this in mind the PAT drive is to have a dynamic manufacturing process that compensates for variability both in raw materials & equipment to produce a consistent product.

Process Analytical Technology Implementation (PAT)

The challenge to date with PAT for pharmaceutical manufacturers is knowing how to start. A common problem is picking a complex process and getting mired in the challenge of collecting and analysing the data.

The following criteria serve as a basic framework for successful PAT roll-outs: (From A PAT Primer)

  • Picking a simple process. (Think Water for Injection (WFI) or Building Monitoring System (BMS)
  • All details and nuances are well understood and explained for that process.
  • Determine what information is easily collected and accessible through current instrumentation.
  • Understanding the appropriate intervals for collecting that data.
  • Evaluating the tools available for reading and synchronizing the data.

PAT Tools

In order to implement a successful PAT project, a combination of three main PAT tools is essential:

  • Multivariate data acquisition and data analysis tools: usually advanced software packages which aid in design of experiments, collection of raw data and statistically analyzing this data in order to determine what parameters are CPP.
  • Process analytical chemistry (PAC) tools: in-line and on-line analytical instruments used to measure those parameters that have been defined as CPP. These include mainly near infrared spectroscopy (NIRS); but also include biosensors, Raman spectroscopy, fiber optics and others.
  • Continuous improvement and/or knowledge management tools: paper systems or software packages which accumulate Quality Control data acquired over time for specific processes with the aim of defining process weaknesses and implementing and monitoring process improvement initiatives. These products may be the same or separated from the statistical analysis tools above.

Long-term goals

The long-term goals of PAT are to:

  • reduce production cycling time
  • prevent rejection of batches
  • enable real time release
  • increase automation and control
  • improve energy and material use
  • facilitate continuous processing

Currently NIR spectroscopy applications dominate the PAT projects. A possible next-generation solution is Energy Dispersive X-Ray Diffraction (EDXRD). 

Although the FDA’s PAT initiative encourages process control based on the real-time acquired data, a small part of PAT applications goes beyond monitoring the processes and follows the PACT (‘Process Analytically Controlled Technology’) approach.

MVA in PAT

Fundamental to process analytical technology (PAT) initiatives are the basics of multivariate analysis (MVDA) and design of experiments (DoE). This is because analysis of the process data is a key to understand the process and keep it under multivariate statistical control.

 

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