26 February, 2020

Why you need PAT to move from batch to continuous processing

07 November, 2019

The future of many processes within complex manufacturing industries lies in continuous production, as opposed to batch manufacturing. For many pharmaceutical, biotech, food and chemical producers’ continuous operations can lead to greatly increased productivity and enhanced product quality. Other benefits include simultaneously adding flexibility, robustness and consistency to the process. Martin Gadsby, director at Optimal Industrial Technologies, looks at why Process Analytical Technology (PAT) provides the cornerstone to continuous manufacturing.

As opposed to batch production, where goods are produced in multiple, separated unit operations - interspersed with downtime for quality controls; continuous manufacturing is characterised by connected operations, where each unit immediately feeds the following one without any interruption.

Paradigm shift in quality management

The first step in implementing a continuous manufacturing strategy requires the adoption of an appropriate product quality management system. The traditional Quality by Testing (QbT) approach involves testing the material being processed after every manufacturing stage to ensure that the critical quality attributes (CQAs) are in line with specifications. Therefore, production needs to stop to collect samples and conduct testing in off-line analytical laboratories. As such, lengthy pauses are inherent to QbT and, as a consequence, it is impossible to implement a continuous manufacturing process.

Only by adopting a holistic, quality centric approach to product development and process design is it possible to transition from batch to continuous processing. This is known as Quality by Design (QbD) and it relies on the principle that product quality should be designed into the process, rather than tested in stages and corrected afterwards. Indeed, increased testing in a QbT paradigm does not improve product quality per se, it can just as easily introduce quality issues1.

Conversely, a responsive system, featuring real-time monitoring of product CQAs and adjustment of critical process parameters (CPPs), allows plant operators to obtain consistent and quality compliant products while reducing the likelihood of re-work or rejects.

In practice, QbD requires a scientific yet pragmatic approach that takes into account both the process and product to enable the design of effective, real-time quality control strategies. In this way, it is possible to achieve a predefined quality objective, i.e. delivering products that consistently meet or exceed the required quality standards. A key enabler for QbD is PAT, as it provides a systematic structure for measuring product quality in real time, facilitating process understanding and ultimately controlling the process to ensure product quality.

More precisely, PAT typically uses a range of spectral (multivariate) and univariate data sources together with prediction engines to make real time product quality predictions. These are at multiple points within a continuous process in order to achieve a holistic, QbD quality system. In the short term, the quality predictions available can be used by plant operators to make changes to the CPPs so as to maintain product quality at all times. In the medium to long term, quality-based control can be achieved by means of closed loop automated control systems. In this way, analytics are performed on-line and in real-time, as the process takes place, so there is no need to stop production to perform quality testing.

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