New mechanics of quality control – bringing medicines to market19 September 2016
Pharmaceutical companies are under growing pressure to bring medicines to market quicker while simultaneously facing greater competition, higher quality and safety concerns, and diminishing margins. They are under pressure to increase capacity usage, reduce cycle times and improve manufacturing times – but how could this be achieved?
Process analytical technology (PAT) is a framework for innovative pharmaceutical development, manufacturing and quality assurance. The US Food and Drug Administration (FDA) defines its initiative as a means to design, analyse and control the pharmaceutical manufacturing process through the measurement of critical process parameters (CPP) that affect critical quality attributes (CQA). It applies to human and veterinary drugs alike, and specified biologic sponsors and applicants. The analytical approach is broad and can include chemical, physical, microbiological, mathematical and risk analyses.
PAT aims to ensure product quality and performance through the design of efficient and effective manufacturing processes. Product and process specification is based on a mechanistic understanding of how formulation and process factors affect product performance.
The goal is to enhance understanding and control of the pharmaceutical manufacturing process; companies need to understand the intended therapeutic objective – patient population; the pharmacological, toxicological and pharmacokinetic effects of a drug; and how it is administered.
Any gains in quality, safety or efficiency will vary depending on the process and product but it is likely to come from a number of variables. This may include reducing cycle times, and using on, in and at-line measurements and controls; preventing rejects, scraps and reprocessing; improving energy and material use and increasing capacity; and increasing automation to improve operator safety and reduce human error.
The traditional way
Pharmaceutical drugs are traditionally produced using a static batch process whereby the drugs are made in batches and tested in the laboratory at the end of this process. This method can be time-consuming, however; pharmaceutical companies still suffer from excessive rework and discarded products, high levels of work in progress, low capacity usage, prolonged cycle time and laboratory bottlenecks.
An estimated industry average for rework and discarded product was 50% in 2004, while plant use ran at 40–50% with the average cycle time between 30 and 90 days. Bottlenecks can add as much as 75% to the cycle time – even more if an investigation is deemed necessary.
And when you consider that the raw materials used to manufacture pharmaceuticals can vary in their attributes – in crystal structure or moisture content, for example – and that the equipment used to manufacture them does not always perform in the same way due to the inherent tolerances of the equipment and its components, it is logical to assume that the end products will vary in terms of quality.
The quality of the final drug is influenced by everything that happens during the manufacturing process; each step and ingredient, the equipment and the manufacturing environment can all lead to variations in the product – something that must be minimised if a product is to be considered safe to bring to market.
A new era
Pharmaceutical manufacturing needs to evolve, and with an increased emphasis on science and engineering principles; effective use of this knowledge throughout the life cycle of a product can improve the efficiency of manufacturing and regulatory processes. PAT has already proven to be a success in the oil and gas industry, and is gaining momentum in pharmaceutical and biotech production, as it can be used to reduce product and process variability, ensure conformity and decrease waste.
PAT makes use of a continuous processing method whereby products are tested and adjusted throughout the procedure. It aims to allow companies to understand their processes by defining what variables are most critical to their final product – their CPPs – and deciding where controls are necessary and what factors control sample degradation.
Central to PAT is the belief that quality should be built into a product by design, not ‘tested in’. If quality is not built in, organisations are forced towards expensive and unreliable methods of achieving the necessary quality requirements. It shows that they have failed to mitigate product risks that occur due to lack of design, poor planning and inadequate control of the manufacturing process.
PAT is based on four principles: process understanding, a risk-based approach, a regulatory strategy to accommodate innovation and real-time release. Companies can analyse and control the manufacturing process by measuring the quality of raw and in-process materials, and alter it when necessary.
They can monitor their CPPs in a timely manner, in-line or online, which enables them to be more efficient in their testing by allowing in-process quality checks while reducing over-processing, enhancing consistency, minimising rejected products and decreasing waste and overall costs. It can also help eliminate error-prone manual intervention and accurately produce the product to meet demands.
This dynamic manufacturing process compensates for variability in raw materials and equipment to produce a consistent product. Controlling this steady state of process when you understand the up and downstream effects along with all variables enables companies to define and monitor the cause of any variability.
From a manufacturing perspective, PAT is very attractive. First-time-right manufacturing helps reduce waste, raw material usage, and work-in-progress and finished goods inventories. Real-time quality assurance and validation also means a more robust, safer product-supply route to the public.
PAT can also help reduce production costs and speed up the time-to-market of a new drug. Traditionally, the industry has taken a conservative approach to implementing process changes and upgrading technology.
Combined with the added cost of restructuring process lines, the whole thing can seem very daunting. Much inefficiency is based on tradition – how things are usually done – along with cost considerations and a general reluctance to change. However, the savings gained from more-efficient use of resources, reduced waste, faster product approvals and a lower risk of product recalls soon outweighs this.
A streamlined approach
A key driver of PAT comes from the regulatory side; FDA has recognised that traditional approval procedures were hindering manufacturing. PAT is expected to encourage innovation but there is a fear of FDA reprisals.
Companies are reluctant to implement PAT only to find problems that wouldn’t have surfaced with normal processing. To combat this argument, FDA has said that routine inspections would be based on current regulatory standards.
Still, companies remain hesitant to introduce new systems to replace their tried-and-tested methods of production because of the uncertainty it might place on standard compliance. Here, though, PAT can help.
It can give a company a much deeper scientific and engineering understanding of a manufacturing process; using this knowledge about the life cycle of a product, the company can then improve the efficiency of its manufacturing and regulatory processes.
This understanding also enables robust licensing packages, and aids faster scale-up and time-to-market for new products. It can also allow the tailoring of regulatory policies and procedures to accommodate current scientific knowledge.
Many companies choose to outsource the design of their framework as they don’t have the resources to generate it in house. To ensure the implementation of PAT is successful, therefore, companies will need to have their stakeholders and teams – key expertise from the laboratory, computer systems, regulatory, control systems and process engineering – on board at an early stage. A good business case needs to educate management on the value of PAT: what it is and its intentions, and how it will be compatible with any with existing (or legacy) systems that are already in place.
Implementation may require a shift in organisational structure, such as the need to develop in-house expertise, or make changes to existing inspection and validation methodologies. The relevant technologies to create an integrated management infrastructure that can handle the volume of data to be recorded will need to be identified.
It will also require advanced automation, visualisation and analysis tools to manage the continuous identification and prediction stages of the process.
The key to PAT is applying these process-monitoring tools, which are needed to analyse each of the critical product attributes. This provides the opportunity to make production adjustments based on analysis during the process by detecting errors or process deviations and correcting them while the product is being made. This is much more cost-effective than testing a batch-processed product only to find it is unacceptable.
Three main tools are considered vital for a successful implementation:
- multivariate data-acquisition and analysis tools: software packages that can help design experiments, collect raw data and analyse this statistically to determine CPPs
- process-analytical chemistry tools: in-line and online analytical instruments to measure CPPs, near infrared spectroscopy or biosensors, for example
- continuous improvement or knowledge-management tools: a paper-based system or software package to collate quality-control data to define process weaknesses, and implement and monitor improvement initiatives.
An online monitoring technique is most prevalent and allows the recording of data. As well as making data visible, it enables companies to respond and make adjustments during the process.
PAT could be a very useful tool in designing, analysing and controlling the pharmaceutical manufacturing process; it provides the opportunity to truly understand the process from raw material to final product while also reducing costs in various ways.
It can also help speed up the development of new drugs by reducing the time needed to gain approval. There is some, however some reluctance in the adoption of such a framework; it could be costly in terms of time and money, and the fear of FDA reprisals is a major deterrent. The benefits, however, certainly outweigh the disadvantages.