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Jin Y. Ooi is Professor of Particulate Solid Mechanics, School of Engineering, University of Edinburgh, United Kingdom.
Particulate modelling has the potential to transform productivity within the pharmaceutical manufacturing industry, speeding up production cycles, reducing manufacturing costs, improving efficiency, and driving inward investment, with the potential to reinstate the UK as a global manufacturing powerhouse.
Back in 2014, George Osborne, who was then the United Kingdom’s Chancellor of the Exchequer, announced the launch of a new £28-million National Formulation Centre (NFC) in an effort to improve productivity and efficiencies within the UK’s process sector, including pharmaceuticals. The new centre, led by The Centre for Process Innovation (CPI), will bring universities, innovation centres, and businesses together to help companies tasked with developing, proving, prototyping, and scaling up the next generation of formulated products and processes.
The initiative will focus specifically on improving areas of product and process design, delivery, stability, and sustainability. A key aspect to this initiative is the introduction of innovative new digital technologies into the manufacturing process, such as discrete element modelling (DEM), to improve product design, speed up production, minimize costs, and reduce wastage. The British government has identified digital technology as a key driver to boosting manufacturing productivity, a view shared across the globe. Digitalization is, in fact, widely recognized as a step change and a potential game changer in the way products are designed and manufactured. During the past 10 years, there has been a massive rise in annual spend across Europe, the UK and the United States in this area. For example, by 2020, nearly €80 billion will be made available for the seven-year Horizon 2020 Funding Programme across Europe, with a focus on science and technology underpinning industrial innovation (1).
The widespread use of digital modelling software techniques such as DEM-a technique that enables engineers to predict the behaviour and impact of particulates on their designs-has the potential to revolutionize the pharmaceutical sector in the UK by boosting productivity and reducing manufacturing costs. But how is particulate modelling so relevant to pharmaceuticals? The efficient handling and processing of particulates is crucial to the profitable manufacture of pharmaceutical products. More than 75% of pharmaceutical products are marketed as solid dosage forms, and particulates are involved in almost every stage of the manufacturing process. Using particulate simulation early in the manufacturing process enables engineers to accurately simulate and analyze the behaviour of their particle systems. Digital modelling will, for example, provide a detailed analysis and visualization of the flow of particles, from powders to tablets, through process segments and handling equipment. The information obtained helps promote innovation in product design and reduces the need for physical prototyping and long development cycles, both of which are costly.
DEM has many applications in pharmaceutical manufacturing, including predicting powder flow properties; helping to evaluate powder testing equipment; optimizing tablet compaction, coating, and handling; and helping with the design and testing of powdered drug-delivery devices. For example, one of the challenges that tablet manufacturers often face is achieving a consistent coating thickness. For coatings that contain the API itself, variability in coating will give rise to variability in potency between tablets. Variability in thickness can also lead to variable drug-release profiles. Finally, high levels of coating variability for cosmetic purposes can result in longer process times to ensure that all tablets have received a sufficient amount of coating.
Companies, such as Pfizer, are using DEM simulation to improve the consistency of tablet coating. The DEM software enables them to predict the total residence time in the spray zone for a given tablet, helping to achieve a more even, consistent coat and to reduce waste. Nonetheless, despite the obvious benefits, the use of digital modelling techniques in the pharmaceutical sector is still underutilized. Today, the majority of pharmaceutical companies rely on assumptions, guess-work, and simple measurement to predict particulate behaviour when designing machinery or predicting active ingredient dosages for medicines or tablet coat thickness. Most manufacturers rely on trial and error and prototyping to achieve consistent designs, resulting in a painfully slow and excessively expensive production process. This approach can often lead to vital drugs being delayed significantly in production.
Particulate modelling can be challenging, which is why only a few companies are using this technology despite its benefits. Companies have achieved models that work well for small-scale operations, but the difficulty comes when scaling up to industrial operations. In short, modelling principles that work for the very small do not apply to the very big, and this issue is a major stalling point for many manufacturers.
The technology and knowhow is getting there, but it is limited to the academics who are developing new techniques and methods. The challenge is to get this knowledge out to the industry cost effectively and providing tools that are accessible to the industry so that companies with limited expertise can benefit from the technology. Currently, modelling is expensive and complex, and these factors are stalling mass adoption across the industry. Multinational companies will often have a greater capacity to adopt new technologies because they can invest in staff and training, but it is much harder for small-medium enterprises (SMEs) that lack the financial and human resources.
The complexity of the modelling software is also an issue. The techniques developed by academia are often not directly accessible for commercial use and rely on technology enablers to bridge the gap. For example, the team at EDEM has worked on developing their particle simulation technology to make the method more accessible, such as by improving the ease of use and building in “intelligence” so that researchers can focus on the problem and not the complexity of the tool.
There is also a general lack of understanding within the industry of what DEM is capable of, as well as an entrenched thinking that defaults engineers to use tried and tested techniques. Moreover, most engineering degrees don’t even include DEM or particle-scale modelling in their syllabus. At the post-graduate level, the situation is better, but only a few students are interested in studying particulate modelling at the post-graduate level because of the lack of awareness and exposure to the topic. It is pertinent that the relevant university degree curriculum highlights the relevance of particulate modelling to prospective engineering undergraduates.
Part of the problem is that academic institutions take a more classical approach to engineering and are not always in touch with the needs of the industry or do not keep up with the development of modern techniques. On a more positive note, there is strong demand for those with appropriate training in particulate modelling because companies are looking for experts in this field.
The universities have a role to play in driving change. Particle scale modelling ought to be introduced in undergraduate engineering degrees, within the solids processing and particle technology curriculum, so the next generation of engineers are aware of its capability early in their education.
The industry also needs to be made aware of the benefits and capabilities of particulate modelling. Firstly, if there are more engineers versed in particulate modelling, this awareness will come from within. Secondly, the technology enablers who recognize the potential of such technology will invest in creating particulate modelling software that can be commercialized for industrial purposes.
The widespread adoption of particulate modelling will also depend on the quality and ease of use of modelling software tools. DEM remains a specialist technique that only a minority of engineers have the expertise to use. It is little wonder that so few companies are using it. The mass adoption of particulate modelling by the pharmaceutical industry depends on the democratization of modelling software so that it is accessible to any design engineer without the need for specialist expertise. For this to happen, more automation and intelligence must be built into the particulate modelling software tools.
Collaboration is also key to success. The industry, the government, and academia must work more closely together to facilitate the seamless transfer of new modelling techniques to the pharmaceutical sector, support SMEs in the adoption of software, finance research within academia, and work with technology enablers to ensure modelling software is accessible. Industrial schemes should be led by the industry and funded by the government, with software companies acting as the intermediary, providing accessible tools to make it happen. Funding projects, such as the CPI initiative, is a step in the right direction.
The next phase of the industrial revolution will be driven by digital technology. If the pharmaceutical industry is willing to adopt new particulate modelling techniques, the benefits will be considerable. Particulate modelling has the potential to transform productivity within the pharmaceutical manufacturing industry, speeding up production cycles, reducing manufacturing costs, improving efficiency, and driving inward investment, with the potential to reinstate the UK as a global manufacturing powerhouse.
1. European Commission, “What is Horizon 2020?”,
https://ec.europa.eu/programmes/horizon2020/en/what-horizon-2020, accessed 5 Jan. 2018.