Discrete computational modelling of twin screw granulation

Many industrial processing operations depend on feed materials that are fine powders with poor handling characteristics, which have to be rectified by granulation to form coarser granules. Generally wet granulation is employed, in which a binder is added to the powder in a mixer usually in batch processes. Continuous Twin Screw Granulation (TSG) has considerable potential, eg in the pharmaceutical sector, because of the flexibility in throughput and equipment design, reproducibility, short residence times, smaller liquid/solid ratios and also the ability to granulate difficult to process formulations. However, there remain significant technical issues that limit its widespread use and a greater understanding of the process is required to meet regulatory requirements. Moreover, encapsulated APIs (Active Pharmaceutical Ingredients) are of increasing interest and the development of a TSG process that did not damage such encapsulates would significantly extend applications.
Experimental optimisation of TSG is expensive and often sub-optimal because of the high costs of APIs and does not lead to a more generic understanding of the process. Computational modelling of the behaviour of individual feed particles during the process will overcome these limitations. The Distinct Element Method (DEM) is the most widely used method but has rarely been applied to the number of particles in a TSG extruder (~ 55 million) and such examples involve simplified interparticle interactions e.g. by assuming that the particles are smooth and spherical and any liquid is present as discrete bridges rather than the greater saturation states associated with granulation. The project will be based on a multiscale strategy to develop advanced interaction laws that are more representative of real systems. The bulk and interfacial properties of a swelling particulate binder such as microcrystalline cellulose will be modelled using Coarse-grained Molecular Dynamics to derive inputs into a meso-scale Finite Discrete Element Method model of formulations that include hard particles and a viscous polymeric binder (hydroxypropylcellulose). Elastic particles (e.g. lactose and encapsulates) with viscous binder formulations will be modelled using the Fast Multi-pole Boundary Element Method. These micro- and meso-scale models will be used to provide closure for a DEM model of TSG. It will involve collaboration with the Chinese Academy of Science, which has pioneered the application of massively parallel high performance computing with GPU clusters to discrete modelling such as DEM, albeit with existing simpler interaction laws. An extensive experimental programme will be deployed to measure physical inputs and validate the models. The screw design and operating conditions of TSG for the formulations considered will be optimised using DEM and the results validated empirically. Optimisation criteria will include the granule size distribution, the quality of tablets for granules produced from the lactose formulation and the minimisation of damage to encapsulates.
The primary benefit will be to provide a modelling toolbox for TSG for enabling more rapid and cost-effective optimisation, and allow encapsulated APIs to be processed. Detailed data post-processing will elucidate mechanistic information that will be used to develop regime performance maps. The multiscale modelling will have applications to a wide range of multiphase systems as exemplified by a large fraction of consumer products, catalyst pastes for extrusion processes, and agriculture products such as pesticides. The micro- and mesoscopic methods have generic applications for studying the bulk and interfacial behaviour of hard and soft particles and also droplets in emulsions. The combination of advanced modelling and implementation on massively parallel high performance GPU clusters will allow unprecedented applications to multiphase systems of enormous complexity.

The economic well-being of the UK is critically dependent on the competitiveness of its manufacturing activity. The chemicals and pharmaceutical sectors are larger than the aerospace and automotive sectors combined eg formulated products have a market size of £180bn in the UK and a potential global market of £1000bn, with multiphase systems being an important market segment. Our ability to compete in these markets requires world class enabling tools and skills. The immediate beneficiaries will be the members of the Advisory Committee. AstraZeneca is a major pharmaceutical company with an active activity in TSG including the incorporation of encapsulates. The project will underpin this investment particularly for formulations that include expensive APIs, which limits empirical process design and optimisation. GEA is a leading supplier of pharmaceutical processing technology including TSG equipment. Improvements in the timescale and costs of specifying optimal design and operation and also an enhanced mechanistic understanding to support regulatory approval would accelerate the wider adoption of TSG. Unilever is a major multinational home and personal care, and food company. It routinely uses computer simulation in the development of product processing, of which the majority are multiphase formulations and many are granular. The project will enhance their virtual process design capability. Sandvik is also a major multinational company with a large proportion of products based on granular materials. The project would directly assist them in improving their paste extrusion processes and the computational tools could have a wider application in other processes. Freeman Technology is a UK SME that has developed a leading position in instruments for measuring the properties of dry and wet powders. The project would assist in interpreting the data generated with this equipment and thus increase in their customer base. The project will also consolidate and strengthen international collaboration with CAS in China by drawing on their extraordinary expertise in high performance computing with GPU clusters and expanding their research portfolio into multiphase systems involving liquids and pharmaceutical research.
In the medium term (< 5 yr), other pharmaceutical companies will benefit from the development of optimised TSG processes. The large number of companies that employ wet batch granulation will be able to exploit the software. While the work will focus on wet solid particulate systems, from partially saturated agglomerates to pastes, the approach is applicable to modelling the properties and behaviour of multiphase systems more generally eg the micro- and meso-scale modelling could be applied to multiphase formulations based on emulsions. Applications include an enormous range of multiphase products in sectors such as home and personal care, processed food, coatings such as paints and catalyst supports made by paste extrusion. An understanding of multiphase systems has huge societal and environment impacts such as sustainable manufacturing processes. The controlled delivery of drugs depends on an understanding of the biological pathways in the human body, which is essentially multiphase, eg blood is a suspension of cells in plasma and FMBEM has been widely deployed in this area but could be enhanced greatly by coupling with CGMD.
Three of the RAs employed will develop a strong capability in discrete computer simulation and close links with one of the leading academic institutions in China. Their skills will be attractive to the many companies involved with multiphase processes and also in the academic sector. The other RA will develop advanced skills in practical TSG and characterisation techniques. Given the importance of wet granulation generally and the expected increase in the use of TSG, this RA would have excellent employment prospects in a wide range of companies and, in particular, the pharmaceutical sector.