(68d) A Mechanistic Approach to Developing Spherical Agglomeration for Process Intensification in Pharmaceutical Manufacturing | AIChE

(68d) A Mechanistic Approach to Developing Spherical Agglomeration for Process Intensification in Pharmaceutical Manufacturing

Authors 

Tew, J. D. - Presenter, The University of Sheffield
Arjmandi-Tash, O., The University of Sheffield
Pitt, K., University of Sheffield
Smith, R., The University of Sheffield
Litster, J. D., The University of Sheffield
The crystallisation of particulate materials is a common process with applications in a variety of industries. This is often the first operation to recover crystalline material from a bulk solution, thereby presenting an opportunity to beneficially tailor material properties. In the pharmaceutical industry, the process is already used to facilitate the formulation of the majority of active pharmaceutical ingredients (APIs). Currently, the formulation and structure of the APIs directly dictate the required number of unit operations to follow. For solid oral dosages, it is imperative that the API has high flowability and compressibility to ensure an appropriate tablet structure is produced. Furthermore, these properties are essential for predictable API performance within the body. To improve these properties, the industry relies upon granulation and milling operations which are both time-consuming, cost-intensive and energy-inefficient. They are also difficult processes to accurately control, which may involve the recycling of crystalline material which is unsuitable for tabletting.

Spherical agglomeration is a process which provides the opportunity for these key properties of APIs to be significantly improved through the direct precipitation and agglomeration of crystalline structures. The precipitation is achieved by addition of a poor solvent (anti-solvent) to a good solvent in which the drug is dissolved and the agglomeration is supported by addition of bringing liquid. These steps can follow on from each other or be achieved simultaneously, often with improved results [Wu et al., 2015]. The particle size can be increased by a factor of ten, compared to the original size [Kawashima et al., 1982]. Additionally, the agglomerates formed are often dense and spherical in nature; a major improvement for naturally acicular particles. As a result, if the process is optimised, there is the potential for several unit operations to be removed from the production process. The process could therefore significantly intensify the manufacture of pharmaceutical products through the reduction of the time to market, reduction of the operating capital required and reduction of equipment requirements. There is also the potential for the system to be operating continuously, further improving API production efficiency.

The current state of the art has already established robust relationships between processing parameters and agglomerate properties. These are consistent, regardless of the crystalline product to be agglomerated. This provides engineers with greater flexibility in identifying a set of process parameters which will yield agglomerates with the required size, porosity and strength, amongst other characteristics. However, for this flexibility to be utilised effectively, it is vital that engineers have reliable models which can accurately predict process performance. Currently, such models do not exist due to a lack of key mechanistic understanding. Whilst previous studies have tried to identify and model some of these mechanisms, no one study has utilised all the mechanisms to produce a model which accurately reflects the process.

Critically, three separate overarching rate processes occur; wetting, growth and breakage. The wetting phase can occur through either the distribution or immersion mechanism, depending on the size of the particles to be agglomerated and the size of the droplets of bridging liquid which agglomerate them. If the droplets are smaller than particles, a distribution mechanism occurs in which the particles are effectively wetted through a coating mechanism, allowing particles to stick together. If the droplets are larger than particles, an immersion mechanism occurs in which the particles move inside the droplets and stick together within it. The latter of these mechanisms gives rise to denser, more spherical agglomerates [Muller & Loffler, 1996]. The growth phase involves the compaction and consolidation of agglomerates as they are subjected to shear forces. Crucially, as more particles adhere to each other, agglomerates growth in size through the creation of liquid bridges. These solidify to yield crystalline bridges upon drying. The breakage phase is not investigated in this study, but occurs as particles collide with each other and the crystallisation vessel.

In this study, we report our initial work in identifying, characterising and modelling of wetting/nucleation and growth/consolidation mechanisms. To do so, the fundamental kinetics were identified and verified using model particles; plastic beads (52 μm) and glass ballotini beads (45-90 μm). A novel, microfluidic device was developed to visualise these mechanisms in-situ with an optical microscope and a high-speed camera. We have also investigated the influence of material properties, such as surface energy, and process parameters, such as shear rate, upon these mechanisms. From these experiments, will have been able to construct the beginnings of a rate process map, which demonstrates the relationship between these parameters and their effect upon the process as a whole.

The roles of such mechanisms and phases of agglomeration using crystal loaded systems, such as salicylic acid, are also presented. Here, two unique pieces of equipment are employed; an oscillatory baffled reactor (OBR) and a particle viewing and measurement (PVM) probe. The OBR has superior mixing capabilities compared to conventional stirred-tank reactors due to the elimination of dead zones. The level of mixing can be analysed computationally through fluid dynamics. The PVM allows the analysis and tracking of particle populations in real-time, allowing us to further understand the agglomeration process with a view to improving and developing prior determined models.

S. Wu, K. Li, T. Zhang, J. Gong, Size Control of Atorvastatin Calcium Particles Based on Spherical Agglomeration, Chem. Eng. Technol. 38 (2015) 1081–1087.

Y. Kawashima, M. Okumura, H. Takenaka, Spherical Crystallization : Direct Spherical Agglomeration of Salicylic Acid Crystals During Crystallization, Science. 216 (1982) 1127–1128.

M. Müller, F. Löffler, Development of agglomerate size and structure during spherical agglomeration in suspension, Part. Part. Syst. Charact. 13 (1996) 322–326.