(724f) A Hybrid Model to Predict the Formulation Dependent Granule Growth in a Bi-Component Wet Granulation Process

The wet granulation process is often a complex unit operation used in various particle processing industries. The complexity of this process lies in understanding the effects of equipment design, operating conditions, and material properties on the granule product quality. Significant knowledge has been accumulated on the population balance modeling of the wet granulation process where the impact of operating conditions on granule product properties was studied [3,2,1,6]; however, there is comparatively less insight on the impact of material properties. The constituent materials involved in the process can vary in properties such as shape, size, hydrophobicity, and strength. This material variability impacts the granulation mechanisms and affects the critical granule properties such as particle size distribution, porosity, microstructure, and content uniformity. Thus, quantifying the effects of material variability on granules is critical for a holistic understanding of the wet granulation process. In this study, a bicomponent wet granulation process is considered, and a modeling framework to predict the impact of material hydrophobicity is proposed.

Although many drug products involve materials with wettability differentials, there is a lack of understanding of how the hydrophobic behavior of materials affects the wet granulation process and granule product quality. To study the impact of wettability/hydrophobicity on granulation, two formulations were considered (I: Ibuprofen, and Microcrystalline cellulose (MCC-101), II: Acetaminophen, and MCC-101) with a wide difference in contact angle. Wet granulation results showed that the compositional distribution of components among granules of different sizes (i.e., content uniformity) is impacted by the granule growth mechanism. Ibuprofen formulation favored viscous force dominant granule growth, and acetaminophen formulation favored capillary force dominant granule growth. Due to viscous force dominant growth, ibuprofen formulation produced granules with a uniform compositional distribution of components among granules of different sizes. Capillary force dominant granule growth of acetaminophen formulation leads to weaker granules resulting in a non-uniform distribution of components among granules of different sizes [5]. Current population balance models lack the ability to capture this phenomenon.

Based on the experimental observations, a hybrid modeling framework was developed for predicting the granule properties in a bi-component wet granulation system with components of differing hydrophobicities(Figure 1). First, a random forest method is used for predicting the probability of nucleation mechanism (immersion and solid-spread) depending upon the formulation hydrophobicity. The predicted nucleation probability is used to determine the aggregation rate as well as the initial particle distribution in the population balance model. The aggregation process was modeled as Type-I: Sticking aggregation and Type-II: Deformation driven aggregation [4]. In Type-I, the capillary force dominant aggregation mechanism is represented by the particles sticking together without deformation. In the case of Type-II, the particle deformation causes an increase in the contact area, representing a viscous force dominant aggregation mechanism. The choice between Type-I and II aggregation is determined based on the difference in nucleation mechanism that is predicted using the random forest method. The model was optimized and validated using the granule content uniformity data obtained from the experimental studies. The proposed framework predicted content non-uniform behavior for formulations that favored immersion nucleation and uniform behavior for formulations that favored solid-spreading nucleation.

References

[1] Chaudhury, A., Armenante, M.E., Ramachandran, R., 2015. Compartment based population balance modeling of a high shear wet granulation process using data analytics. Chemical Engineering Research and Design 95, 211–228.

[2] Chaudhury, A., Wu, H., Khan, M., Ramachandran, R., 2014. A mechanistic population balance model for granulation processes: effect of process and formulation parameters. Chemical Engineering Science 107, 76–92.

[3] Darelius, A., Brage, H., Rasmuson, A., Bj¨orn, I.N., Folestad, S., 2006. A volume-based multidimensional population balance approach for modelling high shear granulation. Chemical Engineering Science 61, 2482–2493.

[4] Goodson, M., Kraft, M., Forrest, S., Bridgwater, J., 2004. A multi-dimensional population balance model for agglomeration, in: PARTEC 2004—International Congress for Particle Technology.

[5] Muthancheri, I., Ramachandran, R., 2020. Mechanistic understanding of granule growth behavior in bi-component wet granulation processes with wettability differentials. Powder Technology 367, 841–859.

[6] Pandey, P., Tao, J., Chaudhury, A., Ramachandran, R., Gao, J.Z., Bindra, D.S., 2013. A combined experimental and modeling approach to study the effects of high-shear wet granulation process parameters on granule characteristics. Pharmaceutical development and technology 18, 210–224.