Improvement of a 1D Population Balance Model for Twin-Screw Wet Granulation by Using Identifiability Analysis
Recently, the pharmaceutical industry has undergone changes in the production of solid oral dosages from traditional inefficient and expensive batch production to continuous manufacturing. The latest advancements include increased use of continuous twin-screw wet granulation and application of advanced modeling tools such as Population Balance Models (PBMs). However, improved understanding of the physical process within the granulator and improvement of current population balance models are necessary for the continuous production process to be successful in practice. In this study, an existing compartmental one-dimensional PBM of a twin-screw granulation process was improved by altering the original aggregation kernel in the wetting zone as a result of an identifiability analysis. In addition, a strategy was successfully applied to reduce the number of model parameters to be calibrated in both the wetting zone and kneading zones. It was found that the new aggregation kernel in the wetting zone is capable of reproducing the particle size distribution that is experimentally observed at different process conditions as well as different types of formulations, varying in hydrophilicity and API concentration. Finally, it was observed that model parameters could be linked not only to the material properties but also to the liquid to solid ratio, paving the way to create a generic PBM to predict the particle size distribution of a new formulation.
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or continue reading here: Barrera Jiménez, A.A.; Van Hauwermeiren, D.; Peeters, M.; De Beer, T.; Nopens, I. Improvement of a 1D Population Balance Model for Twin-Screw Wet Granulation by Using Identifiability Analysis. Pharmaceutics 2021, 13, 692. https://doi.org/10.3390/pharmaceutics13050692
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Design of Experiments
In order to study the influence of the granulation parameters such as screw speed, material throughput and liquid-to-solid (L/S) ratio, in addition to the effect of the nature of the API, on the size distribution of the resulting granules, a five-level central composite design of experiments (DoE) was performed. Three different active pharmaceutical ingredient (API) at both low and high concentrations, resulting in the study of six formulations were studied. Therefore, two or three factors were used for each formulation based on their hydrophilicity, see details in Table 1. The process conditions were chosen to operate the equipment in a stable manner as well as according to the processability of each formulation to obtain similar granules [21,22]. Formulations at low concentration contain 5% (w/w) API, 5% (w/w) hydroxypropylcellulose (The Dow Chemical Company, Midland, MI, USA), 15% (w/w), microcrystalline cellulose (Avicel® PH 101, FMC, Philadelphia, PA, USA), and 75% lactose monohydrate (Lactochem® Regular, DFE Pharma, Goch, Germany). Formulations at high concentration contain 50% (w/w) API, 5% (w/w) hydroxypropylcellulose (The Dow Chemical Company, Midland, MI, USA), 15% (w/w) microcrystalline cellulose (Avicel® PH 101, FMC, Philadelphia, PA, USA), and 30% (w/w) lactose monohydrate (Lactochem® Regular, DFE Pharma, Goch, Germany). The samples were collected at four locations inside the barrel, indicated with the red color labels in Figure 1. These measurements are possible by the usage of a second liquid addition port: this enables us to mimic the granulation behavior of these different zones at the end of the barrel so that granules can be collected continuously without the need for a screw pull-out. This method is described in full detail in the work of Verstraeten et al.