Numerical study of drop dynamics for inkjet based 3D printing of pharmaceutical tablets.

Interest in 3D printing has been growing rapidly especially in pharmaceutical industry due to its multiple advantages such as manufacturing versatility, personalization of medicine, scalability, and cost effectiveness. Inkjet based 3D printing gained special attention after FDA's approval of Spritam® manufactured by Aprecia pharmaceuticals in 2015. The precision and printing efficiency of 3D printing is strongly influenced by the dynamics of ink/binder jetting, which further depends on the ink's fluid properties. In this study, Computational Fluid Dynamics (CFD) has been utilized to study the drop formation process during inkjet-based 3D printing for piezoelectric and thermal printhead geometries using Volume of Fluid (VOF) method. To develop the CFD model commercial software ANSYS-Fluent was used. The developed CFD model was experimentally validated using drop watcher setup to record drop progression and drop velocity. During the study, water, Fujifilm model fluid, and Amitriptyline drug solutions were evaluated as the ink solutions. The drop properties such as drop volume, drop diameter, and drop velocity were examined in detail in response to change ink solution properties such as surface tension, viscosity, and density. A good agreement was observed between the experimental and simulation data for drop properties such as drop volume and drop velocity.

End-point determination of heterogeneous formulations using inline torque measurements for a high-shear wet granulation process.

In this study, the torque profiles of heterogeneous granulation formulations with varying powder properties in terms of particle size, solubility, deformability, and wettability, were studied, and the feasibility of identifying the end-point of the granulation process for each formulation based on the torque profiles was evaluated. Dynamic median particle size (d50) and porosity were correlated to the torque measurements to understand the relationship between torque and granule properties, and to validate distinction between different granulation stages based on the torque profiles made in previous studies. Generally, the torque curves obtained from the different granulation runs in this experimental design could be categorized into two different types of torque profiles. The primary factor influencing the likelihood of producing each profile was the binder type used in the formulation. A lower viscosity, higher solubility binder resulted in a type 1 profile. Other contributing factors that affected the torque profiles include API type and impeller speed. Material properties such as the deformability and solubility of the blend formulation and the binder were identified as important factors affecting both granule growth and the type of torque profiles observed. By correlating dynamic granule properties with torque values, it was possible to determine the granulation end-point based on a pre-determined target median particle size (d50) range which corresponded to specific markers identified in the torque profiles. In type 1 torque profiles, the end-point markers corresponded to the plateau phase, whereas in type 2 torque profiles the markers were indicated by the inflection point where the slope gradient changes. Additionally, we proposed an alternative method of identification by using the first derivative of the torque values, which facilitates an easier identification of the system approaching the end-point. Overall, this study identified the effects of different variations in formulation parameters on torque profiles and granule properties and implemented an improved method of identification of granulation end-point that is not dependent on the different types of torque profiles observed.

Computational Modeling of Fluidized Beds with a Focus on Pharmaceutical Applications: A Review.

The fluidized bed is an essential and standard equipment in the field of process development. It has a wide application in various areas and has been extensively studied. This review paper aims to discuss computational modeling of a fluidized bed with a focus on pharmaceutical applications. Eulerian, Lagrangian, and combined Eulerian-Lagrangian models have been studied for fluid bed applications with the rise of modeling capabilities. Such models assist in optimizing the process parameters and expedite the process development cycle. This paper discusses the background of modeling and then summarizes research papers relevant to pharmaceutical unit operations.

Pharmaceutical applications of powder-based binder jet 3D printing process - A review.

Pharmaceutical applications of the 3D printing process have recently matured, followed by the FDA approval of Spritam, the first commercial 3D printed dosage form. Due to being a new technology in the conventional dosage formulation field, there is still a dearth of understanding in the 3D printing process regarding the effect of the raw materials on the printed dosage forms and the plausibility of using this technology in dosage development beyond the conventional ways. In this review, the powder-based binder jet 3D printing (BJ3DP) process and its pharmaceutical applications have been discussed, along with a perspective of the formulation development step. The recent applications of BJ3DP in pharmaceutical dosage development, the advantages, and limitations have further been discussed here. A discussion of the critical formulation parameters that need to be explored for the preformulation study of the solid oral dosage development using the BJ3DP process is also presented.

Impact of powder-binder interactions on 3D printability of pharmaceutical tablets using drop test methodology.

In this study, a pre-screening test has been developed for the binder-jet 3D printing process (BJ3DP) which has been validated using statistical analysis. The pre-screening test or drop test has been adapted from the wet granulation field and modified later on to be used for tablet manufacturing in BJ3DP. Initially, a total of eight powders and ten water-based binder solutions have been introduced in the preliminary test to understand the powder-binder interactions. Afterward, based on the preliminary test results, three blends were developed which had undergone the same drop test. All these powder and binder combinations were then used for 3D printing. The key parameters such as mechanical strength and shape factors of the drop test agglomerates and 3D printed tablets were then compared using multiple linear regressions. Few dimensionless parameters were introduced in this study such as binding capacity and binding index to capture the printability properties of the powders used in this study. Significant relations (p<0.05) were found between the drop test and the BJ3DP process. Application of drop test was carried out to establish a prescreening test, ii) to develop new blend formulations as well as iii) to develop a fundamental understanding of powder-binder interaction during BJ3DP process.

Binder-Jet 3D Printing of Indomethacin-laden Pharmaceutical Dosage Forms.

Emerging 3D printing technologies offer an exciting opportunity to create customized 3D objects additively from a digital design file. 3D printing may be further leveraged for personalized medicine, clinical trial, and controlled release applications. A wide variety of 3D printing methods exists, and many studies focus on extrusion-based 3D printing techniques that closely resemble hot melt extrusion. In this paper, we explore different pharmaceutical-grade feedstock materials for creating tablet-like dosage forms using a binder jet 3D printing method. In this method, pharmaceutical-grade powders are repeatedly spread onto a build plate, followed by inkjet printing a liquid binder to selectively bind the powders in a predetermined pattern. The physical properties of the pharmaceutical-grade powders and binders have been characterized and a molding method has been developed to select appropriate powder and binder materials for subsequent printing experiments. There was a correlation between the breaking forces of the molded and printed samples, but no clear correlation was observed for disintegration time, which was primarily controlled by the higher porosity of the printed samples. The breaking force and disintegration properties of as-printed and post-processed samples containing indomethacin as an active pharmaceutical ingredient have been measured and compared with relevant literature data.

Formulation design for inkjet-based 3D printed tablets.

The drug loading efficiency was evaluated using a binder-jet 3D printing process by incorporating an active pharmaceutical ingredient (API) in ink, and quantifying the printability property of ink solutions. A dimensionless parameter Ohnesorge was calculated to understand the printability property of the ink solutions. A pre-formulation study was also carried out for the raw materials and printed tablets using thermal analysis and compendial tests. The compendial characterization of the printed tablets was evaluated with respect to weight variation, hardness, disintegration, and size; Amitriptyline Hydrochloride was considered as the model API in this study. Four concentrations of the API ink solutions (5, 10, 20, 40 mg/mL) were used to print four printed tablet batches using the same tablet design file. The excipient mixture used in the study was kept the same and consists of Lactose monohydrate, Polyvinyl pyrrolidone K30, and Di-Calcium phosphate Anhydrate. The minimum drug loading achieved was 30 µg with a minimal variation (RSD) of <0.26%. The distribution of the API on the tablet surface and throughout the printed tablets were observed using SEM-EDS. In contrast, the micro-CT images of the printed tablets indicated the porous surface structure of the tablets. The immediate release properties of the printed tablets were determined using a dissolution study in a modified USP apparatus II.

Multicomponent granular mixing in a Bohle bin Blender-Experiments and simulation.

Study of mixing and segregation of granular materials was performed in a Bohle bin blender using both computational modeling and experiments. A multicomponent mixture of pharmaceutical excipients and coated theophylline granules, an active pharmaceutical ingredient (API) was considered as the blend formulation. A DEM (Discrete Element Method) Model was developed to simulate the flow and mixing of the multicomponent blend to compare with the experimental data. DEM is a numerical modeling technique which incorporates all the material properties (such as Particle size, density, elastic modulus, yield strength, Poisson's ratio, work function etc.)to simulate granular flow (such as mixing, conveying) of particles. In simulation, the degree (Relative standard deviation) of mixing in a Bohle bin blender was assessed as a function of critical processing parameters (loading pattern, rotational rate, and fill percentage). Numerical simulation results reveal radial mixing in a Bohle bin blender is faster than axial mixing due to symmetric geometry limitation. This study investigates a numerical model-based approach to study the effect of the critical process parameters on the mixing dynamics in Bohle bin blender for a moderately cohesive pharmaceutical formulation. The DEM model can be used to provide crucial insights to developed optimized mixing protocols to ascertain the best mixing conditions for different formulation. As for example, as we try to develop a mixing protocol for another formulation with different operational parameters such as loading pattern, rotational speed, and fill percentage, one can device an optimized mixing protocol of the formulation with the help of this DEM model.

Quantification of Moisture-Induced Cohesion in Pharmaceutical Mixtures.

Moisture-induced flow variabilities in pharmaceutical blends lead to multiple impediments during manufacturing of solid dosage formulations. Processing and storage humidity conditions both govern the moisture contents of the pharmaceutical mixtures and bear significant impact on the final product quality. In this study, experimentally validated discrete element method-based computational models along with statistical formalism have been implemented to develop a predictive tool for moisture-induced cohesion in binary and tertiary mixtures. V-blending was applied to prepare the pharmaceutical blends, and mixing characterization was performed using a Raman PhAT probe. Optimum fill volume was established for the mixing conditions to minimize static charging due to blender wall interactions on the pharmaceutical powders. A simplex-centroid (augmented) design for 3-component system was implemented to predict and quantify the nonlinear behavior of moisture-induced cohesion between the pharmaceutical powders based on their systematic hopper discharge studies (experiments and simulations). A methodical implementation of these quantification tools was hence performed to validate a design space that enables an approach to the appropriate selection of blend concentrations that achieve minimum mixture flow variability across different humidity conditions.