Fluid Bed Granulation Articles

One of the ingredients in Granular Dynamics (or DEM) is a description of interparticleforces. In this paper the effect of surface roughness o­n Hamaker and liquid bridgeinteractions is investigated. Three different models are used (excluded volume, stochasticroughness and explicit asperities). In general, the latter two give similar results. Roughnessdecreases interactions up to several orders of magnitude for rigid surfaces. To validate theanalytical results o­n liquid bridge interactions at low humidity, molecular dynamicssimulations were also performed o­n model systems.



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In a fluidized bed in which the particles vary in size or density segregation can occur.Including horizontal sieve-like baffles in the bed can greatly increase the tendency of powdersto segregate. This can make a fluidized bed particle classification process possible. In thisarticle a feasibility study of such a process is presented.Experiments were performed with a model system. It was found that the baffles increase thepurity of both the ‘flotsam’ and the ‘jetsam’ fractions. The capacity of a fluidized bed particleclassifier can be estimated using a mechanistic model, based o­n literature models. With sucha model we found that the baffles are most effective in systems that tend to segregate but doactually hardly segregate without baffles.

The movement of particles in fluidization processes in a model test reactor has been studied using an imaging technique from medical healthcare: Positron Emission Tomography (PET). With this noninvasive technique, tracer particles were followed o­n their way through the fluidized bed. Experiments were performed with pulses of tracer particles in different alignments. The results give a good impression of both axial and radial distribution of particles in fluidized bed. In this paper, the experimental results confirm the basic assumptions of the model. Our stochastic model captures the dynamic movement of particles qualitatively, but indications are that the system exhibits ‘gulfstreaming’, a feature which is not accounted for in the model, but is common in fluidized beds in practice.




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This paper describes a series of experiments tracing a single radioactive particle in a fluidized bed in an ECAT EXACT HR+ PET camera in order to obtain 3-D paths for an actual bed particle – i.e. a particle typical for the bed material – with a high spatial and temporal resolution. The paper describes how "lines of response" (LORs) were calculated from the binary list-mode files from the camera, and how particle positions (1 per ms) were computed from the LORs. It also gives a condensed account of how the data were analyzed further. The particle movement in the bed is shown graphically, and the findings interpreted in light of the theories o­n mechanisms behind particle movement in fluidized beds. Among other things the issue of fast, short-range movement of particles in fluidized beds is discussed. The findings are consistent with the notion of upward particle motion in the wakes of fluidization bubbles, and downward motion in the bulk.

This study assesses the fluidized bed granulation process for the optimization of a model formulation using in-line near-infrared (NIR) spectroscopy for moisture determination. The granulation process was analyzed using an automated granulator and optimization of the verapamil hydrochloride formulation was performed using a mixture design. The NIR setup with a fixed wavelength detector was applied for moisture measurement. Information from other process measurements, temperature difference between process inlet air and granules (Tdiff), and water content of process air (AH), was also analyzed. The application of in-line NIR provided information related to the amount of water throughout the whole granulation process. This information combined with trend charts of Tdiff and AH enabled the analysis of the different process phases. By this means, we can obtain in-line documentation from all the steps of the processing.

Spray-drying is known to produce predominantly amorphous material because of rapid solidification.1 The detection and control of the amorphous portion of powdered material is of utmost importance, as different physical forms of materials have different physicochemical properties that give rise to significant differences in functionality when used in dosage forms. The influence of spray-drier feed concentration o­n the degree of crystallinity and the crystal form of lactose (β-lactose, anhydrous α-lactose, α-lactose monohydrate) has been described previously.2It is known2 that the spray-drying process can be made to produce completely amorphous lactose particles. Furthermore, it is clear that the amorphous form is unstable and that it will revert to the crystalline form.

Dilip M. Parikh,

HERCULES : Pharmaceutical Technology Report

Eetu Räsänen, Osmo Antikainen, Jouko Yliruusi
AAPS PharmSciTech. 2003; 4(4): article 53. The purpose of this research was to develop a new method to predict the flow behavior of pharmaceutical powders using a multichamber microscale fluid bed. Different amounts of poorly flowing paracetamol were added to various grades of microcrystalline celluloses and silicified microcrystalline cellulose powders. Magnesium stearate was used as a lubricant. Experimental minimum fluidization velocities (umf) were defined using 2 to 4 g (equal to 10 mL) of material (Video 1). The reference flowability of the powders was determined using a specific flow meter. Also, the weight variation of the compressed powders, using a single-punch press, was measured. When the amount of paracetamol in the excipients was increased, the experimental umf increased and the fluidization behavior grew worse (Video 2).

Dilip M. Parikh, Niro Inc Significant amounts of solid materials are processed using fluid-bed technology. Suspension and movement of particles in an airstream maximizes the exposure of particle surfaces to air or gas, producing efficient evaporation. The primary factor influencing a fluidized-bed process is airflow. To understand and manipulate processing in a fluid bed, it is important to learn how airflow is generated, conditioned, and distributed through the bed during drying, agglomerating, and coating. This article describes how uncommon pressure drops and related processing problems can be identified and rectified by studying the airflow of the system

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