Comparison between and evaluation of some methods for the assessment of the sphericity of pellets

Image analysis by pulse coupled neural networks (PCNN)—a novel approach in granule size characterization

A biologically inspired spiking neural network model, the pulse coupled neural network (PCNN), has been applied for the first time in bulk particle characterization, and specifically in the characterization of pharmaceutical granule size distributions. The PCNN was trained on surface images of pharmaceutical granule beds, and the adjustable parameters (radius neuron interconnection, r0, linking weight coefficient, β, local threshold potential, VΘ, and number of iterations) were successfully optimized using design of experiments. As demonstrated with size fractions of granules, it was found that the PCNN produced granule size-dependent signals. In general, a first highest and relatively narrow peak located in the region of two to twelve iterations corresponded to smaller particle size, while larger particles resulted in wider peaks and in highest (not first) peak at a range between 13 and 25 iterations. Better predictions, i.e. lower RMSEP (root mean squared error of prediction) values, were obtained using high β value, low r0 and VΘ values, while the number of iterations had to exceed 110 and the optimized model (RMSEP lower than 5) corresponded to PCNN variables: r0 = 1, β = 0.4, VΘ = 2, and number of iterations = 150. The coefficient of determination (R2) of the model was 0.94 and the predicted variation (Q2) was 0.91, while the Pearson correlation coefficient between the predicted and the measured mean particle size by sieving for eight test batches was 0.98. These findings could be characterized as promising and encouraging for the further use of image analysis by PCNNs in pharmaceutical bulk particle size and shape characterization.

The evaluation of modified microcrystalline cellulose for the preparation of pellets with high drug loading by extrusion/spheronization

The performance of microcrystalline cellulose (MCC) which had been modified by the inclusion of various levels of sodium carboxymethylcellulose (SCMC) in the wet cake prior to drying, in terms of their ability to form pellets by a standardised extrusion/spheronization process has been assessed. Initial screening of the ability of the modified MCCs to form pellets with an 80% level of lactose as a model drug identified two potential products containing 6 or 8% of SCMC (B 6 and B 8). These two products were compared with a standard grade of MCC (Avicel PH101) in terms of their ability to produce pellets with 80% of model drugs of low (ibuprofen), intermediate (lactose) and high (ascorbic acid) water solubility when subjected to a standardised extrusion/spheronization process. Also assessed was their ability to retain water with applied pressure using a pressure membrane technique and their ability to restrict water migration during extrusion with a ram extruder. The two new types of MCC (B 6 and B 8) were able to form good quality pellets with all three model drugs, whereas Avicel PH101 could not form pellets with this high level of ibuprofen. This improved performance was related to the ability of the new types of MCC to hold higher levels of water within their structure and restrict the migration of water in the wet mass when subjected to pressure applied during the process of preparing the pellets. There is evidence to show that the two new types of MCC can function over a wider range of water contents than Avicel PH101 and that they have an improved performance if the extrusion process is rapid and if, after incorporation of the water into the powder, the sample is stored for some time before extrusion.

Microscopic image analysis techniques for the morphological characterization of pharmaceutical particles: Influence of the software, and the factor algorithms used in the shape factor estimation

The present report highlights the difficulties of particle shape characterizations of multiparticulate systems obtained using different image analysis techniques. The report describes and discusses a number of shape factors that are widely used in pharmaceutical research. Using photographs of 16 pellets of different shapes, obtained by extrusion-spheronization, we investigated how shape factor estimates vary depending on method of calculation, and among different software packages. The results obtained indicate that the algorithms used (both for estimation of basic dimensions such as perimeter and maximum diameter, and for estimation of shape factors on the basis of these basic dimensions) have marked influences on the shape factor values obtained. These findings suggest that care is required when comparing results obtained using different image analysis programs.

Image Analysis of the Shape of Granulated Powder Grains

This study presents and evaluates two new form factors for the characterization of pharmaceutical microparticles using image analysis techniques. The first factor, denoted Vr, is mean percentage variation in radial chord length (for a large number of radial chords drawn at small angular intervals) with respect to mean radial chord length. The second factor, denoted Vp, is percentage deviation of measured perimeter from the perimeter of a circle with radius equal to the mean radial chord length of the particle. Considering both ideal shapes and real pharmaceutical particle populations, these factors are compared with other form factors widely used in pharmaceutical technology. Our results indicate that Vr and Vp allow effective assessment of whether the particles of a given population show pharmaceutically significant deviations from sphericity. The two factors additionally facilitate identification of the basic shapes of particle outlines (notably ellipsoid, rectangular, and irregular). These factors may thus be of value for the characterization and monitoring of pharmaceutical pelleting processes.

Does a powder surface contain all necessary information for particle size distribution analysis?

The aim of this study was to utilise a new approach where digital image information is used in the characterisation of particle size distributions of a large set of pharmaceutical powders. A novel optical set-up was employed to create images and calculate a stereometric parameter from the digital images of powder surfaces. Analysis was made of 40 granule batches with varying particle sizes and compositions prepared with fluidised bed granulation. The extracted digital image information was then connected to particle size using multivariate modelling. The modelled particle size distributions were compared to particle size determinations with sieve analysis and laser diffraction. The results revealed that the created models corresponded well with the particle size distributions measured with sieve analysis and laser diffraction. This study shows that digital images taken from powder surfaces contain all necessary data that is needed for particle size distribution analysis. To obtain this information from images careful consideration has to be given on the imaging conditions. In conclusion, the results of this study suggest that the new approach is a powerful means of analysis in particle size determination. The method is fast, the sample size needed is very small and the technique enables non-destructive analysis of samples. The method is suitable in the particle size range of approximately 20-1500 microm. However, further investigations with a broad range of powders have to be made to obtain information of the possibilities and limitations of the introduced method in powder characterisation.

Evaluation and simultaneous optimization of some pellets characteristics using a 3(3) factorial design and the desirability function

A 3(3) full factorial design study has been employed in order to investigate the effect of three variables on size, size distribution and three shape parameters, namely roundness, elongation and e(R), of pellets prepared in a fluid bed rotor granulator with the wet granulation technique. The first variable was a formulation variable, the % w/w content of microcrystalline cellulose (MCC) and the other two variables were processing variables, the temperature of inlet air and the spray rate of the granulation liquid. The analysis of variance showed that the three variables had a significant effect (P<0.05) on pellet size and the shape factors, while only the spray rate influenced the particle size distribution. Significant interactions between the factors, for the size and the shape, were also found. The multiple regression analysis of the results led to equations that adequately describe the influence of the independent variables on the selected responses. Furthermore, the desirability function was employed in order to optimize the process under study. It was found that the optimum values of the responses could be obtained at the low levels of the % w/w content of MCC and temperature of inlet air and at the high level of the spray rate.

Preparation of pellets of different shape and their characterization

Pellets of different shapes were produced by modifying the processing parameters of a standardized pellet formulation. The target size of these pellets was 1-1.4 mm. Initially the shape of the pellets was assessed by visual observation. In total, eight batches of pellets were produced of which four were considered to be round, whereas the other four deviated from the spherical shape by various degrees. The different pellet fractions were then characterized for their size, shape, surface, and density properties employing a series of established techniques in order to identify the most appropriate method of characterization and the interrelationships between these properties. The results showed that attempting a task of preparing pellets of graded differences in shape from the same powder blend can result in changes of other important pellet properties such as surface roughness, surface area, and pellet dimensions. Some of these changes could be anticipated by considering the process variables involved, whereas others changed in a manner for which there is no immediate explanation.

Effect of drying rate on porosity and tabletting behaviour of cellulose pellets

The purpose of this study was to investigate the effect of drying rate during static drying on certain physical properties of pellets. Pellets were prepared from microcrystalline cellulose by granulation with different agglomeration liquids (various ethanol/water ratios) and thereafter dried without agitation at different drying rates. The dry pellets were characterised with respect to their shape, porosity, and compression shear strength and the tensile strength of tablets formed from pellets with low and high drying rates was determined. Drying of the pellets occurred at a falling rate and the reduction in liquid content with time obeyed a first order type of relationship. An increased drying rate did not affect the shape and surface texture of the dried pellets and did not cause them to fracture. However, the drying conditions did affect pellet porosity, with an increased drying rate resulting in more porous pellets. Through a relationship with pellet porosity, the drying rate also affected the deformability of the pellets (as assessed from Kawakita 1/b values) and their ability to form tablets. Owing to a strong effect of porosity on pellet compactability, marked changes in tablet tensile strength with variations in drying rate may be obtained.

Micromeritic and packing properties of diclofenac pellets and effects of some formulation variables

The effects of two common diluents (microcrystalline cellulose and calcium phosphate dihydrate), two binding agents (gelatin and methacrylic polymer), and spheronization on the micromeritic (size, shape, density), flow, and packing properties of sodium diclofenac pellets were examined. The shape was assessed as the aspect ratio and was correlated to the flow rate and to the deviation of the tapped porosity from the value of 26%, which corresponds to the ideal rhombohedral packing of spheres. It was found that porosity deviation decreased greatly with spheronization, but it increased with hinder addition. Porosity deviation was proportional to the aspect ratio, while flow rate decreased logarithmically with porosity deviation. Porosity deviation may be a useful index for monitoring the quality of pellets, similar to the aspect ratio, as a successful, simple, and indirect indication of sphericity and of surface roughness as well.

Content-based image retrieval: a new promising technique in powder technology

The aim of the present study was to introduce a new technique for analyzing powders by examining the content information of images of pharmaceutical powder systems. Texture features of images of microcrystalline cellulose were compared by using a content-based image retrieval system (CBIR), QBIC (Query-by-Image-Content). The rank order and image similarities were compared to particle sizes and appearances of different mixtures. The image order of the similarity values was in close agreement with the appearance and particle size of the mixtures. When the image of pure Avicel PH 101 was used as a query image, the most similar images were always from images of mixtures with a large number of particles with smaller particle mean sizes. When images of pure Avicel PH 200 were used as a query image, the closest matches of image similarity were from images of mixtures with a larger amount of larger particles. The results show that the CBIR system extracts applicable content information on images of powders, but the texture features used were not totally adequate for analysis of the powders used. In general, content-based image retrieval seems to be a promising approach to efficiently use the vast image information that is available from pharmaceutical powders. Nevertheless, to achieve an efficient CBIR tool for powder technology requires development of substantial algorithms for feature extraction.

Evaluation of a standardised procedure to assess the shape of pellets using image analysis

The influence of threshold definition, number of pellets counted, image magnification and lightning technique on the assessment of pellet shape has been investigated using three batches of pellets and an image analysis system. The pellet parameters measured were 'aspect ratio', 'circularity', 'projection sphericity', 'e(R)' and 'Feret diameter.' The methodical error, reproducibility and repeatability of the results were chosen as statistical test parameters. The position of the light source is crucial in providing an accurate particle size value. Top light was identified as the illumination technique that gave a mean pellet size similar to the true pellet size. The use of a light table produced significantly larger pellet size values. A minimum pixel resolution appears necessary for an accurate shape parameter definition. One pixel should not cover more than 30 microm for pellets of an average particle size of 1.2 mm. Shape descriptors, which are based on a multiple combination of area and perimeter data such as the circularity, are greatly dependent on the number of pellets counted. Shape factors, which do not (aspect ratio) or only as a single value do involve an area or perimeter measurement (e(R), projection sphericity) are, however, nearly independent of the number of pellets counted, as long as the magnification is sufficiently large and the pellets are randomly drawn from the batch. For nearly spherical particles, the methodical error is below 1%, but for elongated particles this error can reach 5%. The repeatability is also very good for nearly spherical particles (<2%), but increases to very large values if the particles are clearly elongated. The limiting values for the various shape factors should be reconsidered. An upper value for the aspect ratio of 1.1 and a lower value of 0.6 for e(R) are recommended. The circularity should not be used as the shape factor to characterise spheres, because errors in image recognition can affect strongly the applicability of this shape factor. The projection sphericity has only a limited sensitivity to variations in particle shape.