Influence of process parameters on fluidised hot-melt granulation and tablet pressing of pharmaceutical powders

This study investigates the influence of process parameters on the fluidised hot melt granulation of lactose and PEG 6000, and the subsequent tablet pressing of the granules. Granulation experiments were performed to assess the effect of granulation time and binder content of the feed on the resulting granule properties such as mass mean granule size, size distribution, granule fracture stress, and granule porosity. These data were correlated using the granule growth regime model. It was found that the dominant granule growth mechanisms in this melt granulation system were nucleation followed by steady growth (PEG 10–20% w/w). However, with binder contents greater than 20% w/w, the granulation mechanism moved to the “over-wet massing” regime in which discrete granule formation could not be obtained. The granules produced in the melt fluidised bed process were subsequently pressed into tablets using an industrial tablet press. The physical properties of the tablets: fracture stress, disintegration time and friability were assessed using industry standards. These analyses indicated that particle size and binder content of the initial granules influenced the mechanical properties of the tablets. It was noted that a decrease in initial granule size resulted in an increase in the fracture stress of the tablets formed.

Influence of fill factor variation in high shear granulation on the post granulation processes: Compression and tablet properties

This paper describes an investigation of the effect of fill factor; on the compaction behaviour of the granules during tableting and hence mechanical properties of tablets formed. The fill factor; which is the ratio of volume of wet powder material to vessel volume of the granulator, was used as an indicator of batch size. It has been established previously that in high shear granulation the batch size influences the size distribution and granule mechanical properties [1]. The work reported in this paper is an extension to the work presented in [1], hence granules from the same batches were used in production of tablets. The same tabletting conditions were employed during tabletting to allow a comparison of their properties. The compaction properties of the granules are inferred from the data generated during the tabletting process. The tablet strength and dissolution properties of the tablets were also measured. The results obtained show that the granule batch size affects the strength and dissolution of the tablets formed. The tablets produced from large batches were found to be weaker and had a faster dissolution rate. The fill factor was also found to affect the tablet to tablet variation of a non-functional active pharmaceutical ingredient included in the feed powder. Tablets produced from larger batches show greater variation compared to those from smaller batches.

A review of ADP processing software

Data processing is an essential part of Acoustic Doppler Profiler (ADP) surveys, which have become the standard tool in assessing flow characteristics at tidal power development sites. In most cases, further processing beyond the capabilities of the manufacturer provided software tools is required. These additional tasks are often implemented by every user in mathematical toolboxes like MATLAB, Octave or Python. This requires the transfer of the data from one system to another and thus increases the possibility of errors. The application of dedicated tools for visualisation of flow or geographic data is also often beneficial and a wide range of tools are freely available, though again problems arise from the necessity of transferring the data. Furthermore, almost exclusively PCs are supported directly by the ADP manufacturers, whereas small computing solutions like tablet computers, often running Android or Linux operating systems, seem better suited for online monitoring or data acquisition in field conditions. While many manufacturers offer support for developers, any solution is limited to a single device of a single manufacturer. A common data format for all ADP data would allow development of applications and quicker distribution of new post processing methodologies across the industry.

Development of sampling methods for Raman analysis of solid dosage forms of therapeutic and illicit drugs

The results of a study aimed at determining the most important experimental parameters for automated, quantitative analysis of solid dosage form pharmaceuticals (seized and model 'ecstasy' tablets) are reported. Data obtained with a macro-Raman spectrometer were complemented by micro-Raman measurements, which gave information on particle size and provided excellent data for developing statistical models of the sampling errors associated with collecting data as a series of grid points on the tablets' surface. Spectra recorded at single points on the surface of seized MDMA-caffeine-lactose tablets with a Raman microscope (lambda(ex) = 785 nm, 3 mum diameter spot) were typically dominated by one or other of the three components, consistent with Raman mapping data which showed the drug and caffeine microcrystals were ca 40 mum in diameter. Spectra collected with a microscope from eight points on a 200 mum grid were combined and in the resultant spectra the average value of the Raman band intensity ratio used to quantify the MDMA: caffeine ratio, mu(r), was 1.19 with an unacceptably high standard deviation, sigma(r), of 1.20. In contrast, with a conventional macro-Raman system (150 mum spot diameter), combined eight grid point data gave mu(r) = 1.47 with sigma(r) = 0.16. A simple statistical model which could be used to predict sigma(r) under the various conditions used was developed. The model showed that the decrease in sigma(r) on moving to a 150 mum spot was too large to be due entirely to the increased spot diameter but was consistent with the increased sampling volume that arose from a combination of the larger spot size and depth of focus in the macroscopic system. With the macro-Raman system, combining 64 grid points (0.5 mm spacing and 1-2 s accumulation per point) to give a single averaged spectrum for a tablet was found to be a practical balance between minimizing sampling errors and keeping overhead times at an acceptable level. The effectiveness of this sampling strategy was also tested by quantitative analysis of a set of model ecstasy tablets prepared from MDEA-sorbitol (0-30% by mass MDEA). A simple univariate calibration model of averaged 64 point data had R-2 = 0.998 and an r.m.s. standard error of prediction of 1.1% whereas data obtained by sampling just four points on the same tablet showed deviations from the calibration of up to 5%.

Improved Process Monitoring Using Nonlinear Principal Component Models

This paper presents two new approaches for use in complete process monitoring. The firstconcerns the identification of nonlinear principal component models. This involves the application of linear
principal component analysis (PCA), prior to the identification of a modified autoassociative neural network (AAN) as the required nonlinear PCA (NLPCA) model. The benefits are that (i) the number of the reduced set of linear principal components (PCs) is smaller than the number of recorded process variables, and (ii) the set of PCs is better conditioned as redundant information is removed. The result is a new set of input data for a modified neural representation, referred to as a T2T network. The T2T NLPCA model is then used for complete process monitoring, involving fault detection, identification and isolation. The second approach introduces a new variable reconstruction algorithm, developed from the T2T NLPCA model. Variable reconstruction can enhance the findings of the contribution charts still widely used in industry by reconstructing the outputs from faulty sensors to produce more accurate fault isolation. These ideas are illustrated using recorded industrial data relating to developing cracks in an industrial glass melter process. A comparison of linear and nonlinear models, together with the combined use of contribution charts and variable reconstruction, is presented.

The manufacture and characterisation of hot-melt extruded enteric tablets

The aim of this highly novel study was to use hot-melt extrusion technology as an alternative process to enteric coating. In so doing, oral dosage forms displaying enteric properties may be produced in a continuous, rapid process, providing significant advantages over traditional pharmaceutical coating technology. Eudragit (R) L100-55, an enteric polymer, was pre-plasticized with triethyl citrate (TEC) and citric acid and subsequently dry-mixed with 5-aminosalicylic acid, a model active pharmaceutical ingredient (API), and an optional gelling agent (PVP (R) K30 or Carbopol (R) 971P). Powder blends were hot-melt extruded as cylinders, cut into tablets and characterised using powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC) and dissolution testing conducted in both pH 1.2 and pH 6.8 buffers. Increasing the concentration of TEC significantly lowered the glass transition temperature (T,) of Eudragit (R) L100-55 and reduced temperatures necessary for extrusion as well as the die pressure. Moreover, citric acid (17% w/w) was shown to act as a solid-state plasticizer. HME tablets showed excellent gastro-resistance, whereas milled extrudates compressed into tablets released more than 10% w/w of the API in acidic media. Drug release from HME tablets was dependent upon the concentration of TEC, the presence of citric acid, PVP K30, and Carbopol (R) 971P in the matrix, and pH of the dissolution media. The inclusion of an optional gelling agent significantly reduced the erosion of the matrix and drug release rate at pH 6.8; however, the enteric properties of the matrix were lost due to the formation of channels within the tablet. Consequently this work is both timely and highly innovative and identifies for the first time a method of producing an enteric matrix tablet using a continuous hot-melt extrusion process.