Tamás Sovány

Effect of the surface free energy of materials on the lamination tendency of bilayer tablets

Dosage forms with fixed dose combinations of drugs is a frequent and advantageous mode of administration, but their production involves a number of technological problems. Numerous interactions in a homogeneous vehicle may be avoided through the use of layered tablets. The mechanical properties of these dosage forms depend on numerous process parameters and material characteristics. The aim of the present study was a detailed investigation of the relationships between the surface characteristics and deformation properties of tableting materials and the tendency of bilayer tablets to undergo lamination. Bilayer tablets were compressed from unlubricated materials with different plastic-elastic properties and surface free energies according to a mixed 2 and 3-level half-replicated factorial design. The results revealed that the surface characteristics play the main role in the lamination of layered tablets and the effect of the plastic-elastic behavior cannot be interpreted without a knowledge of these properties.

Effects of the wetting liquid and ethylcellulose on the properties of atenolol-containing pellets

The aim of this study was to investigate the influence of the wetting liquid on the properties of pellets prepared by extrusion and spheronization. Different grades of ethylcellulose were used as matrix former, with microcrystalline cellulose as filler and atenolol as model active agent. Each ethylcellulose type was applied with water alone, or with a combination of water and ethanol. The formation of the matrix and the interaction of the components were evaluated via mechanical, dissolution and morphological studies on the pellets. The presence of ethanol in the wetting liquid led to a decrease in the liberation of the active agent in the first phase of the dissolution process, but also caused a reduction in the breaking hardness of the pellets. High viscosity grade ethylcellulose gave rise to a more relevant decrease in breaking hardness. The plasticity of the mass was influenced by variation of the wetting liquid.

Modeling of subdivision of scored tablets with the application of artificial neural networks

The subdivision of scored tablets is an important problem for the exact individual therapy of patients. The recent guidelines of the EU require verification of the equal mass of the tablet halves, but this problem has previously never been investigated in papers published on the production technological aspects. Our aim was therefore to study the effects of the physicochemical properties of the raw materials and the effects of the compression process on the breaking parameters of the tablets. Artificial neural networks (ANNs) were applied for data analysis and modeling, which are very useful optimizing systems. The abilities of four different types of ANNs to predict the parameters of the compression process and the tablets were compared. The radial basis function and multilayer perceptron ANNs furnished statistically significant better results than linear or generalized regression neural networks. These ANN models revealed that the subdivision of scored tablets is strongly influenced by the production parameters and the compositions of the powder mixtures.

Comparison of the Halving of Tablets Prepared with Eccentric and Rotary Tablet Presses

The aim of this study was to compare the densification of powder mixtures on eccentric and rotary tablet presses and to establish relationships with the halving properties of the resulting scored tablets. This is an important problem because the recent guidelines of EU require verification of the equal masses of tablet halves. The models of Walker, Heckel, and Kawakita were used to describe the powder densification on the two machines. The calculated parameters revealed that the shorter compression cycle of rotary machines results in poorer densification and lower tablet hardness at a given compression force. This is manifested in poorer halving properties, which are influenced mainly by the hardness. Better densification improves the halving even at lower tablet hardness. This demonstrates that these parameters can be good predictors of tablet halving properties.

Estimation of design space for an extrusion-spheronization process using response surface methodology and artificial neural network modelling

The application of the Quality by Design principles is one of the key issues of the recent pharmaceutical developments. In the past decade a lot of knowledge was collected about the practical realization of the concept, but there are still a lot of unanswered questions. The key requirement of the concept is the mathematical description of the effect of the critical factors and their interactions on the critical quality attributes (CQAs) of the product. The process design space (PDS) is usually determined by the use of design of experiment (DoE) based response surface methodologies (RSM), but inaccuracies in the applied polynomial models often resulted in the over/underestimation of the real trends and changes making the calculations uncertain, especially in the edge regions of the PDS. The completion of RSM with artificial neural network (ANN) based models is therefore a commonly used method to reduce the uncertainties. Nevertheless, since the different researches are focusing on the use of a given DoE, there is lack of comparative studies on different experimental layouts. Therefore, the aim of present study was to investigate the effect of the different DoE layouts (2 level full factorial, Central Composite, Box-Behnken, 3 level fractional and 3 level full factorial design) on the model predictability and to compare model sensitivities according to the organization of the experimental data set. It was revealed that the size of the design space could differ more than 40% calculated with different polynomial models, which was associated with a considerable shift in its position when higher level layouts were applied. The shift was more considerable when the calculation was based on RSM. The model predictability was also better with ANN based models. Nevertheless, both modelling methods exhibit considerable sensitivity to the organization of the experimental data set, and the use of design layouts is recommended, where the extreme values factors are more represented.

Physicochemical characterisation and investigation of the bonding mechanisms of API-titanate nanotube composites as new drug carrier systems

Titanate nanotube (TNT) has recently been explored as a new carrier material for active pharmaceutical ingredients (API). The aim of the present work was to reveal the physicochemical properties of API-TNT composites, focusing on the interactions between the TNTs and the incorporated APIs. Drugs belonging to different Biopharmaceutical Classification System (BCS) classes were loaded into TNTs: diltiazem hydrochloride (BCS I.), diclofenac sodium (BCS II.), atenolol (BCS III.) and hydrochlorothiazide (BCS IV.). Experimental results demonstrated that it is feasible for spiral cross-sectioned titanate nanotubes to carry drugs and maintain their bioactivity. The structural properties of the composites were characterized by a range of analytical techniques, including FT-IR, DSC, TG-MS, etc. The interactions between APIs and TNTs were identified as electrostatic attractions, mainly dominated by hydrogen bonds. Based on the results, it can be stated that the strength of the association depends on the hydrogen donor strength of the API. The drug release of incorporated APIs was evaluated from compressed tablets and compared to that of pure APIs. Differences noticed in the dissolution profiles due to incorporation showed a correlation with the strength of interactions between the APIs and the TNTs observed in the above analytical studies.

Preparing of pellets by extrusion/spheronization using different types of equipment and process conditions.

Abstract Introduction: The focus of this work was to produce matrix pellets made by extrusion/ spheronization using two types of equipment. The aim was to accomplish the laboratory-scale I process that has been already optimized and accepted with another type of equipment (laboratory-scale II). Methods: A matrix pellet formulation consisting of MCC, Eudragit NE 30D and diclofenac sodium was used in the two types of equipment. Physico-chemical parameters and the dissolution profiles of the pellets in phosphate buffer pH 6.8 were compared. Results: Pellets from both processes were similar in shape and tensile strength. They differed in particle size and dissolution profile. This may be contributed to different spheronization conditions.

Application of Physicochemical Properties and Process Parameters in the Development of a Neural Network Model for Prediction of Tablet Characteristics

The importance of in silico modeling in the pharmaceutical industry is continuously increasing. The aim of the present study was the development of a neural network model for prediction of the postcompressional properties of scored tablets based on the application of existing data sets from our previous studies. Some important process parameters and physicochemical characteristics of the powder mixtures were used as training factors to achieve the best applicability in a wide range of possible compositions. The results demonstrated that, after some pre-processing of the factors, an appropriate prediction performance could be achieved. However, because of the poor extrapolation capacity, broadening of the training data range appears necessary.

Study of the behaviour of magnesium stearate with different specific surface areas on the surface of particles during mixing

The behaviour of two types of magnesium stearate with different specific surface areas on granule particles was examined. The magnesium stearate concentration was measured with an energy-dispersive X-ray fluorescence analyser. Different measurement procedures were used to investigate the properties of the two types of magnesium stearate when using different blending times and rotation speeds. Correlations were found between the specific surface area of the magnesium stearate, the blending time, the rotation speed and the specific surface free energy of the excipients. If magnesium stearate has a high specific surface area it shows higher adhesion work and is able to create a very thin homogeneous layer on the surface of the particles. Magnesium concentration was detected with the energy-dispersive X-ray fluorescence analyser. Based on the X-ray investigation the optimum blending time and rotation speed can be determined.

Optimization of the Critical Parameters of the Spherical Agglomeration Crystallization Method by the Application of the Quality by Design Approach

This research work presents the use of the Quality by Design (QbD) concept for optimization of the spherical agglomeration crystallization method in the case of the active agent, ambroxol hydrochloride (AMB HCl). AMB HCl spherical crystals were formulated by the spherical agglomeration method, which was applied as an antisolvent technique. Spherical crystals have good flowing properties, which makes the direct compression tableting method applicable. This means that the amount of additives used can be reduced and smaller tablets can be formed. For the risk assessment, LeanQbD Software was used. According to its results, four independent variables (mixing type and time, dT (temperature difference between solvent and antisolvent), and composition (solvent/antisolvent volume ratio)) and three dependent variables (mean particle size, aspect ratio, and roundness) were selected. Based on these, a 2–3 mixed-level factorial design was constructed, crystallization was accomplished, and the results were evaluated using Statistica for Windows 13 program. Product assay was performed and it was revealed that improvements in the mean particle size (from ~13 to ~200 µm), roundness (from ~2.4 to ~1.5), aspect ratio (from ~1.7 to ~1.4), and flow properties were observed while polymorphic transitions were avoided.