Zorica Djuric

Preparation of carbamazepine–Soluplus® solid dispersions by hot-melt extrusion, and prediction of drug–polymer miscibility by thermodynamic model fitting

Hot-melt extrusion (HME) is a dust- and solvent-free continuous process enabling the preparation of a variety of solid dosage forms containing solid dispersions of poorly soluble drugs into thermoplastic polymers. Miscibility of drug and polymer is a prerequisite for stable solid dispersion formation. The present study investigates the feasibility of forming solid dispersions of carbamazepine (CBZ) into polyethyleneglycol-polyvinyl caprolactam-polyvinyl acetate grafted copolymer (Soluplus) by hot-melt extrusion. Physicochemical properties of the raw materials, extrudates, co-melted products, and corresponding physical mixtures were characterized by thermo-gravimetric analysis (TGA), differential scanning calorimetry (DSC), attenuated total reflectance infrared (ATR-FTIR) spectroscopy and hot stage microscopy (HSM), while miscibility of CBZ and Soluplus was estimated on the basis of the Flory-Huggins theory, Hansen solubility parameters, and solid-liquid equilibrium equation. It was found that hot-melt extrusion of carbamazepine and Soluplus is feasible on a single-screw hot-melt extruder without the addition of plasticizers. DSC analysis and FTIR spectroscopy revealed that a molecular dispersion is formed when the content of CBZ does not exceed ∼5% w/w while higher CBZ content results in a microcrystalline dispersion of CBZ form III crystals, with the molecularly dispersed percentage increasing with extrusion temperature, at the risk of inducing transformation to the undesirable form I of CBZ. Thermodynamic modeling elucidated potential limitations and temperature dependence of solubility/dispersibility of carbamazepine in Soluplus hot-melt extrudates. The results obtained by thermodynamic models are in agreement with the findings of the HME processing, encouraging therefore their further application in the HME process development.

The application of generalized regression neural network in the modeling and optimization of aspirin extended release tablets with Eudragit® RS PO as matrix substance

The objective of this work is to use a generalized regression neural network (GRNN) in the design of extended-release aspirin tablets. As model formulations, 10 kinds of aspirin matrix tablets were prepared. Eudragit RS PO was used as matrix substance. The amount of Eudragit RS PO and compression pressure were selected as causal factors. In-vitro dissolution-time profiles at four different sampling times, as well as coefficients n (release order) and log k (release constant) from the Peppas equation were estimated as release parameters. A set of release parameters and causal factors were used as tutorial data for the GRNN and analyzing using a computer. A GRNN model was constructed. The optimized GRNN model was used for prediction of formulation with desired in vitro drug release. For two tested formulations there was very good agreement between the GRNN predicted and observed in vitro profiles and estimated coefficients. Calculated difference (f(1)) and similarity (f(2)) factors indicate that there is no difference between predicted and experimental observed drug release profiles. This work illustrates the potential for an artificial neural network, GRNN, to assist in development of extended-release dosage forms. This method can be employed to achieve a desired in vitro dissolution profile.

Tablet disintegration and drug dissolution in viscous media: paracetamol IR tablets.

An investigation into the influence of viscous media on tablet disintegration and drug dissolution was performed with the aim to simulate the potential formulation-specific food effect for a selected highly soluble model drug. Literature data on the in vivo drug absorption in fasted and fed state have been evaluated for in vitro-in vivo correlation (IVIVC) purposes. In vitro studies were conducted in simple buffer media with or without addition of HPMC K4M as a viscosity enhancing agent. Good IVIVC correlation (r>0.95) was obtained for paracetamol dissolution in viscous media at 50rpm and fed state absorption profiles, while in vitro dissolution in simple media at lower stirring speed was predictable of drug products in vivo behaviour in the fasted state. The data obtained support the existing idea that relatively simple dissolution media and/or set of experimental conditions may be used to differentiate formulation-specific food-drug interactions. Such tests would be a useful tool in the development of formulations that would not be susceptible to the influence of co-administered meal and, furthermore, facilitate regulatory decision on the necessity to conduct food effect studies in vivo.

Artificial Neural Networks in the Modeling and Optimization of Aspirin Extended Release Tablets With Eudragit L 100 as Matrix Substance

The purpose of the present study was to model the effects of the concentration of Eudragit L 100 and compression pressure as the most important process and formulation variables on the in vitro release profile of aspirin from matrix tables formulated with Eudragit L 100 as matrix substance and to optimize the formulation by artificial neural network. As model formulations, 10 kinds of aspirin matrix tablets were prepared. The amount of Eudragit L 100 and the compression pressure were selected as causal factors. In vitro dissolution time profiles at 4 different sampling times were chosen as responses. A set of release parameters and causal factors were used as tutorial data for the generalized regression neural, network (GRNN) and analyzed using a computer. Observed results of drug release studies indicate that drug release rates vary widely between investigated formulations, with a range of 5 hours to more than 10 hours to complete dissolution. The GRNN model was optimized. The root mean square value for the trained network was 1.12%, which indicated that the optimal GRNN model was reached. Applying the generalized distance function method, the optimal tablet formulation predicted by GRNN was with 5% of Eudragit L 100 and tablet hardness 60N. Calculated difference (f1 2.465) and similarity (f2 85.61) factors indicate that there is no difference between predicted and experimentally observed drug release profiles for the optimal formulation. This work illustrates the potential for an artificial neural network, GRNN, to assist in development of extended release dosage forms.

Improvement of Aripiprazole Solubility by Complexation with (2-Hydroxy)propyl-β-cyclodextrin Using Spray Drying Technique

Due to the fact that the number of new poorly soluble active pharmaceutical ingredients is increasing, it is important to investigate the possibilities of improvement of their solubility in order to obtain a final pharmaceutical formulation with enhanced bioavailability. One of the strategies to increase drug solubility is the inclusion of the APIs in cyclodextrins. The aim of this study was to investigate the possibility of aripiprazole solubility improvement by inclusion in (2-hydroxy)propyl-β-cyclodextrin (HPBCD) and simultaneous manipulation of pH of the medium and addition of polyvinylpyrrolidone. Aripiprazole–HPBCD complexes were prepared by spray drying aqueous drug–HPBCD solutions, and their properties were compared with those prepared by solvent-drop co-grinding and physical mixing. The obtained powders were characterized by thermoanalytical methods (TGA and DSC), FTIR spectroscopy, their dissolution properties were assessed, while the binding of aripiprazole into the cavity of HPBCD was studied by molecular docking simulations. The solubilization capacity was found to be dependent on pH as well as the buffer solution’s ionic composition. The presence of PVP in the formulation could affect the solubilization capacity significantly, but further experimentation is required before its effect is fully understood. On the basis of solubility studies, the drug/HPBCD stoichiometry was found to be 1:3. The spray-dried products were free of crystalline aripiprazole, they possessed higher solubility and dissolution rate, and were stable enough over a prolonged period of storage. Spray drying of cyclodextrin solutions proved to be an appropriate and efficient technique for the preparation of highly soluble inclusion compounds of aripiprazole and HPBCD.

Influence of hydrophilic polymers on the complexation of carbamazepine with hydroxypropyl-β-cyclodextrin

In this study binary carbamazepine-hydroxypropyl-β-cyclodextrin, as well as ternary carbamazepine-hydroxypropyl-β-cyclodextrin-hydrophilic polymer systems were used to improve dissolution rate of carbamazepine. It has been shown that addition of hydrophilic polymers (Soluplus® and two types of hydroxypropyl methylcellulose-Metolose® 90SH-100 and Metolose® 65SH-1500) significantly increased solubilization capacity of hydroxypropyl-β-cyclodextrin for carbamazepine. Evaluation of carbamazepine-hydroxypropyl-β-cyclodextrin-hydrophilic polymer interactions using molecular modeling techniques showed interactions between carbamazepine, which dissociates from inclusion complexes and hydroxypropyl methylcellulose that can prevent crystallization of dissolved carbamazepine. These results can contribute to better understanding of drug-cyclodextrin-hydrophilic polymer interactions which are still not well understood. After evaluation of carbamazepine solubilization with hydroxypropyl-β-cyclodextrin and hydrophilic polymers, both binary carbamazepine-hydroxypropyl-β-cyclodextrin and ternary carbamazepine-hydroxypropyl-β-cyclodextrin-hydrophilic polymer systems were prepared by spray drying. The results of solid state characterization methods showed amorphous nature of carbamazepine in all spray dried systems, which together with the results of molecular modeling techniques indicates inclusion complex formation. Carbamazepine dissolution rate was significantly improved from spray dried formulations compared to pure drug. Binary carbamazepine-hydroxypropyl-β-cyclodextrin and ternary carbamazepine-hydroxypropyl-β-cyclodextrin-Soluplus® systems exhibited the fastest carbamazepine release, wherein the entire amount of carbamazepine was released during first 5 min.

Artificial neural networks in evaluation and optimization of modified release solid dosage forms.

Implementation of the Quality by Design (QbD) approach in pharmaceutical development has compelled researchers in the pharmaceutical industry to employ Design of Experiments (DoE) as a statistical tool, in product development. Among all DoE techniques, response surface methodology (RSM) is the one most frequently used. Progress of computer science has had an impact on pharmaceutical development as well. Simultaneous with the implementation of statistical methods, machine learning tools took an important place in drug formulation. Twenty years ago, the first papers describing application of artificial neural networks in optimization of modified release products appeared. Since then, a lot of work has been done towards implementation of new techniques, especially Artificial Neural Networks (ANN) in modeling of production, drug release and drug stability of modified release solid dosage forms. The aim of this paper is to review artificial neural networks in evaluation and optimization of modified release solid dosage forms.

Preparation and dissolution characteristics of controlled release diltiazem pellets

AbstractDifferent series of Diltiazem pellets with slow release of the active substance were prepared, by pan coating technique, using different mixtures of acrylic polymers (Eudragit E, Eudragit L, Eudragit RL and Eudragit RS) as film coating agents. The thickness of the coatings were varied by different amounts of Eudragit. Release profiles of Diltiazem hydrochloride were investigated using USP XX rotating basket method (Erweka DT-D6) with 1000 ml buffer solution (pH values 1.5; 2.2; 5.5; 6.8; 7.0) at 37°C as solvent. In vitro dissolution findings showed that Eudragit coatings gave prolonged release of Diltiazem hydrochloride. The permeability of coatings in gastric and intenstinal juices was found to be influenced by the amount of Eudragit L in the formulation. Also, the drug release rate was found to be dependent on the amount of coating applied. In order to understand the drug release mechanism better, the release data were tested assuming common kinetic models. In the present study square - root of ...

Effect of composition in the development of carbamazepine hot-melt extruded solid dispersions by application of mixture experimental design

This study investigates the application of hot‐melt extrusion for the formulation of carbamazepine (CBZ) solid dispersions, using polyethyleneglycol‐polyvinyl caprolactam‐polyvinyl acetate grafted copolymer (Soluplus, BASF, Germany) and polyoxyethylene–polyoxypropylene block copolymer (Poloxamer 407). In agreement with the current Quality by Design principle, formulations of solid dispersions were prepared according to a D‐optimal mixture experimental design, and the influence of formulation composition on the properties of the dispersions (CBZ heat of fusion and release rate) was estimated.

Dissolution rate enhancement and physicochemical characterization of carbamazepine-poloxamer solid dispersions

Abstract This study investigates the potential of poloxamers as solid dispersions (SDs) carriers in improving the dissolution rate of a poorly soluble drug, carbamazepine (CBZ). Solid dispersions were prepared with poloxamer 188 (P188) and poloxamer 407 (P407) by melting method in different drug:carrier ratios (1:1, 1:2 and 1:3). Prepared samples were characterized using differential scanning calorimetry (DSC), hot-stage polarized light microscopy (HSM), powder X-ray diffraction (PXRD) and Fourier transform infrared spectroscopy (FT-IR) to investigate drug physical state within the SDs matrix, possible polymorphic transitions and drug-polymer interactions. The interactions between CBZ molecules and polymeric chains were also evaluated using molecular dynamics simulation (MDS) technique. The most thermodynamically stable polymorphic form III of CBZ was present in all SDs, regardless of the type of poloxamer and drug-to-carrier ratio. The absence of drug-polymer interactions was observed by FT-IR analysis and additionally confirmed by MDS. Formation of persistent hydrogen bond between two CBZ molecules, observed by MDS indicate high tendency of CBZ molecules to aggregate and form crystalline phase within dispersion. P188 exhibit higher efficiency in increasing CBZ dissolution rate due to its more pronounced hydrophilic properties, while increasing poloxamers concentration resulted in decreasing drug release rate, as a consequence of their thermoreversible gelation.