Combined application of mixture experimental design and artificial neural networks in the solid dispersion development.

This study for the first time demonstrates combined application of mixture experimental design and artificial neural networks (ANNs) in the solid dispersions (SDs) development. Ternary carbamazepine-Soluplus®-poloxamer 188 SDs were prepared by solvent casting method to improve carbamazepine dissolution rate. The influence of the composition of prepared SDs on carbamazepine dissolution rate was evaluated using d-optimal mixture experimental design and multilayer perceptron ANNs. Physicochemical characterization proved the presence of the most stable carbamazepine polymorph III within the SD matrix. Ternary carbamazepine-Soluplus®-poloxamer 188 SDs significantly improved carbamazepine dissolution rate compared to pure drug. Models developed by ANNs and mixture experimental design well described the relationship between proportions of SD components and percentage of carbamazepine released after 10 (Q10) and 20 (Q20) min, wherein ANN model exhibit better predictability on test data set. Proportions of carbamazepine and poloxamer 188 exhibited the highest influence on carbamazepine release rate. The highest carbamazepine release rate was observed for SDs with the lowest proportions of carbamazepine and the highest proportions of poloxamer 188. ANNs and mixture experimental design can be used as powerful data modeling tools in the systematic development of SDs. Taking into account advantages and disadvantages of both techniques, their combined application should be encouraged.

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

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.

A case study of in silico modelling of ciprofloxacin hydrochloride/metallic compound interactions.

With the development of physiologically based absorption models, there is an increased scientific and regulatory interest in in silico modelling and simulation of drug-drug and drug-food interactions. Clinically significant interactions between ciprofloxacin and metallic compounds are widely documented. In the current study, a previously developed ciprofloxacin-specific in silico absorption model was employed in order to simulate ciprofloxacin/metallic compound interaction observed in vivo. Commercially available software GastroPlus™ (Simulations Plus Inc., USA) based on the ACAT model was used for gastrointestinal (GI) simulations. The required input parameters, relating to ciprofloxacin hydrochloride physicochemical and pharmacokinetic characteristics, were experimentally determined, taken from the literature or estimated by GastroPlus™. Parameter sensitivity analysis (PSA) was used to assess the importance of selected input parameters (solubility, permeability, stomach and small intestine transit time) in predicting percent drug absorbed. PSA identified solubility and permeability as critical parameters affecting the rate and extent of ciprofloxacin absorption. Using the selected input parameters, it was possible to generate a ciprofloxacin absorption model, without/with metal cation containing preparations co-administration, which matched well the in vivo data available. It was found that reduced ciprofloxacin absorption in the presence of aluminium hydroxide, calcium carbonate or multivitamins/zinc was accounted for by reduced drug solubility. The impact of solubility-permeability interplay on ciprofloxacin absorption can be observed in the ciprofloxacin-aluminium interaction, while in ciprofloxacin-calcium and ciprofloxacin-zinc interactions, effect of solubility was more pronounced. The results obtained indicate that in silico model developed can be successfully used to complement relevant in vitro studies in the simulation of physicochemical ciprofloxacin/metallic compound interactions.

Preliminary evaluation of the in vitro release and in vivo absorption in rabbits of the modified-release dosage forms.

OBJECTIVE: The suitability of the rabbit as an animal model for the primary screening and selection of the pilot scale batches during the early stages of the formulation development was studied. MATERIALS AND METHODS: Three modified-release formulations of aminophylline consisted of Carbopol® 971P/HPMC K4M (F-I), and HPMC K100M (F-II) or HPMC K4M (F-III) were used. Commercial products were Aminofilin retard 350 mg tablets, Srbolek, Serbia (R-I) and Phyllocontin(®) 350, tablets Purdue Frederic, Canada (R-II). RESULTS: Calculated release rate constants and the ƒ2 values between R-I/F-I (84.1) and R-II/F-III (83.4) indicated similar in vitro release while the coefficient n showed presence of different mechanisms of release from Anomalous transport, Fickian diffusion to Case-II transport. Higher Tmax, was found in the rabbits, dosed with F-II (12.00 h), F-III (10.50 h), and R-II (15.00 h) formulation. The highest Cmax (9.22 mg/L) was obtained with F-II, similar lower values was seen for F-I and F-III, while commercial products showed the lowest values R-I (5.58 mg/L) and R-II (4.18 mg/L). Higher AUC values were detected for all three formulations (from 115.90 to 204.06 mgh/L) in relation to commercial products (105.33 and 113.25 mgh/L). DISCUSSION AND CONCLUSION: The results demonstrated a good correlation of Level A (r(2) = 0.97) for the two formulations (F-I, F-III) and commercial product (R-I) indicates that there is a reasonable assumption that the rabbit might be use as a model for the preliminary comparison of scale up formulations in the early stages of the product development.

Improvement of aripiprazole solubility by complexation with (2-hydroxy)propyl-ß-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-ß-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.

In vitro-in vivo correlation for gliclazide immediate-release tablets based on mechanistic absorption simulation.

The aim of this study was to develop a drug-specific absorption model for gliclazide (GLK) using mechanistic gastrointestinal simulation technology (GIST) implemented in GastroPlus(TM) software package. A range of experimentally determined, in silico predicted or literature data were used as input parameters. Experimentally determined pH-solubility profile was used for all simulations. The human jejunum effective permeability (P (eff)) value was estimated on the basis of in vitro measured Caco-2 permeability (literature data). The required PK inputs were taken from the literature. The results of the simulations were compared with actual clinical data and revealed that the GIST-model gave accurate prediction of gliclazide oral absorption. The generated absorption model provided the target in vivo dissolution profile for in vitro-in vivo correlation and identification of biorelevant dissolution specification for GLK immediate-release (IR) tablets. A set of virtual in vitro data was used for correlation purposes. The obtained results suggest that dissolution specification of more than 85% GLK dissolved in 60 min may be considered as "biorelevant" dissolution acceptance criteria for GLK IR tablets.

Application of design of experiments and multilayer perceptrons neural network in the optimization of diclofenac sodium extended release tablets with Carbopol 71G.

The purpose of the study was to screen the effects of formulation factors on the in vitro release profile of diclofenac sodium from matrix tablets using design of experiment (DOE). Formulations of diclofenac sodium tablets, with Carbopol 71G as matrix substance, were optimized by artificial neural network. According to Central Composite Design, 10 formulations of diclofenac sodium matrix tablets were prepared. As network inputs, concentration of Carbopol 71G and the Kollidon K-25 were selected. In vitro dissolution time profiles at 5 different sampling times were chosen as responses. The independent variables and the release parameters were processed by multilayer perceptrons neural network (MLP). Results of drug release studies indicate that drug release rates vary between different formulations, with a range of 1 h to more than 8 h to complete dissolution. For two tested formulations there was no difference between experimental and MLP predicted in vitro profiles. The MLP model was optimized. The root mean square value for the trained network was 0.07%, which indicated that the optimal MLP model was reached. The optimal tablet formulation predicted by MLP was with 23% of Carbopol 71G and 0.8% of Kollidon K-25. Calculated difference factor (f(1) 7.37) and similarity factor (f(2) 70.79) indicate that there is no difference between predicted and experimentally observed drug release profiles for the optimal formulation. The satisfactory prediction of drug release for optimal formulation by the MLP in this study has shown the applicability of this optimization method in modeling extended release tablet formulation.

An investigation into effects of in vitro test condition on the release properties of theophylline from HPMC matrices using factorial design.

The purpose of this study was to investigate the effect of various in vitro test conditions, on the release properties of theophylline (TP) from aminophylline (AP) matrices based on different hydroxypropylmethylcellulose (HPMC) ratio and viscosity grades. The general full factorial experimental design 3 x 3 x 3 was used, based on three independent variables: applied in vitro test (X1), HPMC/drug ratio (X2) and polymer viscosity grade (X3). The drug release percent at 2h (Y(2h)), 4h (Y(4h)) and 8 h (Y(8h)) and time for 50% of TP release from matrices (Y(T50%)) were response variables. Three in vitro tests were used: test 1 and test 4 (theophylline extended-release capsules, USP 30) and half-change method. According to factorial design analyses, in vitro test was the most significant factor influencing mechanism and amount of drug release. For half change method erosion was the predominant mechanism indicating case - II transport, while for test 1 the release mechanism were followed by both diffusion and erosion. The lowest release exponent n values, obtained from Ritger-Pepass equation, for test 4 indicate diffusion process inclining from Fickian diffusion to anomalous transport. Therefore, it is in the stage of development, useful to consider the influence of various in vitro test conditions on the formulation, in order to choose an optimal test for the purpose of future drug release examination.

Mathematical modeling of pH-surfactant-mediated solubilization of nimesulide.

AIM: The equilibrium-based mathematical model was used to describe the pH-surfactant-mediated solubilization of weakly acidic electrolyte, nimesulide, in buffer solutions. This model assumed that the total drug solubility could be expressed as a sum of the solubilities of four different species: unionized and ionized form in solution and their corresponding micellar forms. Sucrose-laurate, new synthetic surfactant, and polysorbate 80 were investigated for their benefits in the testing of poorly soluble acidic model drug. METHOD: Two sets of solubility data, determined at pH values 4.5 and 9.0 in media containing different surfactant concentrations, were used to calculate solubilization slopes and corresponding micellar equilibrium constants for the unionized (Kn) and ionized (K(i)) drug. These values were used to estimate drug solubilization in media considered to represent physiologically relevant conditions. RESULTS: Predicted solubility values were in good agreement with the experimental data, suggesting that the impact of pH and surfactant on nimesulide solubility could be well characterized by the equilibrium model described in this article. CONCLUSIONS: Obtained results indicated that the extent of solubilization was significantly dependent on the surfactant used.

Evaluation of diclofenac sodium release from matrix pellets compressed into MUPS tablets.

The purpose of the study was to screen the effects of formulation factors on the in vitro release profile of diclofenac sodium from matrix pellets compressed into multiple unit pellet system (MUPS) tablets using design of experiment (DOE). Extended release of diclofenac sodium was accomplished using Carbopol 71G as matrix substance. According to Fractional Factorial Design FFD 2(3-1) four formulations of diclofenac sodium MUPS matrix tablets were prepared. The process of direct pelletization and subsequently compression of the pellets into tablets was applied in order to investigate a different approach in formulation of matrix systems and to achieve a better control of the process factors over the principal response - the release of the drug. The investigated factors were X1-the percentage of polymer Carbopol 71G, X2-crushing strength of the tablet and X3-different batches of the diclofenac sodium. In vitro dissolution time profiles at 6 different sampling times were chosen as responses. Results of drug release studies indicated that drug release rates vary between different formulations, with a range of 1 to 8 h to complete dissolution. The most important impact on the drug release had factor X1-the percentage of polymer Carbopol 71G. The polymer percentage is suggested as release regulator for diclofenac sodium release from MUPS matrix tablets. All other investigated factors had no significant influence on the release profile of diclofenac sodium.

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.

The impact of primary packaging on the quality of parenteral products.

The unique approach in manufacturing of pharmaceutical dosage forms of active substances known to be unstable in aqueous solution is the introduction of lyophilization process. Nevertheless, these products must be reconstituted using the diluent from a separate container before application. The possible solution for this problem is the application of dual chamber vials comprising the freeze-dried product in a lower compartment of the vial and the solution for reconstitution in the upper chamber. The main issue in development of such product is the choice of contact packaging (rubber closures, glass vials and the container closure system as a whole). The most important parameter used for evaluation of the influence of contact material on product quality was the pH value. The results have shown that the type of vials (moulded or tubular glass) has no impact on pH shift of the solution for reconstitution (tested solution-TS), while significant differences in pH value of the TS were observed depending on the rubber closures formulation used (with some formulations, the pH shift during the test was 6.5-9.14). Benzyl alcohol assay during the tests remained unchanged. Integrity tests of the container closure system (CCS) have demonstrated the adequacy of the selected packaging system. The quality of the CCS of choice was confirmed in the course of stability studies, only parameters directly influenced by CCS being presented in this work: loss on drying and pH value. On the basis of these results, no changes in loss on drying were connected to CCS, and the pH value of the reconstituted solution remains unchanged in samples tested both ex-tempore and after in-use period of 48 h.

An investigation into the usefulness of generalized regression neural network analysis in the development of level A in vitro-in vivo correlation.

Quantitative correlations between in vivo and in vitro data (IVIVC) reduce the number of human in vivo studies, thus decreasing the overall time and expenses necessary for the development of optimal drug product formulation. Although linear regression analysis represents the simplest relationship, it is recognized that IVIVC should not be limited to linear relationship. With regards to the implementation of non-linear IVIVC models and the ability of artificial neural network (ANN) computing to cope with non-linear relationships, the usefulness of ANN analysis in the development of IVIVC merits further evaluation. The present paper is an attempt to develop an IVIVC for model sustained release paracetamol matrix tablet formulations employing various correlation approaches based on linear and non-linear modeling of in vitro and in vivo data. Currently accepted compendial methodology was compared with the alternative approaches, involving general mixed effects model and generalized regression neural network (GRNN) analysis, in order to evaluate their usefulness for predicting the in vivo behavior of drug products. Although based on analogous approaches, data generated by GRNN were closer to those observed in vivo, leading to the higher level of IVIVC than obtained by convolution. It can be assumed that GRNN analysis was able to generalize complex relations between the output and input parameters and could account for the differences in drug release kinetics observed under various conditions in vitro, thus offering potential as a reliable and robust estimate of drug products in vivo behavior.

Generalized regression neural networks in prediction of drug stability.

This study had two aims. Firstly, we wanted to model the effects of the percentage of Eudragit RS PO and compression pressure as the most important process and formulation variables on the time course of drug release from extended-release matrix aspirin tablets. Secondly, we investigated the possibility of predicting drug stability and shelf-life using an artificial neural network (ANN). Ten types of matrix aspirin tablets were prepared as model formulations and were stored in stability chambers at 60 degrees C, 50 degrees C, 40 degrees C and 30 degrees C and controlled humidity. Samples were removed at predefined time points and analysed for acetylsalicylic acid (ASA) and salicylic acid (SA) content using stability-indicating HPLC. The decrease in aspirin content followed apparent zero-order kinetics. The amount of Eudragit RS PO and compression pressure were selected as causal factors. The apparent zero-order rate constants for each temperature were chosen as output variables for the ANN. A set of output parameters and causal factors were used as training data for the generalized regression neural network (GRNN). For two additional test formulations, Arrhenius plots were constructed from the experimentally observed and GRNN-predicted results. The slopes of experimentally observed and predicted Arrhenius plots were tested for significance using Student's t-test. For test formulations, the shelf life (t(95%)) was then calculated from experimentally observed values (t(95%) 82.90 weeks), as well as from GRNN-predicted values (t(95%) 81.88 weeks). These results demonstrate that GRNN networks can be used to predict ASA content and shelf life without stability testing for formulations in which the amount of polymer and tablet hardness are within the investigated range.

Modeling in the quality by design environment: Regulatory requirements and recommendations for design space and control strategy appointment.

Mathematical models can be used as an integral part of the quality by design (QbD) concept throughout the product lifecycle for variety of purposes, including appointment of the design space and control strategy, continual improvement and risk assessment. Examples of different mathematical modeling techniques (mechanistic, empirical and hybrid) in the pharmaceutical development and process monitoring or control are provided in the presented review. In the QbD context, mathematical models are predominantly used to support design space and/or control strategies. Considering their impact to the final product quality, models can be divided into the following categories: high, medium and low impact models. Although there are regulatory guidelines on the topic of modeling applications, review of QbD-based submission containing modeling elements revealed concerns regarding the scale-dependency of design spaces and verification of models predictions at commercial scale of manufacturing, especially regarding real-time release (RTR) models. Authors provide critical overview on the good modeling practices and introduce concepts of multiple-unit, adaptive and dynamic design space, multivariate specifications and methods for process uncertainty analysis. RTR specification with mathematical model and different approaches to multivariate statistical process control supporting process analytical technologies are also presented.

Biopharmaceutical characterization of sustained release matrix tablets based on novel carbomer polymers: formulation and in vivo investigation.

With the increased interest in modified release dosage forms and drug delivery systems, there is an increasing concern for biopharmaceutical characterization of the formulation in the early stages of drug product development. The main objectives of biopharmaceutical characterization are the in vitro and in vivo evaluation of the selected formulations in order to identify the factors influencing drug release; define the in vitro test methodology that would be predictive of drug products in vivo behavior and develop quantitative in vitro - in vivo correlation. The purpose of this study was to assess the potential of novel carbomer polymers, Carbopol 971P and Carbopol 71G, as a sustained release agents in matrix tablets containing high dosage drug substance. Although chemically identical, the two polymers exhibited substantially different drug release properties in vitro. Hypothetical in vivo drug release profiles were calculated by numerical deconvolution from cumulative urinary excretion data observed in vivo. The obtained results indicated that sound and reliable in vivo drug release profiles could be obtained from urinary excretion data and also, emphasized the need for in vitro testing under a range of experimental conditions in order to develop the biorelevant drug release methodology.

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

In this study binary carbamazepine-hydroxypropyl-ß-cyclodextrin, as well as ternary carbamazepine-hydroxypropyl-ß-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-ß-cyclodextrin for carbamazepine. Evaluation of carbamazepine-hydroxypropyl-ß-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-ß-cyclodextrin and hydrophilic polymers, both binary carbamazepine-hydroxypropyl-ß-cyclodextrin and ternary carbamazepine-hydroxypropyl-ß-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-ß-cyclodextrin and ternary carbamazepine-hydroxypropyl-ß-cyclodextrin-Soluplus® systems exhibited the fastest carbamazepine release, wherein the entire amount of carbamazepine was released during first 5 min.

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.

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 tablets 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.

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

OBJECTIVES: 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. METHODS: Prepared solid dispersions were characterized using differential scanning calorimetry, attenuated total reflectance infrared spectroscopy and hot stage microscopy, as well as by determination of the dissolution rate of CBZ from the hot-melt extrudates. KEY FINDINGS: Solid dispersions of CBZ can be successfully prepared using the novel copolymer Soluplus. Inclusion of Poloxamer 407 as a plasticizer facilitated the processing and decreased the hardness of hot-melt extrudates. Regardless of their composition, all hot-melt extrudates displayed an improvement in the release rate compared to the pure CBZ, with formulations having the ratio of CBZ : Poloxamer 407 = 1 : 1 showing the highest increase in CBZ release rate. CONCLUSIONS: Interactions between the mixture components (CBZ and polymers), or quadratic effects of the components, play a significant role in overall influence on the CBZ release rate.