Jelena Djuris

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.

Characterization and evaluation of solid self-microemulsifying drug delivery systems with porous carriers as systems for improved carbamazepine release

The purpose of this study was to investigate solid self-microemulsifying drug delivery system (SSMEDDS), as potential delivery system for poorly water soluble drug carbamazepine (CBZ). Self-microemulsifying drug delivery system (SMEDDS) was formulated using the surfactant polyoxyethylene 20 sorbitan monooleate [Polysorbate 80] (S), the cosurfactant PEG-40 hydrogenated castor oil [Cremophor(®) RH40] (C) and the oil caprylic/capric triglycerides [Mygliol(®) 812] (O). Four different adsorbents with high specific surface area were used: Neusilin(®) UFL2, Neusilin(®) FL2 (magnesium aluminometasilicate), Sylysia(®) 320 and Sylysia(®) 350 (porous silica). Microemulsion area at the surfactant to cosurfactant ratio (K(m)) 1:1 was evaluated and for further investigation SMEDDS with SC/O ratio 8:2 was selected. Solubilization capacity of selected SMEDDS for CBZ was 33.771±0.041 mg/ml. Rheological measurements of unloaded and CBZ-loaded SMEDDS at water content varied from 10 to 60% (w/w) were conducted. It has been found that CBZ has great influence on rheological behaviour of investigated system upon water dilution. Photon correlation spectroscopy has shown the ability of CBZ-loaded SMEDDS to produce microemulsion droplet size. SSMEDDS improved release rate of CBZ, but the type of adsorbent significantly affects release rate of CBZ. For SSMEDDS with different magnesium aluminometasilicate adsorbents, release rate of CBZ decreased with increasing specific surface area due to entrapment of liquid SMEDDS inside the pores and its gradual exposure to dissolution medium. With porous silica adsorbents no difference in release rate was found in comparison to physical mixtures. In physical mixtures at 12.5% (w/w) CBZ content, presence of amorphous CBZ led to high dissolution rate.

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.

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.

Application of D‐optimal experimental design method to optimize the formulation of O/W cosmetic emulsions

This study investigates the application of D‐optimal mixture experimental design in optimization of O/W cosmetic emulsions. Cetearyl glucoside was used as a natural, biodegradable non‐ionic emulsifier in the relatively low concentration (1%), and the mixture of co‐emulsifiers (stearic acid, cetyl alcohol, stearyl alcohol and glyceryl stearate) was used to stabilize the formulations.

Spray coating as a powerful technique in preparation of solid dispersions with enhanced desloratadine dissolution rate

Solid dispersion systems have been widely used to enhance dissolution rate and oral bioavailability of poorly water-soluble drugs. However, the formulation process development and scale-up present a number of difficulties which has greatly limited their commercial applications. In this study, solid dispersions (SDs) of desloratadine (DSL) with povidone (PVP) and crospovidone (cPVP) were prepared by spray coating technique. The process involved the spray application of 96% ethanol solution of DSL and PVP/cPVP, and subsequent deposition of the coprecipitates onto microcrystalline cellulose pellets during drying by air flow in a mini spray coater. The results from the present study demonstrated that the spray coating process is efficient in preparing SDs with enhanced drug dissolution rate and it is highly efficient in organic solvent removal. Both PVP and cPVP greatly improved drug dissolution rate by SDs, with PVP showing better solubilization capability. Very fast drug dissolution rate is achieved from SDs containing PVP regardless of differences in K grade. SD with smaller particles of cPVP have higher drug dissolution rate in comparison to the cPVP with larger particles. Results from physical state characterization indicate that DSL in SDs exist in the amorphous (high free-energy) state which is probably stabilized by PVP/cPVP. After 6-month accelerated stability study, DSL remains amorphous, while PVP and cPVP act as anti-plasticizing agents, offering efficient steric hindrance for nucleation and crystal growth.

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

Abstract 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.

Application of Quality by Design Concepts in the Development of Fluidized Bed Granulation and Tableting Processes

This study illustrates the application of experimental design and multivariate data analysis in defining design space for granulation and tableting processes. According to the quality by design concepts, critical quality attributes (CQAs) of granules and tablets, as well as critical parameters of granulation and tableting processes, were identified and evaluated. Acetaminophen was used as the model drug, and one of the study aims was to investigate the possibility of the development of immediate- or extended-release acetaminophen tablets. Granulation experiments were performed in the fluid bed processor using polyethylene oxide polymer as a binder in the direct granulation method. Tablets were compressed in the laboratory excenter tablet press. The first set of experiments was organized according to Plackett-Burman design, followed by the full factorial experimental design. Principal component analysis and partial least squares regression were applied as the multivariate analysis techniques. By using these different methods, CQAs and process parameters were identified and quantified. Furthermore, an in-line method was developed to monitor the temperature during the fluidized bed granulation process, to foresee possible defects in granules CQAs. Various control strategies that are based on the process understanding and assure desired quality attributes of the product are proposed.

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.