Powder bed fusion-laser beam (PBF-LB) three-dimensional (3D) printing: Influence of laser hatching distance on the properties of zolpidem tartrate tablets.

Laser sintering, known as powder bed fusion-laser beam (PBF-LB), offers promising potential for the fabrication of patient-specific drugs. The aim of this study was to provide an insight into the PBF-LB process with regard to the process parameters, in particular the laser hatching distance, and its influence on the properties of zolpidem tartrate (ZT) tablets. PHARMACOAT® 603 was used as the polymer, while Candurin® Gold Sheen and AEROSIL® 200 were added to facilitate 3D printing. The particle size distribution of the powder blend showed that the layer height should be set to 100 µm, while the laser hatching distance was varied in five different steps (50, 100, 150, 200 and 250 µm), keeping the temperature and laser scanning speed constant. Increasing the laser hatching distance and decreasing the laser energy input led to a decrease in the colour intensity, mass, density and hardness of the ZT tablets, while the disintegration and dissolution rate were faster due to the more fragile bonds between the particles. The laser hatching distance also influenced the ZT dosage, indicating the importance of this process parameter in the production of presonalized drugs. The absence of drug-polymer interactions and the amorphization of the ZT were confirmed.

Numerical Modeling of Particle Dynamics Inside a Dry Powder Inhaler.

The development of novel dry powders for dry powder inhalers (DPIs) requires the in vitro assessment of DPI aerodynamic performance. As a potential complementary method, in silico numerical simulations can provide additional information about the mechanisms that guide the particles and their behavior inside DPIs. The aim of this study was to apply computational fluid dynamics (CFDs) coupled with a discrete phase model (DPM) to describe the forces and particle trajectories inside the RS01® as a model DPI device. The methodology included standard fluid flow equations but also additional equations for the particle sticking mechanism, as well as particle behavior after contacting the DPI wall surface, including the particle detachment process. The results show that the coefficient of restitution between the particle and the impact surface does not have a high impact on the results, meaning that all tested combinations gave similar output efficiencies and particle behaviors. No sliding or rolling mechanisms were observed for the particle detachment process, meaning that simple bouncing off or deposition particle behavior is present inside DPIs. The developed methodology can serve as a basis for the additional understanding of the particles' behavior inside DPIs, which is not possible using only in vitro experiments; this implies the possibility of increasing the efficiency of DPIs.

Processability evaluation of multiparticulate units prepared by selective laser sintering using the SeDeM Expert System approach.

3D printing in dosage forms fabrication is in the focus of researchers, however, the attempts in multiparticulate units (MPUs) preparation are scarce. The aim of this study was to fabricate different size MPUs by selective laser sintering (SLS), using different polymers, and investigate their processability based on the SeDeM Expert System approach. MPUs (1- or 2-mm size) were prepared with model drug (ibuprofen or caffeine), polymer (poly(ethylene)oxide (PEO), ethyl cellulose (EC) or methacrylic acid-ethyl acrylate copolymer (MA-EA)) and printing aid. Comprehensive sample characterization was performed and experimentally obtained parameters were mathematically transformed and evaluated using the SeDeM Expert System framework. The obtained samples exhibited irregular shape, despite the spherical printing object design. Polymer incorporated notably affected MPUs properties. The obtained samples exhibited low bulk density, good flowability-, as well as stability-related parameters, which indicated their suitability for filling into capsules or sachets. Low density values implied that compressibility enhancing excipients may be required for MPUs incorporation in tablets. Samples containing EC and MA-EA were found suitable for compression, due to high compacts tensile strength. The obtained results indicate that SeDeM Expert System may extended from powder compressibility evaluation tool to framework facilitating powders/multiparticulate units processing.

Formulation and characterization of immediate-release oral dosage forms with zolpidem tartrate fabricated by digital light processing (DLP) 3D printing technique.

The introduction of three-dimensional (3D) printing in the pharmaceutical field has made great strides towards innovations in the way drugs are designed and manufactured. In this study, digital light processing (DLP) technique was used to fabricate oral dosage forms of different shapes with zolpidem tartrate (ZT), incorporated within its therapeutic range. Formulation factors, such as poly(ethylene glycol) diacrylate (PEGDA) and poly(ethylene glycol) 400 (PEG 400) ratio, as well as water content, were varied in combination with the surface area/volume (SA/V) ratio to achieve immediate drug release. Hypromellose (HPMC) was used as a stabilizing agent of photoreactive suspensions in an attempt to prevent drug sedimentation and subsequent variations in drug content uniformity. Oral dosage forms with doses in the range from 0.15 mg to 6.37 mg, showing very rapid and rapid drug dissolution, were successfully fabricated, confirming the potential of this technique in drug manufacturing with the ability to provide flexible dose adjustments and desirable release profiles by varying formulation factors and geometry of 3D models. DSC (differential scanning calorimetry), XRPD (X-ray powder diffraction) and scanning electron microscopy (SEM) showed that ZT remained in a crystalline form within printed dosage forms and no interactions were found between ZT and polymers.

In-Depth Analysis of Physiologically Based Pharmacokinetic (PBPK) Modeling Utilization in Different Application Fields Using Text Mining Tools.

In the past decade, only a small number of papers have elaborated on the application of physiologically based pharmacokinetic (PBPK) modeling across different areas. In this review, an in-depth analysis of the distribution of PBPK modeling in relation to its application in various research topics and model validation was conducted by text mining tools. Orange 3.32.0, an open-source data mining program was used for text mining. PubMed was used for data retrieval, and the collected articles were analyzed by several widgets. A total of 2699 articles related to PBPK modeling met the predefined criteria. The number of publications per year has been rising steadily. Regarding the application areas, the results revealed that 26% of the publications described the use of PBPK modeling in early drug development, risk assessment and toxicity assessment, followed by absorption/formulation modeling (25%), prediction of drug-disease interactions (20%), drug-drug interactions (DDIs) (17%) and pediatric drug development (12%). Furthermore, the analysis showed that only 12% of the publications mentioned model validation, of which 51% referred to literature-based validation and 26% to experimentally validated models. The obtained results present a valuable review of the state-of-the-art regarding PBPK modeling applications in drug discovery and development and related fields.

Development of Lipid-Based Gastroretentive Delivery System for Gentian Extract by Double Emulsion-Melt Dispersion Technique.

Gentian (Gentiana lutea L., Gentianaceae) root extract (GRE) is used for the treatment of gastrointestinal disorders. However, its bioactive potential is limited in conventional forms due to the low bioavailability and short elimination half-life of the dominant bioactive compound, gentiopicroside. The aim of study was to encapsulate GRE in the lipid-based gastroretentive delivery system that could provide high yield and encapsulation efficiency, as well as the biphasic release of gentiopicroside from the tablets obtained by direct compression. Solid lipid microparticles (SLM) loaded with GRE were prepared by freeze-drying double (W/O/W) emulsions, which were obtained by a multiple emulsion-melt dispersion technique, with GRE as the inner water phase, Gelucire® 39/01 or 43/01, as lipid components, with or without the addition of porous silica (Sylysia® 350) in the outer water phase. Formulated SLM powders were examined by SEM and mercury intrusion porosimetry, as well as by determination of yield, encapsulation efficiency, and flow properties. Furthermore, in vitro dissolution of gentiopicroside, the size of the dispersed systems, mechanical properties, and mucoadhesion of tablets obtained by direct compression were investigated. The results have revealed that SLM with the macroporous structure were formulated, and, consequently, the powders floated immediately in the acidic medium. Formulation with porous silica (Sylysia® 350) and Gelucire® 43/01 as a solid lipid was characterized with the high yield end encapsulation efficiency. Furthermore, the mucoadhesive properties of tablets obtained by direct compression of that formulation, as well as the biphasic release of gentiopicroside, presence of nanoassociates in dissolution medium, and optimal mechanical properties indicated that a promising lipid-based gastroretentive system for GRE was developed.

3D Printed Buccal Films for Prolonged-Release of Propranolol Hydrochloride: Development, Characterization and Bioavailability Prediction.

Gelatin-polyvinylpyrrolidone (PVP) and gelatin-poly(vinyl alcohol) (PVA) mucoadhesive buccal films loaded with propranolol hydrochloride (PRH) were prepared by semi-solid extrusion 3D printing. The aim of this study was to evaluate the effects of the synthetic polymers PVP and PVA on thermal and mechanical properties and drug release profiles of gelatin-based films. The Fourier-transform infrared spectroscopy showed that hydrogen bonding between gelatin and PVP formed during printing. In the other blend, neither the esterification of PVA nor gelatin occurred. Differential scanning calorimetry revealed the presence of partial helical structures. In line with these results, the mechanical properties and drug release profiles were different for each blend. Formulation with gelatin-PVP and PRH showed higher tensile strength, hardness, and adhesive strength but slower drug release than formulation with gelatin-PVA and PRH. The in silico population simulations indicated increased drug bioavailability and decreased inter-individual variations in the resulting pharmacokinetic profiles compared to immediate-release tablets. Moreover, the simulation results suggested that reduced PRH daily dosing can be achieved with prolonged-release buccal films, which improves patient compliance.

Improving Tableting Performance of Lactose Monohydrate by Fluid-Bed Melt Granulation Co-Processing.

Co-processing is commonly used approach to improve functional characteristics of pharmaceutical excipients to become suitable for tablet production by direct compression. This study aimed to improve tableting characteristics of lactose monohydrate (LMH) by co-processing by fluid-bed melt granulation with addition of hydrophilic (PEG 4000 and poloxamer 188) and lipophilic (glyceryl palmitostearate) meltable binders. In addition to binding purpose, hydrophilic and lipophilic excipients were added to achieve self-lubricating properties of mixture. Co-processed mixtures exhibit superior flow properties compared to pure LMH and comparable or better flowability relative to commercial excipient Ludipress®. Compaction of mixtures co-processed with 20% PEG 4000 and 20% poloxamer 188 resulted in tablets with acceptable tensile strength (>2 MPa) and good lubricating properties (ejection and detachment stress values below 5 MPa) in a wide range of compression pressures. While the best lubricating properties were observed when glyceryl palmitostearate was used as meltable binder, obtained tablets failed to fulfil required mechanical characteristics. Although addition of meltable binder improves interparticle bonding, disintegration time was not prolonged compared to commercial excipient Ludipress®. Co-processed mixtures containing 20% of either PEG 4000 or poloxamer 188 showed superior tabletability and lubricant properties relative to LMH and Ludipress® and can be good candidates for tablet production by direct compression.

The evaluation of the effect of different superdisintegrants on the drug release from FDM 3D printed tablets through different applied strategies: In vitro-in silico assessment.

Paracetamol-loaded tablets were printed by fused deposition modelling technique, using polyvinyl alcohol as a backbone polymer and Affinisol™ HPMC as a plasticizer in all formulations. Four different strategies were applied in order to accelerate the drug release from the tablets. First, different release enhancers were added: sodium starch glycolate, croscarmellose sodium, Kollidon CL and mannitol. Kollidon CL and mannitol showed the greatest influence on the drug dissolution rate. The second strategy included lowering the infill density, which did not make any significant changes in dissolution profiles, according to the calculated similarity factor. Then the best two release enhancers from the first strategy were combined (Kollidon CL and mannitol) and this proved to be the most effective in the drug release acceleration. The fourth strategy, increasing the percentage of the release enhancers in formulation, revealed the importance of their concentration limits. In summary, the drug release accelerated from 58% released after 5 h to reaching the plateau within 2 h. In silico physiologically-based biopharmaceutics modelling showed that formulations with mannitol and Kollidon CL, especially the formulation containing a combination of these release enhancers, can provide relatively fast drug release and extent of drug absorption that complies with an immediate release tablet.

Tailoring amlodipine release from 3D printed tablets: Influence of infill patterns and wall thickness.

The aim of this study was to investigate the impact of infill patterns on the drug release of 3D-printed tablets and the possibility of tailoring drug release through the use of excipients. Furthermore, the influence of wall thickness was evaluated. Amlodipine was used as a model drug, polyvinyl alcohol (PVA) as a polymer and excipients including sodium starch glycolate (SSG) and hydroxypropyl methyl cellulose (HPMC) HME 4 M were used. Four different formulations were prepared. Firstly, the substances were mixed and then extruded by hot melt extrusion to form filaments. The obtained filaments were used to print amlodipine tablets by fused deposition modeling (FDM) 3D-printing technique. Each formulation was printed in four different infill patterns: zigzag, cubic, tri-hexagon and concentric, while infill density remained constant (20%). The mechanical properties of the obtained filaments were also evaluated using three-point bend test. Amlodipine tablets were printed with varying wall thickness (1 mm, 2 mm and 3 mm) and varying infill patterns. With regard to the infill patterns, higher drug release was achieved with zigzag infill pattern. The simultaneous effect of excipients and infill patterns on amlodipine release has been described and modeled through self - organizing maps (SOMs), which visualize the effect of these variables. Self-organizing maps confirmed the fastest drug release when the zigzag pattern and SSG were used, but also showed that the presence of HPMC HME 4 M was not decisive for drug release rate. As for the wall thickness, higher drug release was achieved with decreasing wall thickness. The results indicated that proper selection of excipients and/or adjusting the infill pattern and wall thickness are ways of tailoring drug release in FDM 3D printing. This study draws the attention to the importance of adjusting the settings of the printer and the usage of excipients to produce release-tailored medications.

Comparative Assessment of In Vitro and In Silico Methods for Aerodynamic Characterization of Powders for Inhalation.

In vitro assessment of dry powders for inhalation (DPIs) aerodynamic performance is an inevitable test in DPI development. However, contemporary trends in drug development also implicate the use of in silico methods, e.g., computational fluid dynamics (CFD) coupled with discrete phase modeling (DPM). The aim of this study was to compare the designed CFD-DPM outcomes with the results of three in vitro methods for aerodynamic assessment of solid lipid microparticle DPIs. The model was able to simulate particle-to-wall sticking and estimate fractions of particles that stick or bounce off the inhaler's wall; however, we observed notable differences between the in silico and in vitro results. The predicted emitted fractions (EFs) were comparable to the in vitro determined EFs, whereas the predicted fine particle fractions (FPFs) were generally lower than the corresponding in vitro values. In addition, CFD-DPM predicted higher mass median aerodynamic diameter (MMAD) in comparison to the in vitro values. The outcomes of different in vitro methods also diverged, implying that these methods are not interchangeable. Overall, our results support the utility of CFD-DPM in the DPI development, but highlight the need for additional improvements in these models to capture all the key processes influencing aerodynamic performance of specific DPIs.

Understanding the Effect of Energy Density and Formulation Factors on the Printability and Characteristics of SLS Irbesartan Tablets-Application of the Decision Tree Model.

Selective laser sintering (SLS) is a rapid prototyping technique for the production of three-dimensional objects through selectively sintering powder-based layer materials. The aim of the study was to investigate the effect of energy density (ED) and formulation factors on the printability and characteristics of SLS irbesartan tablets. The correlation between formulation factors, ED, and printability was obtained using a decision tree model with an accuracy of 80%. FT-IR results revealed that there was no interaction between irbesartan and the applied excipients. DSC results indicated that irbesartan was present in an amorphous form in printed tablets. ED had a significant influence on tablets' physical, mechanical, and morphological characteristics. Adding lactose monohydrate enabled faster drug release while reducing the possibility for printing with different laser speeds. However, formulations with crospovidone were printable with a wider range of laser speeds. The adjustment of formulation and process parameters enabled the production of SLS tablets with hydroxypropyl methylcellulose with complete release in less than 30 min. The results suggest that a decision tree could be a useful tool for predicting the printability of pharmaceutical formulations. Tailoring the characteristics of SLS irbesartan tablets by ED is possible; however, it needs to be governed by the composition of the whole formulation.

Potential application of low molecular weight excipients for amorphization and dissolution enhancement of carvedilol.

In this study, four low molecular weight (LMW) excipients, tryptophan (TRY), phenylalanine (PHE), lysine (LYS) and saccharin (SAC) were evaluated as co-formers to generate co-amorphous systems (CAMS) by ball milling with carvedilol (CRV). Mixtures of CRV and LMW excipient in 1:0.5, 1:1 and 1:2 drug:excipient molar ratios were ball milled and analysed by powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC), Fourier transform (FT-IR) infrared spectroscopy and dissolution testing. CAMS were formed by milling of a mixture of CRV with TRY in 1:2 M ratio and SAC in 1:1 M ratio, while amorphization of only CRV was achieved in other mixtures with SAC. In other samples containing TRY and PHE, milling resulted in partial amorphization, while LYS was the least suitable excipient for the amorphization of CRV. Unexpectedly, the highest supersaturation of CRV was achieved from samples containing CRV and LYS in 1:1 and 1:2 M ratios, despite the absence of a significant reduction in CRV crystallinity upon milling of these samples. Increase of hydrophobic surface area caused by milling of samples with TRY and PHE and agglomeration during dissolution testing of samples containing SAC are likely causes of poor dissolution performance of mixtures containing fully or partially amorphous CRV.

Prediction of Drug Stability Using Deep Learning Approach: Case Study of Esomeprazole 40 mg Freeze-Dried Powder for Solution.

A critical step in the production of Esomeprazole powder for solution is a period between the filling process and lyophilization, where all vials, partially closed, are completely exposed to environmental influences. Excessive instability reflects in pH value variations caused by oxygen's impact. In order to provide pH control, which consequently affects drug stability, Esomeprazole batches, produced in the same way, were kept in partially closed vials for 3 h at temperatures of 20 °C and -30 °C, after which they were lyophilized and stored for long-term stability for 36 months. The aim of the presented study was to apply a deep-learning algorithm for the prediction of the Esomeprazole stability profile and to determine the pH limit for the reconstituted solution of the final freeze-dried product that would assure a quality product profile over a storage period of 36 months. Multilayer perceptron (MLP) as a deep learning tool, with four layers, was used. The pH value of Esomeprazole solution and time of storage (months) were inputs for the network, while Esomeprazole assay and four main impurities were outputs of the network. In order to keep all related substances and Esomeprazole assay in accordance with specifications for the whole shelf life, the pH value for the reconstituted finish product should be set in the range of 10.4-10.6.

Application of Machine-Learning Algorithms for Better Understanding of Tableting Properties of Lactose Co-Processed with Lipid Excipients.

Co-processing (CP) provides superior properties to excipients and has become a reliable option to facilitated formulation and manufacturing of variety of solid dosage forms. Development of directly compressible formulations with high doses of poorly flowing/compressible active pharmaceutical ingredients, such as paracetamol, remains a great challenge for the pharmaceutical industry due to the lack of understanding of the interplay between the formulation properties, process of compaction, and stages of tablets' detachment and ejection. The aim of this study was to analyze the influence of the compression load, excipients' co-processing and the addition of paracetamol on the obtained tablets' tensile strength and the specific parameters of the tableting process, such as (net) compression work, elastic recovery, detachment, and ejection work, as well as the ejection force. Two types of neural networks were used to analyze the data: classification (Kohonen network) and regression networks (multilayer perceptron and radial basis function), to build prediction models and identify the variables that are predominantly affecting the tableting process and the obtained tablets' tensile strength. It has been demonstrated that sophisticated data-mining methods are necessary to interpret complex phenomena regarding the effect of co-processing on tableting properties of directly compressible excipients.

An Integrative in silico Drug Repurposing Approach for Identification of Potential Inhibitors of SARS-CoV-2 Main Protease.

Considering the urgent need for novel therapeutics in ongoing COVID-19 pandemic, drug repurposing approach might offer rapid solutions comparing to de novo drug design. In this study, we designed an integrative in silico drug repurposing approach for rapid selection of potential candidates against SARS-CoV-2 Main Protease (Mpro ). To screen FDA-approved drugs, we implemented structure-based molecular modelling techniques, physiologically-based pharmacokinetic (PBPK) modelling of drugs disposition and data mining analysis of drug-gene-COVID-19 association. Through presented approach, we selected the most promising FDA approved drugs for further COVID-19 drug development campaigns and analysed them in context of available experimental data. To the best of our knowledge, this is unique in silico study which integrates structure-based molecular modeling of Mpro inhibitors with predictions of their tissue disposition, drug-gene-COVID-19 associations and prediction of pleiotropic effects of selected candidates.

Predicting drug release from diazepam FDM printed tablets using deep learning approach: Influence of process parameters and tablet surface/volume ratio.

The aim of this study was to apply artificial neural networks as deep learning tools in establishing a model for understanding and prediction of diazepam release from fused deposition modeling (FDM) printed tablets. Diazepam printed tablets of various shapes were created by a computer-aided design (CAD) program and prepared by fused deposition modeling using previously prepared polyvinyl alcohol/diazepam filaments via hot-melt extrusion. The surface to volume ratio (SA/V) for each shape was calculated. Printing parameters were varied including infill density (20%, 70% and 100%) and infill pattern (line and zigzag). Influence of tablet SA/V ratio and printing parameters (infill density and infill pattern) on the release of diazepam from printed tablets were modeled using self-organizing maps (SOM) and multi-layer perceptron (MLP). SOM as an unsupervised neural network was used for visualizing interrelation among the data, whereas MLP was used for the prediction of drug release properties. MLP had three layers (with structure 2-3-5) and was trained using back propagation algorithm. Input parameters for the modeling were: infill density and SA/V ratio; while output parameters were percent of drug release in five time points. The data set for network training was divided into training, validation and test sets. The dissolution rate increased with higher SA/V ratio, lower infill density (less than 50%) and zigzag infill pattern. The established ANN model was tested; calculated f 2 factors for two tested formulations (70.24 and 77.44) showed similarity between experimentally observed and predicted drug release profiles. Trained MLP network was able to predict drug release behavior as a function of infill density and SA/Vol ratio, as established design space for formulated 3D printed diazepam tablets.

Mucoadhesive Gelatin Buccal Films with Propranolol Hydrochloride: Evaluation of Mechanical, Mucoadhesive, and Biopharmaceutical Properties.

This study processes and characterizes propranolol hydrochloride/gelatin mucoadhesive buccal films. Two types of gelatin are used: Gelatin from porcine skin, type A (GA), and gelatin from bovine skin (GB). The influence of gelatin type on mechanical, mucoadhesive, and biopharmaceutical characteristics of buccal films is evaluated. Fourier-Transfer infrared spectroscopy (FTIR) and differential scanning calorimetry (DSC) analysis show that GA with propranolol hydrochloride (PRH) in the film (GAP) formed a physical mixture, whereas GB with PRH (GBP) form a compound-complex. Results of mechanical testing (tensile test, hardness) revealed that GAP films exhibit higher elastic modulus, tensile strength, and hardness. A mucoahesion test shows that GBP has higher adhesion strength, while GAP shows higher work of adhesion. Both in vitro release study and in silico simulation indicated that processed films can provide effective drug transport through the buccal mucosa. In silico simulation shows improved bioavailability from buccal films, in comparison to the immediate-release tablets-indicating that the therapeutic drug dose can be markedly reduced.

Enhanced antimicrobial activity and physicochemical stability of rapid pyro-fabricated silver-kaolinite nanocomposite.

The present research aims to enhance the antimicrobial activity of kaolinite surfaces by a one-step cost-effective and energy-efficient dry thermal reaction, producing an antibacterial and antifungal silver-kaolinite (Ag-Kao) nanocomposite agent. Pharmaceutical grade kaolin powder samples, with variable kaolinite structural order-disorder degree, were homogeneously mixed with silver nitrate in a proportion 1:4 AgNO3:kaolin (w/w) and sintered at 400 °C for 30 min. The composition, microstructure, microtexture and surface characteristics of the pyro-fabricated nanocomposites were characterized by XRD/XRF diffractometry, differential scanning calorimetry DSC, FT-IR spectroscopy, TEM/EDX, zeta potential (mV) measured within the 2-12 pH range, and BET method. Physicochemical stability was evaluated by silver dissociation testing under close-neutral and acidic conditions with Ag content assay using ICP-OES. The resulting Ag-Kao nanocomposites exhibited bulk silver contents ranging from 9.29% to 13.32% with high physicochemical stability in both neutral and acidic mediums (Ag dissociation rate <0.5% in 5 days). Ag nanocrystals exhibited particle sizes ranging from 5 to 30 nm, which were embedded and reinforced within the kaolinite matrix. The sizes of the Ag nanocrystals and their distribution patterns on the edges and faces of kaolinite platelets were controlled by the structural order-disorder degree. Highly ordered kaolinites (Hinckley Index, HI > 1) produced platelet edge-clustered silver nanocrystals due to the abundance of the dangling hydroxyls on platelet edges, while the highly disordered kaolinite (HI < 1) provided homogeneous platelet basal-doped silver nanocrystals due to the presence of some residual charges by exposed basal hydroxyl groups with interplatelet silver diffusivity. At pH 2, the magnitude of the positive surface charge was influenced by the silver nanocrystal size. Nanocomposites with the smallest silver nanocrystals (10-5 nm) exhibited the highest positive zeta potential (+15.2 mV to +17.0 mV), while those with larger silver nanocrystals (up to 30 nm) indicated lower positive zeta potential values (+9.5 mV to +3.6 mV). Under the same testing conditions using the Mueller-Hinton broth microdilution method, the raw kaolin samples did not show any significant antimicrobial activity, while all the pyro-fabricated Ag-Kao nanocomposite samples showed potent antibacterial and antifungal activity at low doses (MIC range 0.1-0.0125 mg/mL). Therefore, modulation of the effective electrostatic surface charge of the kaolinite platelets, via thermal doping of silver within their basal planes and edges, was found to be strongly dependent on the pH as well as the size and microtexture of the silver nanocrystals (mainly controlled by the order-disorder degree HI). The resulting modified nanostructure, with physicochemical stability and the efficient surface properties of the designed pyro-fabricated nanocomposite, led to an enhanced synergistic biophysical antimicrobial activity.

Development of solid lipid microparticles by melt-emulsification/spray-drying processes as carriers for pulmonary drug delivery.

The aim of this study was to optimize the parameters of the complex melt-emulsification process coupled with the spray-drying, in order to maintain the balance between solid lipid microparticles (SLMs) powders aerodynamic performance and salbutamol sulfate release rate. Quality target product profile was identified and risk management and principal component analysis were used to guide formulation development. Obtained dry powders for inhalation (DPIs) were evaluated in terms of SLMs size distribution, morphology, true density, drug content, solid state characterization studies, in vitro aerosol performance and in vitro drug release. SLMs micrographs indicated spherical, porous particles. Selected powders showed satisfactory aerosol performance with a mean mass aerodynamic diameter of around 3 µm and acceptable fine particle fraction (FPF). Addition of trehalose positively affected SLMs aerodynamic properties. The results of in vitro dissolution testing indicated that salbutamol sulfate release from the tested SLMs formulations was modified, in comparison to the raw drug release. In conclusion, SLMs in a form of DPIs were successfully developed and numerous factors that affects SLMs properties were identified in this study. Further research is required for full understanding of each factor's influence on SLMs properties and optimization of DPIs with maximized FPFs.