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Characterization of Spray Dried Particles Through Microstructural Imaging
Abstract
Spray drying is commonly used to produce amorphous solid dispersions (ASD) to improve the bioperformance of poorly water-soluble drugs. In this study, imaging techniques such as focused ion beam-scanning electron microscopy (FIB-SEM) and X-ray microcomputed tomography (XRCT) were used to study the microstructure of spray dried (SD) particles. Spray drying at higher outlet temperature (Tout) was found to produce more spherical hollow particles with smooth surface and thinner walls, while more raisin-like particles with thicker walls were generated at lower Tout. For the first time, an artificial intelligence–facilitated XRCT image analysis tool was developed to make quantitative analysis of thousands of particles individually possible. The particle size distribution through XRCT image analysis is generally in line with what is measured by laser diffraction. The image analysis reveals envelope density as a more sensitive physical attribute for process change than conventional bulk/tap density. Further, the tensile strength of SD particle compacts correlates with the particle wall thickness, and this is likely caused by the larger interparticle contact area generated by more deformation of particles with thinner walls. The knowledge gained here can help enable SD particle engineering and drug product with more robust process and optimized performance.
... Xi et al. successfully developed a method for measuring the particle size distribution of spray-dried particles using XRCT images [89]. This study used an AI-facilitated tool to quantitatively study thousands of individual particles. ...
... These image analysis results have demonstrated a high correlation with the measurement by laser diffraction. More importantly, this method can potentially facilitate the development of spray-dried particles with optimized performance [89]. ...
... Moreover, some applications of AI/ML in solid dosage development processes have yet to be investigated. For example, deep learning-based image analysis technology can extract a variety of properties of the formulations including particle size distribution [89]. It would be significant if the image analysis were incorporated with a process analytical technology (PAT) instrument for the in-silico measurement of some properties during the manufacturing process. ...
Artificial Intelligence (AI)-based formulation development is a promising approach for facilitating the drug product development process. AI is a versatile tool that contains multiple algorithms that can be applied in various circumstances. Solid dosage forms, represented by tablets, capsules, powder, granules, etc., are among the most widely used administration methods. During the product development process, multiple factors including critical material attributes (CMAs) and processing parameters can affect product properties, such as dissolution rates, physical and chemical stabilities, particle size distribution, and the aerosol performance of the dry powder. However, the conventional trial-and-error approach for product development is inefficient, laborious, and time-consuming. AI has been recently recognized as an emerging and cutting-edge tool for pharmaceutical formulation development which has gained much attention. This review provides the following insights: (1) a general introduction of AI in the pharmaceutical sciences and principal guidance from the regulatory agencies, (2) approaches to generating a database for solid dosage formulations, (3) insight on data preparation and processing, (4) a brief introduction to and comparisons of AI algorithms, and (5) information on applications and case studies of AI as applied to solid dosage forms. In addition, the powerful technique known as deep learning-based image analytics will be discussed along with its pharmaceutical applications. By applying emerging AI technology, scientists and researchers can better understand and predict the properties of drug formulations to facilitate more efficient drug product development processes.
... In addition to application of typical physical characterization tools, in this work we have applied X-Ray microcomputed tomography to obtain additional understanding of the drug product intermediates and tablets formed from ASDs made by different techniques. X-Ray micro-computed tomography (interchangeably termed MicroCT, XRCT or μCT), has recently been used for microstructural assessment of tablets (33,34), granules (35), and spray dried dispersions (36). Advances in non-invasive 3D imaging allows X-ray Microscopy (XRM) through AI-based image processing to quantitatively interrogate API or spray dried dispersion domains and morphology in powder blends and tablets (36)(37)(38). ...
... X-Ray micro-computed tomography (interchangeably termed MicroCT, XRCT or μCT), has recently been used for microstructural assessment of tablets (33,34), granules (35), and spray dried dispersions (36). Advances in non-invasive 3D imaging allows X-ray Microscopy (XRM) through AI-based image processing to quantitatively interrogate API or spray dried dispersion domains and morphology in powder blends and tablets (36)(37)(38). ...
... Shriveled particles are formed when the partial pressure of the solvent trapped in the particle is lower (53). Previous investigation using FIB-SEM and XRM has shown that for a model system (20% MK-A and 80% HPMC-AS), SDD particle morphologies can range from hollow spheres with thin walls, to raisin-like particles with thicker shell and reduced void spaces, to solid particles with no internal voids (36). The morphology was found to be sensitive to the process conditions, in particular the outlet temperature. ...
Purpose
The purpose of this work is to evaluate the interrelationship of microstructure, properties, and dissolution performance for amorphous solid dispersions (ASDs) prepared using different methods.
Methods
ASD of GDC-0810 (50% w/w) with HPMC-AS was prepared using methods of spray drying and co-precipitation via resonant acoustic mixing. Microstructure, particulate and bulk powder properties, and dissolution performance were characterized for GDC-0810 ASDs. In addition to application of typical physical characterization tools, we have applied X-Ray Microscopy (XRM) to assess the contribution of microstructure to the characteristics of ASDs and obtain additional quantification and understanding of the drug product intermediates and tablets.
Results
Both methods of spray drying and co-precipitation produced single-phase ASDs. Distinct differences in microstructure, particle size distribution, specific surface area, bulk and tapped density, were observed between GDC-0810 spray dried dispersion (SDD) and co-precipitated amorphous dispersion (cPAD) materials. The cPAD powders prepared by the resonant acoustic mixing process demonstrated superior compactibility compared to the SDD, while the compressibility of the ASDs were comparable. Both SDD powder and tablets showed higher in vitro dissolution than those of cPAD powders. XRM calculated total solid external surface area (SA) normalized by calculated total solid volume (SV) shows a strong correlation with micro dissolution data.
Conclusion
Strong interrelationship of microstructure, physical properties, and dissolution performance was observed for GDC-0810 ASDs. XRM image-based analysis is a powerful tool to assess the contribution of microstructure to the characteristics of ASDs and provide mechanistic understanding of the interrelationship.
... In addition to an improvement in non-invasive 3D imaging from the geometrical magnification limitations of conventional MicroCT, XRM provides exceptional resolution down to 0.5 μm and is versatile for imaging a range of both small samples as well as whole dosage units (40,41). AI-based image processing has allowed for quantitative interrogation specifically of API or spray dried dispersions domains in powder blends and tablets (42)(43)(44). ...
... The XRM methodology used in this study is expected to be applicable to other formulation compositions where the API exhibits sufficient density difference relative to the excipients. Generation of detailed external and internal particulate attribute information with XRM methods shown here and on other types drug product materials (43,65) is also illustrative of its potential utility in more routine applications. This work shows that significant understanding of the interplay among API, excipients, and pharmaceutical processing on particle physical characteristics can be generated through focused application of XRM and quantitative image analysis techniques using just a few relevant samples. ...
Assessment and understanding of changes in particle size of active pharmaceutical ingredients (API) and excipients as a function of solid dosage form processing is an important but under-investigated area that can impact drug product quality. In this study, X-ray microscopy (XRM) was investigated as a method for determining the in situ particle size distribution of API agglomerates and an excipient at different processing stages in tablet manufacturing. An artificial intelligence (AI)-facilitated XRM image analysis tool was applied for quantitative analysis of thousands of individual particles, both of the API and the major filler component of the formulation, microcrystalline cellulose (MCC). Domain size distributions for API and MCC were generated along with the calculation of the porosity of each respective component. The API domain size distributions correlated with laser diffraction measurements and sieve analysis of the API, formulation blend, and granulation. The XRM analysis demonstrated that attrition of the API agglomerates occurred secondary to the granulation stage. These results were corroborated by particle size distribution and sieve potency data which showed generation of an API fines fraction. Additionally, changes in the XRM-calculated size distribution of MCC particles in subsequent processing steps were rationalized based on the known plastic deformation mechanism of MCC. The XRM data indicated that size distribution of the primary MCC particles, which make up the larger functional MCC agglomerates, is conserved across the stages of processing. The results indicate that XRM can be successfully applied as a direct, non-invasive method to track API and excipient particle properties and microstructure for in-process control samples and in the final solid dosage form. The XRM and AI image analysis methodology provides a data-rich way to interrogate the impact of processing stresses on API and excipients for enhanced process understanding and utilization for Quality by Design (QbD).
... The 3D XRM images were subjected to an initial intensity normalization procedure using the sample container and the inter-sphere air as the calibration standards. Following the image intensity normalization, the images were segmented into either the microsphere phase or inter-sphere air phase using iterative supervised machine learning and deep learning methods [22][23][24]. In brief, a small crop of a 2D cross sections of the XRM scan from one sample was used to train a supervised machine learning model based on the Random Forest classification algorithm. ...
The intra-sphere and inter-sphere structural attributes of controlled release microsphere drug products can greatly impact their release profile and clinical performance. In developing a robust and efficient method to characterize the structure of microsphere drug products, this paper proposes X-ray microscopy (XRM) combined with artificial intelligence (AI)-based image analytics. Eight minocycline loaded poly(lactic-co-glycolic acid) (PLGA) microsphere batches were produced with controlled variations in manufacturing parameters, leading to differences in their underlying microstructures and their final release performances. A representative number of microspheres samples from each batch were imaged using high resolution, non-invasive XRM. Reconstructed images and AI-assisted segmentation were used to determine the size distribution, XRM signal intensity, and intensity variation of thousands of microspheres per sample. The signal intensity within the eight batches was nearly constant over the range of microsphere diameters, indicating high structural similarity of spheres within the same batch. Observed differences in the variation of signal intensity between different batches suggests inter-batch non-uniformity arising from differences in the underlying microstructures associated with different manufacturing parameters. These intensity variations were correlated with the structures observed from higher resolution focused ion beam scanning electron microscopy (FIB-SEM) and the in vitro release performance for the batches. The potential for this method for rapid at-line and offline product quality assessment, quality control, and quality assurance is discussed.
... These characteristics yield information about the nature of the respective sample and do not necessarily describe individual particles. Although this is part of recent investigations in spray dried, spherical particles and metal particles [10][11][12][13], non-spherical particles are seldom covered. Samples containing spherical individual particles allow for efficient application of artificial intelligence (AI) methods and post-processing algorithms. ...
The knowledge of product particle size distribution (PSD) in crystallization processes is of high interest for the pharmaceutical and fine chemical industries, as well as in research and development. Not only can the efficiency of crystallization/production processes and product quality be increased but also new equipment can be qualitatively characterized. A large variety of analytical methods for PSDs is available, most of which have underlying assumptions and corresponding errors affecting the measurement of the volume of individual particles. In this work we present a method for the determination of particle volumes in a bulk sample via micro-computed tomography and the application of artificial intelligence. The particle size of bulk samples of sucrose were measured with this method and compared to classical indirect measurement methods. Advantages of the workflow are presented.
... The images were segmented into solid material and air with an artificial intelligence-based image segmentation (AIBIS) algorithm (22). In brief, the collection of pixels from the imaging signal reflects a unique textural pattern for different phases. ...
Hollow SDD particles raise challenges with respect toappropriate and meaningful particle characterization. Whilstmeasurements of particle size and bulk density provide someinformation, the results can be confounded due to incorrectassumptions. Correspondingly, any correlation to powder/formulation properties may be erroneous or misleading.Quantitative knowledge about the size of the particle,the volume of solid contained within the particle, and themorphological habit is required to more adequately describethe range of morphological characteristics within an SDDsample and thereby a means to better understand theinfluence of the process conditions on the final particle andbulk powder properties.The work demonstrates an approach to utilizesubmicronCT measurements of particle and solid/void vol-umes for SDD particles to achieve a more appropriate meansto describe both the size and morphological habit of SDDparticles within a sample.The work also suggests a means to utilize the measuredsolid volume data to calculate the droplet size required tohold that volume of solid. This type of approach may enable afuture path to better model the link between droplet size andfinal particle size and thereby an understanding of theindividual droplet drying kinetics and particle formationmechanisms across an SDD sample as well as the parameterspace of SDD formulations.
... In this work, an artificial intelligence-based image segmentation algorithm (AIBIS) developed by DigiM was used to overcome the limitation of the conventional approach. The method has been discussed and validated extensively in a variety of pharmaceutical applications [27][28][29][30][31][32]. In brief, the AIBIS algorithm mimics the ability of the human eyes which can recognize a feature not only based on the greyscale value of pixels, but also its relationship with its surrounding pixels. ...
Imaging-based characterization of polymeric drug-eluting implants can be challenging due to the microstructural complexity and scale of dispersed drug domains and polymer matrix. The typical evaluation via real-time (and accelerated in vitro experiments not only can be very labor intensive since implants are designed to last for 3 months or longer, but also fails to elucidate the impact of the internal microstructure on the implant release rate. A novel characterization technique, combining multi-scale high resolution three-dimensional imaging, was developed for a mechanistic understanding of the impact of formulation and manufacturing process on the implant microstructure. Artificial intelligence-based image segmentation and imaging analytics convert “visualized” structural properties into numerical models, which can be used to calculate key parameters governing drug transport in the polymer matrix, such as effective permeability. Simulations of drug transport in structures constructed on the basis of image analytics can be used to predict the release rates for the drug-eluting implant without running lengthy experiments. Multi-scale imaging approach and image-based characterization generate a large amount of quantitative structural information that are difficult to obtain experimentally. The direct-imaging based analytics and simulation is a powerful tool and has potential to advance fundamental understanding of drug release mechanism and the development of robust drug-eluting implants.
... The sensitivity of quality attributes to drug formulation parameters (such as drug loading, polymer choice, and particle morphology) and under various processing conditions (such as process temperature and compaction force) can be thoroughly studied. [4][5] Numerical drug formulations can be constructed from the real image data, evaluating factors such as optimal drug loading and porosity. 6 The numerical model allows a pharmaceutical scientist to rapidly traverse multi-variable parameter space, and narrow down formulation parameters and optimal processing conditions. ...
Visible and subvisible particles are a quality attribute in sterile pharmaceutical samples. A common method for characterizing and quantifying pharmaceutical samples containing particulates is imaging many individual particles using high-throughput instrumentation and analyzing the populations data. The analysis includes conventional metrics such as the particle size distribution but can be more sophisticated by interpreting other visual/morphological features. To avoid the hurdles of building new image analysis models capable of extracting such relevant features from scratch, we propose using well-established pretrained deep learning image analysis models such as EfficientNet. We demonstrate that such models are useful as a prescreening tool for high-level characterization of biopharmaceutical particle image data. We show that although these models are originally trained for completely different tasks (such as the classification of daily objects in the ImageNet database), the visual feature vectors extracted by such models can be useful for studying different types of subvisible particles. This applicability is illustrated through multiple case studies: (i) particle risk assessment in prefilled syringe formulations containing different particle types such as silicone oil, (ii) method comparability with the example of accelerated forced degradation, and (iii) excipient influence on particle morphology with the example of Polysorbate 80 (PS80). As examples of agnostic applicability of pretrained models, we also elucidate the application to two high-throughput microscopy methods: microflow and background membrane imaging. We show that different particle populations with different morphological and visual features can be identified in different samples by leveraging out-of-the-box pretrained models to analyze images from each sample.
For effective resolution of regional subacute inflammation and prevention of biofouling formation, we have developed a polymeric implant that can release meloxicam, a selective cyclooxygenase (COX)-2 inhibitor, in a sustained manner. Meloxicam-loaded polymer matrices were produced by hot-melt extrusion, with commercially available biocompatible polymers, poly(ε-caprolactone) (PCL), poly(lactide-co-glycolide) (PLGA), and poly(ethylene vinyl acetate) (EVA). PLGA and EVA had a limited control over the drug release rate partly due to the acidic microenvironment and hydrophobicity, respectively. PCL allowed for sustained release of meloxicam over two weeks and was used as a carrier of meloxicam. Solid-state and image analyses indicated that the PCL matrices encapsulated meloxicam in crystalline clusters, which dissolved in aqueous medium and generated pores for subsequent drug release. The subcutaneously implanted meloxicam-loaded PCL matrices in rats showed pharmacokinetic profiles consistent with their in vitro release kinetics, where higher drug loading led to faster drug release. This study finds that the choice of polymer platform is crucial to continuous release of meloxicam and the drug release rate can be controlled by the amount of drug loaded in the polymer matrices.
The development of long-acting drug formulations requires efficient characterization technique as the designed 6-12 months release duration renders real-time in vitro and in vivo experiments cost and time prohibitive. Using a novel image-based release modeling method, release profiles were predicted from X-Ray Microscopy (XRM) of T0 samples. A validation study with the in vitro release test shows good prediction accuracy of the initial burst release. Through fast T0 image-based release prediction, the impact of formulation and process parameters on burst release rate was investigated. Recognizing the limitations of XRM, correlative imaging with Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) was introduced. A water stress test was designed to directly elucidate the formation of pores through polymer-drug-water interplay. Through an iterative correction method that considers poly(lactic-co-glycolic acid) (PLGA) polymer degradation, good agreement was achieved between release predictions using FIB-SEM images acquired from T0 samples and in vitro testing data. Furthermore, using image-based release simulations, a practical percolation threshold was identified that has profound influence on the implant performance. It is proposed as an important critical quality attribute for biodegradable long-acting delivery system, that needs to be investigated and quantified.
For oral solid dosage forms, disintegration and dissolution properties are closely related to the powders and particles used in their formulation. However, there remains a strong need to characterize the impact of particle structures on tablet compaction and performance. Three-dimensional non-invasive tomographic imaging plays an increasingly essential role in the characterization of drug substances, drug product intermediates, and drug products. It can reveal information hidden at the micro-scale which traditional characterization approaches fail to divulge due to a lack of resolution. In this study, two batches of spray-dried particles (SDP) and two corresponding tablets of an amorphous product, merestinib (LY2801653), were analyzed with 3D X-Ray Microscopy. Artificial intelligence-based image analytics were used to quantify physical properties, which were then correlated with dissolution behavior. The correlation derived from the image-based characterization was validated with conventional laboratory physical property measurements. Quantitative insights obtained from image-analysis including porosity, pore size distribution, surface area and pore connectivity helped to explain the differences in dissolution behavior between the two tablets, with root causes traceable to the microstructure differences in their corresponding SDPs.
Powder compaction is a complex manufacturing process, even though the procedural description is simple. While different methods are used in the literature, it is still challenging to understand the governing principles. It is especially challenging for empirical studies to investigate particle-level interactions. Thus, computational analyses are required for particle-level understanding. A wide range of computational methods has been developed, such as the discrete element method (DEM) and the multi-particle finite element method (MPFEM), to characterize powder compaction at the particle level. However, a limited number of studies in the literature have analyzed powder compaction using the 3D multi-particle finite element method. Historically, these studies focus only on solid particles. The compaction behavior of hollow spheres, common to pharmaceutical spray drying, was investigated both computationally and experimentally. In the computational analysis, two different particle sizes with different shell-thicknesses were examined using the 3D multi-particle finite element method. In the experimental study, polymer hydroxypropyl methylcellulose acetate succinate (HPMCAS) particles spray-dried at two different outlet temperatures (45 °C and 80 °C) were used. The results showed that particle diameter/shell-thickness (d/w) plays an essential role in powder compaction behavior. Regardless of the particle size, reducing shell-thickness reduced the required global axial stress to reach equivalent levels of relative density. However, with a constant ratio of d/w, changes to particle size (d) did not significantly influence the global compaction behavior. Similar results were observed in experimental studies. Simulation results showed that thinner-shell particles yield early in the compaction stage. Additionally, both experimentally and computationally, a spherical hollow particle buckling effect was observed. In summary, this study provides new information on how powder compaction behavior was influenced by particle size and particle shell-thickness.
Long-acting implants are typically formulated using carrier(s) with specific physical and chemical properties, along with the active pharmaceutical ingredient (API), to achieve the desired daily exposure for the target duration of action. In characterizing such formulations, real-time in-vitro and in-vivo experiments that are typically used to characterize implants are lengthy, costly, and labor intensive as these implants are designed to be long acting. A novel characterization technique, combining high resolution three-dimensional X-Ray microscopy imaging, image-based quantification, and transport simulation, has been employed to provide a mechanistic understanding of formulation and process impact on the microstructures and performance of a polymer-based implant. Artificial intelligence-based image segmentation and image data analytics were used to convert morphological features visualized at high resolution into numerical microstructure models. These digital models were then used to calculate key physical parameters governing drug transport in a polymer matrix, including API uniformity, API domain size, and permeability. This powerful new tool has the potential to advance the mechanistic understanding of the interplay between drug-microstructure and performance and accelerate the therapeutic development long-acting implants.
Carrier-based dry powder inhaler (DPI) formulations need to be accurately characterised for their particle size distributions, surface roughnesses, fines contents and flow properties. Understanding the micro-structure of the powder formulation is crucial, yet current characterisation methods give incomplete information. Commonly used techniques like laser diffraction (LD) and optical microscopy (OM) are limited due to the assumption of sphericity and can give variable results depending on particle orientation and dispersion. The aim of this work was to develop new powder analytical techniques using X-ray computed tomography (XCT) that could be employed for non-destructive metrology of inhaled formulations. α-lactose monohydrate powders with different characteristics have been analysed, and their size and shape (sphericity/aspect ratio) distributions compared with results from LD and OM. The three techniques were shown to produce comparable size distributions, while the different shape distributions from XCT and OM highlight the difference between 2D and 3D imaging. The effect of micro-structure on flowability was also analysed through 3D measurements of void volume and tap density. This study has demonstrated for the first time that XCT provides an invaluable, non-destructive and analytical approach to obtain number- and volume-based particle size distributions of DPI formulations in 3D space, and for unique 3D characterisation of powder micro-structure.
PurposeWhile including amorphous solid dispersion (ASD) in tablet formulations is increasingly common, tablets containing high ASD loading are associated with slow disintegration, which presents a challenge to control pill burden for less potent compounds.Methods
We use a model ASD, composed of a hydrophobic drug with copovidone and a non-ionic surfactant, to explore formulation options that can prevent slow disintegration.ResultsIn addition to the ASD loading, the pH of the disintegration medium and the inclusion of inorganic salts in the tablet also have an impact on the tablet disintegration time. Certain kosmotropic salts, when added in the formulation, can significantly accelerate tablet disintegration, though the rank order in their effectiveness does not exactly follow the Hofmeister series at pH 1.8. The particle size and dissolution rate of the salt can contribute to its overall effectiveness.Conclusion
We provided a mechanistic explanation of the disintegration process: fast-dissolving kosmotropic salt results in a concentrated salt solution inside the restrained tablet matrix, thus inhibiting the dissolution of copovidone and preventing polymer gelling which is the main cause leading the slow disintegration. The outcome of this study has enabled the design of a higher ASD loading platform formulation for copovidone based ASD.
MicroCT aids the mechanistic understanding of the role of inorganic salt in the tablet disintegration of amorphous solid dispersion based formulation
Management, Analysis, and Simulation of Micrographs with Cloud Computing - Volume 27 Issue 2 - Shawn Zhang, Alan P. Byrnes, Jasna Jankovic, Joseph Neilly
Poor water solubility of many drugs has emerged as one of the major challenges in the pharmaceutical world. Polymer-based amorphous solid dispersions have been considered as the major advancement in overcoming limited aqueous solubility and oral absorption issues. The principle drawback of this approach is that they can lack necessary stability and revert to the crystalline form on storage. Significant upfront development is, therefore, required to generate stable amorphous formulations. A thorough understanding of the processes occurring at a molecular level is imperative for the rational design of amorphous solid dispersion products. This review attempts to address the critical molecular and thermodynamic aspects governing the physicochemical properties of such systems. A brief introduction to Biopharmaceutical Classification System, solid dispersions, glass transition, and solubility advantage of amorphous drugs is provided. The objective of this review is to weigh the current understanding of solid dispersion chemistry and to critically review the theoretical, technical, and molecular aspects of solid dispersions (amorphization and crystallization) and potential advantage of polymers (stabilization and solubilization) as inert, hydrophilic, pharmaceutical carrier matrices. In addition, different preformulation tools for the rational selection of polymers, state-of-the-art techniques for preparation and characterization of polymeric amorphous solid dispersions, and drug supersaturation in gastric media are also discussed.
Purpose
Although the bonding area (BA) and bonding strength (BS) interplay is used to explain complex tableting behaviors, it has never been experimentally proven. The purpose of this study is to unambiguously establish the distinct contributions of each by decoupling the contributions from BA and BS.
Methods
To modulate BA, a Soluplus® powder was compressed into tablets at different temperatures and then broken following equilibration at 25°C. To modulate BS, tablets were equilibrated at different temperatures. To simultaneously modulate BA and BS, both powder compression and tablet breaking test were carried out at different temperatures.
Results
Lower tablet tensile strength is observed when the powder is compressed at a lower temperature but broken at 25°C. This is consistent with the increased resistance to polymer deformation at lower temperatures. When equilibrated at different temperatures, the tensile strength of tablets prepared under identical conditions increases with decreasing storage temperature, indicating that BS is higher at a lower temperature. When powder compression and tablet breaking are carried out at the same temperature, the profile with a maximum tensile strength at 4°C is observed due to the BA-BS interplay.
Conclusion
By systematically varying temperature during tablet compression and breaking, we have experimentally demonstrated the phenomenon of BA-BS interplay in tableting.
Application of amorphous solid dispersions (ASDs) is considered one of the most promising approaches to increase the dissolution rate and extent of bioavailability of poorly water soluble drugs. Such intervention is often required for new drug candidates in that enablement, bioavailability is not sufficient to generate a useful product. Importantly, tableting of ASDs is often complicated by a number of pharmaceutical and technological challenges including poor flowability and compressibility of the powders, compression-induced phase changes or phase separation and slow disintegration due to the formation of a gelling polymer network (GPN). The design principles of an ASD-based system include its ability to generate supersaturated systems of the drug of interest during dissolution. These metastable solutions can be prone to precipitation and crystallization reducing the biopharmaceutical performance of the dosage form. The main aim of the research in this area is to maintain the supersaturated state and optimally enhance bioavailability, meaning that crystallization should be delayed or inhibited during dissolution, as well as in solid phase (e.g., during manufacturing and storage). Based on the expanding use of ASD technology as well as their downstream processing, there is an acute need to summarize the results achieved to this point to better understand progress and future risks. The aim of this review is to focus on the conversion of ASDs into tablets highlighting results from various viewpoints.
Copyright © 2015. Published by Elsevier B.V.
Purpose:
To demonstrate the novel application of nano X-ray computed tomography (NanoXCT) for visualizing and quantifying the internal structures of pharmaceutical particles.
Methods:
An Xradia NanoXCT-100, which produces ultra high-resolution and non-destructive imaging that can be reconstructed in three-dimensions (3D), was used to characterize several pharmaceutical particles. Depending on the particle size of the sample, NanoXCT was operated in Zernike Phase Contrast (ZPC) mode using either: 1) large field of view (LFOV), which has a two-dimensional (2D) spatial resolution of 172 nm; or 2) high resolution (HRES) that has a resolution of 43.7 nm. Various pharmaceutical particles with different physicochemical properties were investigated, including raw (2-hydroxypropyl)-beta-cyclodextrin (HβCD), poly (lactic-co-glycolic) acid (PLGA) microparticles, and spray-dried particles that included smooth and nanomatrix bovine serum albumin (BSA), lipid-based carriers, and mannitol.
Results:
Both raw HβCD and PLGA microparticles had a network of voids, whereas spray-dried smooth BSA and mannitol generally had a single void. Lipid-based carriers and nanomatrix BSA particles resulted in low quality images due to high noise-to-signal ratio. The quantitative capabilities of NanoXCT were also demonstrated where spray-dried mannitol was found to have an average void volume of 0.117 ± 0.247 μm(3) and average void-to-material percentage of 3.5%. The single PLGA particle had values of 1993 μm(3) and 59.3%, respectively.
Conclusions:
This study reports the first series of non-destructive 3D visualizations of inhalable pharmaceutical particles. Overall, NanoXCT presents a powerful tool to dissect and observe the interior of pharmaceutical particles, including those of a respirable size.
Over the last 15 years, x-ray microtomography has become a useful technique to obtain morphological,
structural, and topological information on materials. Moreover, these three-dimensional (3D) images can be
used as input data to assess certain properties (e.g., permeability) or to simulate phenomena (e.g., transfer
properties). In order to capture all the features of interest, high spatial resolution is required. This involves
imaging small samples, raising the question of the representativity of the data sets. In this article, we (i) present
a methodology to analyze the microstructural properties of complex porous media from 3D images, (ii) assess
statistical representative elementary volumes (REVs) for such materials; and (iii) establish criteria to delimit
these REVs. In the context of cultural heritage conservation, a statistical study was done on 30 quarry samples
for three sorts of stones. We first present the principles of x-ray microtomography experiments and emphasize
the care that must be taken in the 3D image segmentation steps. Results show that statistical REVs exist for these
media and are reached for the image sizes studied (1300×1300×1000 voxels) for two characteristics: porosity
and chord length distributions. Furthermore, the estimators used (porosity, autocorrelation function, and chord
length distributions) are sufficiently sensitive to quantitatively distinguish these three porous media from each
other. Lastly, this study puts forward criteria based on the above-mentioned estimators to evaluate the REVs.
These criteria avoid having to repeat the statistical study for each new material studied. This is particularly
relevant to quantitatively monitor the modifications in materials (weathering, deformation . . . ) or to determine
the smallest 3D volume for simulation in order to reduce computing time.
The effect of contact flattening and material properties on the fracture stress calculation for the diametrical compression test used to evaluate compact strength was examined through finite element simulations. Two-dimensional simulations were carried out using linear elastic, elastoplastic, and porous elastoplastic models with commercial finite element software. A parametric study was performed by varying the elastic modulus (E), Poisson's ratio (), contact frictional coefficient (), yield stress (yield), and compact relative density (RD). Stress contours generated from these simulations were compared to the Hertzian and Hondros analytical expressions. Linear elastic simulations show excellent agreement with the analytical solutions. Significant deviation, however, occurs for the elastoplastic and porous elastoplastic simulations at larger diametrical strain with material plasticity. A better understanding of the stress-state of diametrically loaded plastically deforming disks has been demonstrated in this computational and experimental work. Results from these finite element simulations confirm that the standard tensile strength calculation: f = 2P/ Dt, is suitable for linear elastic materials. However, the incorporation of plasticity into the material model results in a significant change in the maximum principal stress field (magnitude and location) rendering the Hertzian estimate of tensile strength invalid. A map to check the validity of the Hertzian equation is proposed.
The characterization and performance of stable amorphous solid dispersion systems were evaluated in 40 research papers reporting active pharmaceutical ingredient (API) dissolution and bioavailability from various systems containing polymers. The results from these studies were broadly placed into three categories: amorphous dispersions that improved bioavailability (∼82% of the cases), amorphous dispersions possessing lower bioavailability than the reference material (∼8% of the cases), and amorphous dispersions demonstrating similar bioavailabilities as the reference material (∼10% of the cases). A comparative analysis of these studies revealed several in vitro and in vivo variables that could have influenced the results. The in vitro factors compared primarily centered on dissolution testing and equipment, content and amount of dissolution media, sink or nonsink conditions, agitation rates, media pH, dissolution characteristics of the polymer, and dispersion particle size. The in vivo factors included reference materials used for bioavailability comparisons, animal species utilized, fasting versus fed conditions, and regional differences in gastrointestinal (GI) content and volume. On the basis of these considerations, a number of recommendations were made on issues ranging from the assessment of physical stability of API-polymer dispersions to in vivo GI physiological factors that require consideration in the performance evaluation of these systems.
The current study aimed to examine the pharmaceutical applications of the focused-ion-beam (FIB) in the inhalation aerosol field, particularly to particle porosity determination (i.e. percentage of particles having a porous interior).
The interior of various spray dried particles (bovine serum albumin (BSA) with different degrees of surface corrugation, mannitol, disodium cromoglycate and sodium chloride) was investigated via FIB milling at customized conditions, followed by viewing under a high resolution field-emission scanning electron microscope. Two sets of ten particles for each sample were examined.
For the spray-dried BSA particles, a decrease in particle porosity (from 50 to 0%) was observed with increasing particle surface corrugation. Spray-dried mannitol, disodium cromoglycate and sodium chloride particles were determined to be 90-100%, 0-10% and 0% porous, respectively. The porosity in the BSA and mannitol particles thus should be considered for the aerodynamic behaviour of these particles.
The FIB technology represents a novel approach useful for probing the interior of particles linking to the aerosol properties of the powder. Suitable milling protocols have been developed which can be adapted to study other similar particles.
Relatively large (>5 microm) and porous (mass density <0.4 g/cm3) particles present advantages for the delivery of drugs to the lungs, e.g., excellent aerosolization properties. The aim of this study was, first, to formulate such particles with excipients that are either FDA-approved for inhalation or endogenous to the lungs; and second, to compare the aerodynamic size and performance of the particles with theoretical estimates based on bulk powder measurements.
Dry powders were made of water-soluble excipients (e.g., lactose, albumin) combined with water-insoluble material (e.g., lung surfactant), using a standard single-step spray-drying process. Aerosolization properties were assessed with a Spinhaler device in vitro in both an Andersen cascade impactor and an Aerosizer.
By properly choosing excipient concentration and varying the spray drying parameters, a high degree of control was achieved over the physical properties of the dry powders. Mean geometric diameters ranged between 3 and 15 microm, and tap densities between 0.04 and 0.6 g/cm3. Theoretical estimates of mass mean aerodynamic diameter (MMAD) were rationalized and calculated in terms of geometric particle diameters and bulk tap densities. Experimental values of MMAD obtained from the Aerosizer most closely approximated the theoretical estimates, as compared to those obtained from the Andersen cascade impactor. Particles possessing high porosity and large size, with theoretical estimates of MMAD between 1-3 microm, exhibited emitted doses as high as 96% and respirable fractions ranging up to 49% or 92%, depending on measurement technique.
Dry powders engineered as large and light particles, and prepared with combinations of GRAS (generally recognized as safe) excipients, may be broadly applicable to inhalation therapy.
This review covers recent developments in the area of particle engineering via spray drying. The last decade has seen a shift from empirical formulation efforts to an engineering approach based on a better understanding of particle formation in the spray drying process. Microparticles with nanoscale substructures can now be designed and their functionality has contributed significantly to stability and efficacy of the particulate dosage form. The review provides concepts and a theoretical framework for particle design calculations. It reviews experimental research into parameters that influence particle formation. A classification based on dimensionless numbers is presented that can be used to estimate how excipient properties in combination with process parameters influence the morphology of the engineered particles. A wide range of pharmaceutical application examples -- low density particles, composite particles, microencapsulation, and glass stabilization -- is discussed, with specific emphasis on the underlying particle formation mechanisms and design concepts.
Tablet defects encountered during the manufacturing of oral formulations can result in quality concerns, timeline delays, and elevated financial costs. Internal tablet cracking is not typically measured in routine inspections but can lead to batch failures such as tablet fracturing. X-ray computed tomography (XRCT) has become well-established to analyze internal cracks of oral tablets. However, XRCT normally generates very large quantities of image data (thousands of 2D slices per data set) which require a trained professional to analyze. A user-guided manual analysis is laborious, time-consuming, and subjective, which may result in a poor statistical representation and inconsistent results. In this study, we have developed an analysis program that incorporates deep learning convolutional neural networks to fully automate the XRCT image analysis of oral tablets for internal crack detection. The computer program achieves robust quantification of internal tablet cracks with an average accuracy of 94%. In addition, the deep learning tool is fully automated and achieves a throughput capable of analyzing hundreds of tablets. We have also explored the adaptability of the deep learning analysis program towards different products (e.g., different types of bottles and tablets). Finally, the deep learning tool is effectively implemented into the industrial pharmaceutical workflow.
Spray drying is used by numerous industries, with applications ranging from dairy and flavorings to detergents and ceramics. This chapter focuses on amorphous solid dispersions (ASDs), which is typically used by small molecule active ingredients in a polymer matrix and spray‐dried out of an organic solvent. It presents an overview of the role of solid dispersions, in particular spray‐dried solid dispersions, within the pharmaceutical industry. The chapter considers these spray‐dried particles from a pharmaceutical materials perspective, both in consideration of materials selected during formulation and in understanding of the stability of ASDs. It also considers spray drying in context of individual unit operations used to convert active ingredients and raw materials in to a final dosage form. Common methods for spray drying atomization include pressure nozzles, rotary atomizers, and two‐fluid nozzles. The chapter illustrates the usefulness of using scale‐independent parameters and mechanistic understanding for the support of process scale‐up of transfer.
Quantitative Characterization of Crystallization in Amorphous Solid Dispersion Drug Tablets Using X-Ray Micro-Computed Tomography - Volume 24 Supplement - Shawn Zhang, Joseph Neilly, Aiden Zhu, Jacie Chen, Gerald Danzer
Downstream processing aspects of a stable form of amorphous itraconazole exhibiting enhanced dissolution properties were studied. Preparation of this ternary amorphous solid dispersion by either spray drying or hot melt extrusion led to significantly different powder processing properties. Particle size and morphology was analysed using scanning electron microscopy. Flow, compression, blending and dissolution were studied using rheometry, compaction simulation and a dissolution kit. The spray dried material exhibited poorer flow and reduced sensitivity to aeration relative to the milled extrudate. Good agreement was observed between differing forms of flow measurement, such as Flow Function, Relative flow function, Flow rate index, Aeration rate, the Hausner ratio and the Carr index. The stability index indicated that both powders were stable with respect to agglomeration, de-agglomeration and attrition. Tabletability and compressibility studies showed that spray dried material could be compressed into stronger compacts than extruded material. Blending of the powders with low moisture, freely-flowing excipients was shown to influence both flow and compression. Porosity studies revealed that blending could influence the mechanism of densification in extrudate and blended extrudate formulations. Following blending, the powders were compressed into four 500 mg tablets, each containing a 100 mg dose of amorphous itraconazole. Dissolution studies revealed that the spray dried material released drug faster and more completely and that blending excipients could further influence the dissolution rate.
A complete description of the particle formation process can only be realized with techniques that enable the measurement of the composition and structural dependence of individual particles.
The purpose of this publication is to highlight the utility of one such high resolution imaging technique; focused-ion scanning electron microscopy (FIB-SEM). As a model system, amorphous dispersion particles of felodipine and polyvinylpyrrolidone (PVP) were prepared by spray drying and used to interrogate single particles. Further, FIB-SEM was coupled with energy dispersive X-ray analysis (EDX) to characterize spatial chemical distributions in spray dried amorphous solid dispersion particles. Within a single spray drying batch, individual particles exhibited different phase behavior as a function of particle size. Larger particles showed notable amorphous-amorphous phase separation while smaller particles showed uniform composition. The morphology of particles was also found to be a function of particle size. Larger particles were consistently more porous in nature compared to smaller particles. The observed differences in compositional heterogeneity of different spray dried particles as a function of size are interpreted via theoretical arguments based on the Peclet number, the ratio of the evaporative flux of the solvent to the diffusive flux of the drug and the polymer within the droplet. Phase behavior may also be interpreted in terms of equilibrium ternary phase diagrams. Regardless, commonly used bulk physical and chemical characterization techniques may be used to establish correlations between the nature of the dispersion and the processing parameters. However, these techniques lack the resolution to provide a scientific link between the processing conditions and the nature of individual particles. The current paper highlights the utility of high resolution morphological and compositional measurements of individual particles.
X-ray computed tomography (XRCT) is a technique that uses X-ray images to reconstruct the internal microstructure of objects. Known as a CAT scan in medicine, it has found wide application for whole-body and partial-body imaging of hard tissues (e.g., bone). A modern tabletop XRCT system with a resolution of about 4 μm was used to characterize some pharmaceutical granules. Total porosity, pore size distribution, and geometric structure of pores in granules produced using different conditions and materials were studied. The results were compared to data obtained from mercury porosimetry. It was found that while XRCT is less precise in the determination of total porosity in comparison to mercury porosimetry, it provides detailed morphological information such as pore shape, spatial distribution, and connectivity. The method is nondestructive and accurate down to the resolution of the instrument.Tomographic images show that the pore network of individual granules comprises relatively large cavities connected by narrow pore necks. The major structural difference between granules produced at different conditions of compaction and shear is a reduction in the pore neck diameter; the cavity size is relatively insensitive to these conditions. Comparison of pore size distributions determined from tomographic images and mercury porosimetry indicates that mercury intrusion measures the pore neck size distribution, while tomography measures the true size distribution of pores ca. 4 μm or larger (the instrument resolution).
Spray drying is an efficient technology for solid dispersion manufacturing since it allows extreme rapid solvent evaporation leading to fast transformation of an API-carrier solution to solid API-carrier particles. Solvent evaporation kinetics certainly contribute to formation of amorphous solid dispersions, but also other factors like the interplay between the API, carrier and solvent, the solution state of the API, formulation parameters (e.g. feed concentration or solvent type) and process parameters (e.g. drying gas flow rate or solution spray rate) will influence the final physical structure of the obtained solid dispersion particles. This review presents an overview of the interplay between manufacturing process, formulation parameters, physical structure, and performance of the solid dispersions with respect to stability and drug release characteristics.
The aim of this work was to study the performance of mannitol carrier particles of tailored surface roughness in dry powder inhaler formulations. Carrier particles of different surface roughness were prepared by spray drying of aqueous mannitol solutions at different outlet temperatures at a pilot-scale spray dryer. However, the carrier particles did not only change in surface roughness but also in shape. This is why the impact of carrier shape on the performance of carrier based dry powder inhalates was evaluated also. The highest fine particle fraction (FPF), that is the amount of active pharmaceutical substance, delivered to the deep lung, is achieved when using rough, spherical carrier particles (FPF=29.23±4.73%, mean arithmetic average surface roughness (mean R(a))=140.33±27.75nm, aspect ratio=0.925). A decrease of surface roughness (mean R(a)=88.73±22.25nm) leads to lower FPFs (FPF=14.62±1.18%, aspect ratio=0.918). The FPF further decreases when irregular shaped particles are used. For those particles, the micronized active accumulates within the cavities of the carrier surface during the preparation of the powder mixtures. Upon inhalation, the cavities may protect the active from being detached from the carrier.
Theoretical and experimental investigations of the particle formation process during spray drying are presented. A novel experimental method allows observation of individual, free flowing droplets during drying in a laminar gas flow and subsequent analysis of the resulting monodisperse, monomorphic dry particles. A second method combines a vibrating orifice generator and a bench top spray drier, which allows production and sampling of monodisperse particles at different drying stages. The experimental results are compared to a full numerical model and a simplified analytical model. Two dimensionless parameters are identified that influence particle formation: the Peclet number, which is the ratio of the diffusion coefficient of the solute and the evaporation rate, and the initial saturation of the excipients. In an application example, particle design is shown to improve the aerosol properties of powders intended for pulmonary drug delivery.
Drug-polymer solid dispersion has been demonstrated as a feasible approach to formulate poorly water-soluble drugs in the amorphous form, for the enhancement of dissolution rate and bioperformance. The solubility (for crystalline drug) and miscibility (for amorphous drug) in the polymer are directly related to the stabilization of amorphous drug against crystallization. Therefore, it is important for pharmaceutical scientists to rationally assess solubility and miscibility in order to select the optimal formulation (e.g., polymer type, drug loading, etc.) and recommend storage conditions, with respect to maximizing the physical stability. This commentary attempts to discuss the concepts and implications of the drug-polymer solubility and miscibility on the stabilization of solid dispersions, review recent literatures, and propose some practical strategies for the evaluation and development of such systems utilizing a working diagram.
Spray drying is a transformation of feed from a fluid state into a dried particulate form by spraying the feed into a hot drying medium. The main aim of drying by this method in pharmaceutical technology is to obtain dry particles with desired properties. This review presents the hardware and process parameters that affect the properties of the dried product. The atomization devices, drying chambers, air-droplet contact systems, the collection of dried product, auxiliary devices, the conduct of the spray drying process, and the significance of the individual parameters in the drying process, as well as the obtained product, are described and discussed.
The amorphous state is critical in determining the solid-state physical and chemical properties of many pharmaceutical dosage forms. This review describes the characteristics of the amorphous state and some of the most common methods that can be used to measure them. Examples of pharmaceutical situations where the presence of the amorphous state plays an important role are presented. The application of our current knowledge to pharmaceutical formulation problems is illustrated, and some strategies for working with amorphous character in pharmaceutical systems are provided.
The importance of amorphous pharmaceutical solids lies in their useful properties, common occurrence, and physicochemical instability relative to corresponding crystals. Some pharmaceuticals and excipients have a tendency to exist as amorphous solids, while others require deliberate prevention of crystallization to enter and remain in the amorphous state. Amorphous solids can be produced by common pharmaceutical processes, including melt quenching, freeze- and spray-drying, milling, wet granulation, and drying of solvated crystals. The characterization of amorphous solids reveals their structures, thermodynamic properties, and changes (crystallization and structural relaxation) in single- and multi-component systems. Current research in the stabilization of amorphous solids focuses on: (i) the stabilization of labile substances (e.g., proteins and peptides) during processing and storage using additives, (ii) the prevention of crystallization of the excipients that must remain amorphous for their intended functions, and (iii) the selection of appropriate storage conditions under which amorphous solids are stable.
3D characterisation of dry powder inhaler formulations: developing X-ray micro computed tomography approaches.
- Gajjar P.
- Styliari I.
- Nguyen T.
- Carr J.
Manufacturing of solid dispersions of poorly water soluble drugs by spray drying: formulation and process considerations.
- Paudel A.
- Worku Z.A.
- Guns J.M.S.
- Guns S.