Investigation of coating layer morphology by micro-computed X-ray tomography

Three-Dimensional Characterization of Dry Particle Coating Structures Originating from the Mechano-fusion Process

Dry particle coating processes are of key importance for creating functionalized materials. By a change in surface structure, initiated during coating, a surface property change and thus functionalization can be achieved. This study introduces an innovative approach employing 3D X-ray micro-computed tomography (micro-CT) to characterize coated particles, consisting of spherical alumina particles (d50 = 45.64 μm), called hosts, surrounded by spherical polystyrene particles (d50 = 3.5 μm), called guests. The formed structures, hetero-aggregates, are generated by dry particle coating using mechano-fusion (MF). A deeper understanding of the influence of MF process parameters on the coating structures is a crucial step toward tailoring of coating structure, resulting surface property and functionalization. Therefore, the influence of rotational speed, process time, and total mechanical energy input during MF is explored. Leveraging micro-CT data, acquired of coated particles, enables non-stereologically biased and quantitative coating structure analysis. The guest's coating thickness is analyzed using the maximum inscribed sphere and ray method, two different local thickness measurement approaches. Particle-discrete information of the coating structure are available after a proper image processing workflow is implemented. Coating efficiency and guest's neighboring relations (nearest neighbor distance and number of neighbors inside search radius) are evaluated.

Advances in Structure Pharmaceutics from Discovery to Evaluation and Design

Drug delivery systems (DDSs) play an important role in delivering active pharmaceutical ingredients (APIs) to targeted sites with a predesigned release pattern. The chemical and biological properties of APIs and excipients have been extensively studied for their contribution to DDS quality and effectiveness; however, the structural characteristics of DDSs have not been adequately explored. Structure pharmaceutics involves the study of the structure of DDSs, especially the three-dimensional (3D) structures, and its interaction with the physiological and pathological structure of organisms, possibly influencing their release kinetics and targeting abilities. A systematic overview of the structures of a variety of dosage forms, such as tablets, granules, pellets, microspheres, powders, and nanoparticles, is presented. Moreover, the influence of structures on the release and targeting capability of DDSs has also been discussed, especially the in vitro and in vivo release correlation and the structure-based organ- and tumor-targeting capabilities of particles with different structures. Additionally, an in-depth discussion is provided regarding the application of structural strategies in the DDSs design and evaluation. Furthermore, some of the most frequently used characterization techniques in structure pharmaceutics are briefly described along with their potential future applications.

Characterization of Pharmaceutical Tablets by X-ray Tomography

Solid dosage forms such as tablets are extensively used in drug administration for their simplicity and large-scale manufacturing capabilities. High-resolution X-ray tomography is one of the most valuable non-destructive techniques to investigate the internal structure of the tablets for drug product development as well as for a cost effective production process. In this work, we review the recent developments in high-resolution X-ray microtomography and its application towards different tablet characterizations. The increased availability of powerful laboratory instrumentation, as well as the advent of high brilliance and coherent 3rd generation synchrotron light sources, combined with advanced data processing techniques, are driving the application of X-ray microtomography forward as an indispensable tool in the pharmaceutical industry.

Development of Flow-Through Cell Dissolution Method for In Situ Visualization of Dissolution Processes in Solid Dosage Forms Using X-ray μCT

Visualization of the dynamic behavior of pharmaceutical dosage forms during the dissolution process offers a better understanding of the drug release mechanism, enabling the design of customized dosage forms. In this study, an X-ray tomography-based approach is proposed to monitor and analyze the dynamics of the structure at the pore scale level during the dissolution process. A flow-through cell dissolution apparatus was developed, capable of mimicking the standard in vitro dissolution process, which can be easily positioned in an X-ray tomography setup. The method was utilized to study the dissolution of a Capa^® (polycaprolactone)-based sustained-release 3D printed tablet. The impact of the flow rate on the active pharmaceutical ingredient (API) release rate was studied and 16 mL/min was selected as a suitable flow rate. Furthermore, cesium chloride (CsCl) was used as a contrast agent to increase the contrast between the sample and the dissolution medium. Data obtained with this novel technique were in a good agreement with the released drug rate acquired by the standard in vitro dissolution test (the similarity factor (f2) = 77%). Finally, the proposed approach allowed visualizing the internal structure of the sample, as well as real-time tracking of solution ingress into the product.

A semi-empirical model for estimation of flaw size in internally defective tablets

Capping is a mechanical defect in tablets, which is attributed to multiple factors including intrinsic material properties and tableting conditions. A suitable non-destructive approach using acoustically derived elastic modulus has showed distinctive features between a defective tablet and a defect-free tablet. In this work, a semi-empirical model was developed to estimate flaw size in an internally defective tablet from the relationship among elastic modulus, tablet density, and time of flight (acoustic wave to traverse through the tablet). The model was found fundamentally consistent where the derived flaw size showed clear dependence on powder mechanical properties of seven diverse formulations studied. Furthermore, the flaw size was reasonably correlated with the internal tablet microstructure illustrated by X-ray micro-tomography findings, both qualitatively and quantitatively. This model could thus be efficiently implemented for risk-based evaluation of internal defects in visibly intact tablets to ensure robustness of drug products.

Optimization of in-line near-infrared measurement for practical real time monitoring of coating weight gain using design of experiments

This study was conducted to develop an in-line near-infrared (NIR) spectroscopy approach that allows real time quantitative analysis of the coating weight gain on a moving tablet surface during a coating process where talc is used. A holder directly inserting a diffuse reflectance probe into a coating pan was designed, and the optimal measurement conditions were identified using the design of experiments (DoE). The surface of the probe was kept clean of coating droplets at a maximum distance between the probe and the holder of 272.5 mm, leading to the acquisition of accurate spectral data. Under this condition, partial least squares regression (PLSR) was developed using the spectra from 7197 to 6233 cm^-1, which covers the specific peaks for the core tablet and the coating solution. Under the same conditions, least squares regression (LSR) was developed using the univariate predictive analysis of the single absorption spectrum of talc at 7181 cm^-1. In a comparison of the accuracy of the two models, PLSR was found to be more accurate as a result of testing the significance of differences between these distributions in terms of the root mean square errors of prediction (RMSEP) using a randomization t-test. Additionally, it confirmed that the predicted weight gain using NIR spectroscopy was correlated with the coating thickness measured using micro-CT. In conclusion, this study developed an in-line NIR measurement approach for the real-time monitoring of the coating weight gain of tablets and optimized the conditions by evaluating the effect of various factors.

A micro-XRT image analysis and machine learning methodology for the characterisation of multi-particulate capsule formulations

The application of X-ray microtomography for quantitative structural analysis of pharmaceutical multi-particulate systems was demonstrated for commercial capsules, each containing approximately 300 formulated ibuprofen pellets. The implementation of a marker-supported watershed transformation enabled the reliable segmentation of the pellet population for the 3D analysis of individual pellets. Isolated translation- and rotation-invariant object cross-sections expanded the applicability to additional 2D image analysis techniques. The full structural characterisation gave access to over 200 features quantifying aspects of the pellets' size, shape, porosity, surface and orientation. The extracted features were assessed using a ReliefF feature selection method and a supervised Support Vector Machine learning algorithm to build a model for the detection of broken pellets within each capsule. Data of three features from distinct structure-related categories were used to build classification models with an accuracy of more than 99.55% and a minimum precision of 86.20% validated with a test dataset of 886 pellets. This approach to extract quantitative information on particle quality attributes combined with advanced data analysis strategies has clear potential to directly inform manufacturing processes, accelerating development and optimisation.

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Coupling micro-XRT analysis with feature selection and machine learning for advanced pharmaceutical product characterisation.

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Information on particle 3D-orientation were utilised to extract translation- and rotation-invariant object cross-sections.

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Successful extraction of over 200 quantitative pellet descriptors linked to size, shape, porosity, surface and orientation.

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Sensitivity analysis and ReliefF feature selection approach to identify predictive features for pellet classification.

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Feature-based binary SVM classification model for the detection of broken pellets within the formulated system.

WITHDRAWN: A micro-XRT Image Analysis and Machine Learning Methodology for the Characterisation of Multi-Particulate Capsule Formulations

The Publisher regrets that this article is an accidental duplication of a published article,https://doi.org/10.1016/j.ijpx.2020.100041. The duplicate article has therefore been withdrawn. The full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/our-business/policies/article-withdrawal.

Application of X-ray micro-CT for micro-structural characterization of APCVD deposited SiC coatings on graphite conduit

SiC coatings are commonly used as oxidation protective materials in high-temperature applications. The operational performance of the coating depends on its microstructure and uniformity. This study explores the feasibility of applying tabletop X-ray micro-CT for the micro-structural characterization of SiC coating. The coating is deposited over the internal surface of pipe structured graphite fuel tube, which is a prototype of potential components of compact high-temperature reactor (CHTR). The coating is deposited using atmospheric pressure chemical vapor deposition (APCVD) and properties such as morphology, porosity, thickness variation are evaluated. Micro-structural differences in the coating caused by substrate distance from precursor inlet in a CVD reactor are also studied. The study finds micro-CT a potential tool for characterization of SiC coating during its future course of engineering. We show that depletion of reactants at larger distances causes development of larger pores in the coating, which affects its morphology, density and thickness.