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.

Spin freeze-drying, as a part of a continuous freeze-drying technology, is associated with a much higher drying rate and a higher level of process control in comparison with batch freeze-drying. However, the impact of the spin freezing rate on the dried product layer characteristics is not well understood at present. This research focuses on the relation between spin-freezing and pore size, pore shape, dried product mass transfer resistance and solid state of the dried product layer. This was thoroughly investigated via high-resolution X-ray micro-computed tomography (µCT), scanning electron microscopy (SEM), thermal imaging and solid state X-ray diffraction (XRD). It was concluded that slow spin-freezing rates resulted in the formation of highly tortuous structures with a high dried-product mass-transfer resistance, while fast spin-freezing rates resulted in lamellar structures with a low tortuosity and low dried-product mass-transfer resistance.

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 ($f_2$) = 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.

Digital volume correlation (DVC) is a 3D image-based technique for displacement and strain computation. Traditionally, both (digital image correlation) DIC and DVC are methods based on two individual time frames; the estimation of the displacement and strain field is done using one reference and one moving frame as input. However, dynamic experiments generate more than two temporal frames. Therefore, with classical DVC techniques, only a subset of the available data is used. In this study, we propose a novel DVC method that can rely on more than two frames for the displacement and strain computation. The proposed method aims to be as general as possible; there is no constraint regarding the nature or the rate of the displacement (e.g., cyclic or linear). The aim of this method is to impose a temporal regularization that improves the self-consistency of the algorithm. The multi-frame DVC improves the quality of the registration in challenging situations. As an example, we investigate the dissolution of a pharmaceutical tablet in water, which undergoes three processes: swelling, gel formation, and material erosion. The accuracy of the registration—quantified by the sum of square differences (SSD)—has improved by 23% on an average with respect to the classical two-frame method. Classical DVC methods fail in registering images with structures that change appearance through time, such as the tablet that, in contact with water, reacts chemically, changing phase and becoming a gel. Moreover, we proved that multi-frame DVC is more robust in registering images with severe but realistic motion artefacts. As an example for this case, we apply the method to a series of μ-CT datasets of aluminum foam during a compression experiment. As seen with the tablets, we are in a situation where the appearance of the structures in the images changes through time, but in this case it is because of motion artefacts. Finally, the use of more than two frames makes the method more robust against noisy images, with an average improvement of 35% in registration accuracy obtained using the three-frame DVC method compared to the classical two-frame DVC method.