Comparison of Raman and Near-Infrared Chemical Mapping for the Analysis of Pharmaceutical Tablets

Quantitative analysis of drug tablet aging by fast hyper-spectral stimulated Raman scattering microscopy

Pharmaceutical development of solid-state formulations requires testing active pharmaceutical ingredients (API) and excipients for uniformity and stability. Solid-state properties such as component distribution and grain size are crucial factors that influence the dissolution profile, which greatly affect drug efficacy and toxicity, and can only be analyzed spatially by chemical imaging (CI) techniques. Current CI techniques such as near infrared microscopy and confocal Raman spectroscopy are capable of high chemical and spatial resolution but cannot achieve the measurement speeds necessary for integration into the pharmaceutical production and quality assurance processes. To fill this gap, we demonstrate fast chemical imaging by epi-detected sparse spectral sampling stimulated Raman scattering to quantify API and excipient degradation and distribution.

Exploring the complexities of drug formulation selection, storage, and shelf-life for exploration spaceflight

Medications have been a part of space travel dating back to the Apollo missions. Currently, medical kits aboard the International Space Station (ISS) contain medications and supplies to treat a variety of possible medical events. As we prepare for more distant exploration missions to Mars and beyond, risk management planning for astronaut healthcare should include the assembly of a medication formulary that is comprehensive enough to prevent or treat anticipated medical events, remains safe and chemically stable, and retains sufficient potency to last for the duration of the mission. Emerging innovation and technologies in pharmaceutical development, delivery, quality maintenance, and validation offer promise for addressing these challenges. The present editorial will summarize the current state of knowledge regarding innovative formulary optimization strategies, pharmaceutical stability assessment techniques, and storage and packaging solutions that could enhance drug safety and efficacy for future exploration spaceflight missions.

Hydrogel-enzyme micropatch array format for chemical mapping: A proof of concept

Conventional sensing methods report on concentrations of analytes in a single point of sampled medium or provide an average value. However, distributions of substances on surfaces of sampled objects often exhibit intricate inhomogeneities. In order to obtain snapshots of the chemical distributions on surfaces, we have developed enzyme-loaded hydrogel arrays (5 × 5 and 10 × 10). The acrylic 10 × 10 array base contains 100 holes, which are filled with agarose hydrogel containing assay enzymes and substrates. Such arrays can be exposed to the analyzed surfaces to collect minute amounts of analytes. Following a brief incubation, they are subsequently visualized in a custom-built array reader device. The reader incorporates a light-emitting diode-based light source, miniature camera, and Raspberry Pi single-board computer. Two Python programs capture and analyze the images of the array to extract pixel saturation values corresponding to individual hydrogel micropatches. The method has been thoroughly optimized for mapping of glucose and lactic acid. The optimized parameters were: contact time, agarose concentration, substrate concentration, enzyme concentration ratio, and enzyme concentration. The array biosensor was further tested by mapping glucose distribution in fruit/vegetable cross-sections (apple, guava, and cucumber) and lactic acid distribution in cheese. We think that this new hydrogel-based chemical mapping method can find applications in studies related to food science, plant physiology, clinical chemistry, and forensics; wherever the distributions of analytes on the tested surfaces need to be assessed.

Comparing the Performance of Raman and Near-Infrared Imaging in the Prediction of the In Vitro Dissolution Profile of Extended-Release Tablets Based on Artificial Neural Networks

In this work, the performance of two fast chemical imaging techniques, Raman and near-infrared (NIR) imaging is compared by utilizing these methods to predict the rate of drug release from sustained-release tablets. Sustained release is provided by adding hydroxypropyl methylcellulose (HPMC), as its concentration and particle size determine the dissolution rate of the drug. The chemical images were processed using classical least squares; afterwards, a convolutional neural network was applied to extract information regarding the particle size of HPMC. The chemical images were reduced to an average HPMC concentration and a predicted particle size value; these were used as inputs in an artificial neural network with a single hidden layer to predict the dissolution profile of the tablets. Both NIR and Raman imaging yielded accurate predictions. As the instrumentation of NIR imaging allows faster measurements than Raman imaging, this technique is a better candidate for implementing a real-time technique. The introduction of chemical imaging in the routine quality control of pharmaceutical products would profoundly change quality assurance in the pharmaceutical industry.

Advancing non-destructive analysis of 3D printed medicines

Pharmaceutical 3D printing (3DP) has attracted significant interest over the past decade for its ability to produce personalised medicines on demand. However, current quality control (QC) requirements for traditional large-scale pharmaceutical manufacturing are irreconcilable with the production offered by 3DP. The US Food and Drug Administration (FDA) and the UK Medicines and Healthcare Products Regulatory Agency (MHRA) have recently published documents supporting the implementation of 3DP for point-of-care (PoC) manufacturing along with regulatory hurdles. The importance of process analytical technology (PAT) and non-destructive analytical tools in translating pharmaceutical 3DP has experienced a surge in recognition. This review seeks to highlight the most recent research on non-destructive pharmaceutical 3DP analysis, while also proposing plausible QC systems that complement the pharmaceutical 3DP workflow. In closing, outstanding challenges in integrating these analytical tools into pharmaceutical 3DP workflows are discussed.

Research progress on the application of spectral imaging technology in pharmaceutical tablet analysis

Tablet as a traditional dosage form in pharmacy has the advantages of accurate dosage, ideal dissolution and bioavailability, convenient to carry and transport. The most concerned tablet quality attributes include active pharmaceutical ingredient (API) contents and polymorphic forms, components distribution, hardness, density, coating state, dissolution behavior, etc., which greatly affect the bioavailability and consistency of tablet final products. In the pharmaceutical industry, there are usually industry standard methods to analyze the tablet quality attributes. However, these methods are generally time-consuming and laborious, and lack a comprehensive understanding of the properties of tablets, such as spatial information. In recent years, spectral imaging technology makes up for the shortcomings of traditional tablet analysis methods because it provides non-contact and rich information in time and space. As a promising technology to replace the traditional tablet analysis methods, it has attracted more and more attention. The present paper briefly describes a series of spectral imaging techniques and their applications in tablet analysis. Finally, the possible application prospect of this technology and the deficiencies that need to be improved were also prospected.

Evaluation of laser direct infrared imaging for rapid analysis of pharmaceutical tablets

Vibrational spectroscopic chemical imaging is an important tool in the pharmaceutical industry for characterising the spatial distribution of components within final drug products. The applicability of these techniques is currently limited by the long data acquisition times required to obtain high-definition chemical images of a sample surface. Advancements in quantum cascade laser (QCL) technology have provided an exciting new opportunity for infrared (IR) imaging. Instead of collecting a full IR spectrum at each point, it is possible to focus on distinct spectral bands to reduce imaging data collection time. This study explores a laser direct infrared (LDIR) chemical imaging approach that couples QCL technology with rapid scanning optics to provide high-definition chemical images at an order of magnitude faster than traditional imaging techniques. The capabilities of LDIR chemical imaging were evaluated for pharmaceutical formulations and compared with other established spectroscopic chemical imaging techniques including Raman, near-infrared (NIR) and scanning electron microscopy-energy dispersive X-ray (SEM-EDX) spectroscopy with regards to data acquisition time and image quality. The study showed that LDIR imaging provided high-definition component distribution maps comparable to Raman and SEM-EDX at orders of magnitude faster in terms of time. The ability to obtain high-definition chemical images of the whole tablet surface in relatively fast time frames indicates LDIR imaging could be a promising tool in the pharmaceutical industry to rapidly characterise the size and distribution of components within tablets and could help enhance drug product manufacturing understanding.

Carbamazepine polymorphism: a re-visitation using Raman imaging

Raman imaging methods have appeared in the last years as a powerful approach to monitoring the quality of pharmaceutical compounds. Because polymorphism occurs in many crystalline pharmaceutical compounds, it is essential to monitor polymorphic transformations induced by different external stimulus, such as temperature changes, to which those compounds may be submitted. Raman imaging with k-means cluster analysis (CA) is used here as an essential technique to investigate structural and chemical transformations occurring in carbamazepine p-monoclinic (CBZ III) into carbamazepine triclinic (CBZ I) when submitted to temperatures near the melting point of CBZ III (178 °C) and CBZ I (193°C). CBZ III commercial powder and laboratorial prepared CBZ I were analyzed by differential scanning calorimetry, powder X-ray diffraction and Raman spectroscopy with variable temperature. After thermal treatment, the resultant CBZ powder was evaluated by Raman imaging, in which all imaging data was analyzed using CA. Raman imaging allowed the identification of different polymorphs of CBZ (CBZ III and CBZ I) and iminostilbene (IMS), a degradation product of CBZ, in the treated samples, depending on the heating treatment method.

Evaluation of distributional homogeneity of pharmaceutical formulation using laser direct infrared imaging

The distributional homogeneity of chemicals is a key parameter of solid pharmaceutical formulations. Indeed, it may affect the efficacy of the drug and consequently its safety. Chemical imaging offers a unique insight enabling the visualisation of the different constituents of a pharmaceutical tablet. It allows identifying ingredients poorly distributed offering the possibility to optimize the process parameters or to adapt characteristics of incoming raw materials to increase the final product quality. Among the available chemical imaging tools, Raman imaging is one of the most widely used since it offers a high spatial resolution with well-resolved peaks resulting in a high spectral specificity. However, Raman imaging suffers from sample autofluorescence and long acquisition times. Recently commercialised, laser direct infrared reflectance imaging (LDIR) is a quantum cascade laser (QCL) based imaging technique that offers the opportunity to rapidly analyse samples. In this study, a typical pharmaceutical formulation blend composed of two active pharmaceutical ingredients and three excipients was aliquoted at different mixing timepoints. The collected aliquots were tableted and analysed using both Raman and LDIR imaging. The distributional homogeneity indexes of one active ingredient image were then computed and compared. The results show that both techniques achieved similar conclusions. However, the analysis times were drastically different. While Raman imaging required a total analysis time of 4 h per tablet to obtain the distribution map of acetylsalicylic acid with a step size of 100 µm, it only took 7.5 min to achieve the same result with LDIR. The results obtained in the present study show that LDIR is a promising technique for the analysis of pharmaceutical formulations and that it could be a valuable tool when developing new pharmaceutical formulations.

Topologically directed confocal Raman imaging (TD-CRI): Advanced Raman imaging towards compositional and micromeritic profiling of a commercial tablet components

Particle size distribution (PSD), spatial location and particle cluster size of ingredients, polymorphism, compositional distribution of a pharmaceutical product are few of the most important attributes in establishing the drug release-controlling microstructural and solid state properties that would be used to (re)design or reproduce similar products. There are numerous solid-state techniques available for PSD analysis. Laser diffraction (LD) is mostly used to study PSD of raw materials. However, a constraint of LD is the interference between the active pharmaceutical ingredients (API) and excipients, where it is very challenging to measure API size in a tablet. X-ray powder diffraction (XRPD) is widely employed in establishing the polymorphism of API and excipients. This research examined a commercial osmotic tablet in terms of extracting solid state properties of API and functional excipient by Raman Imaging. Establishing repeatability, reproducibility, and sample representativeness when the samples are non-uniform and inhomogeneous necessitates multiple measurements. In such scenarios, when employing imaging-based techniques, it can be time-consuming and tedious. Advanced statistical methodologies are used to overcome these disadvantages and expedite the characterization process. Overall, this study demonstrates that Raman imaging can be employed as a non-invasive and effective offline method for assessing the solid-state characteristics of API and functional excipients in complex dosage forms like osmotic tablets.