Counterfeit and Substandard Test of the Antimalarial Tablet Riamet® by Means of Raman Hyperspectral Multicomponent Analysis

Spectrally Resolved and Highly Parallelized Raman Difference Spectroscopy for the Analysis of Drug-Target Interactions between the Antimalarial Drug Chloroquine and Hematin

Malaria is a severe disease caused by cytozoic parasites of the genus Plasmodium, which infiltrate and infect red blood cells. Several drugs have been developed to combat the devastating effects of malaria. Antimalarials based on quinolines inhibit the crystallization of hematin into hemozoin within the parasite, ultimately leading to its demise. Despite the frequent use of these agents, there are unanswered questions about their mechanisms of action. In the present study, the quinoline chloroquine and its interaction with the target structure hematin was investigated using an advanced, highly parallelized Raman difference spectroscopy (RDS) setup. Simultaneous recording of the spectra of hematin and chloroquine mixtures with varying compositions enabled the observation of changes in peak heights and positions based on the altered molecular structure resulting from their interaction. A shift of (-1.12 ± 0.05) cm-1 was observed in the core-size marker band ν(CαCm)asym peak position of the 1:1 chloroquine-hematin mixture compared to pure hematin. The oxidation-state marker band ν(pyrrole half-ring)sym exhibited a shift by (+0.93 ± 0.13) cm-1. These results were supported by density functional theory (DFT) calculations, indicating a hydrogen bond between the quinolinyl moiety of chloroquine and the oxygen atom of ferric protoporphyrin IX hydroxide (Fe(III)PPIX-OH). The consequence is a reduced electron density within the porphyrin moiety and an increase in its core size. This hypothesis provided further insights into the mechanism of hemozoin inhibition, suggesting chloroquine binding to the monomeric form of hematin, thereby preventing its further crystallization to hemozoin.

Isotopomeric Peak Assignment for N2O in Cross-Labeling Experiments by Fiber-Enhanced Raman Multigas Spectroscopy

Human intervention in nature, especially fertilization, greatly increased the amount of N2O emission. While nitrogen fertilizer is used to improve nitrogen availability and thus plant growth, one negative side effect is the increased emission of N2O. Successful regulation and optimization strategies require detailed knowledge of the processes producing N2O in soil. Nitrification and denitrification, the main processes responsible for N2O emissions, can be differentiated using isotopic analysis of N2O. The interplay between these processes is complex, and studies to unravel the different contributions require isotopic cross-labeling and analytical techniques that enable tracking of the labeled compounds. Fiber-enhanced Raman spectroscopy (FERS) was exploited for sensitive quantification of N2O isotopomers alongside N2, O2, and CO2 in multigas compositions and in cross-labeling experiments. FERS enabled the selective and sensitive detection of specific molecular vibrations that could be assigned to various isotopomer peaks. The isotopomers 14N15N16O (2177 cm-1) and 15N14N16O (2202 cm-1) could be clearly distinguished, allowing site-specific measurements. Also, isotopomers containing different oxygen isotopes, such as 14N14N17O, 14N14N18O, 15N15N16O, and 15N14N18O could be identified. A cross-labeling showed the capability of FERS to disentangle the contributions of nitrification and denitrification to the total N2O fluxes while quantifying the total sample headspace composition. Overall, the presented results indicate the potential of FERS for isotopic studies of N2O, which could provide a deeper understanding of the different pathways of the nitrogen cycle.

Molecular Interactions Identified by Two-Dimensional Analysis-Detailed Insight into the Molecular Interactions of the Antimalarial Artesunate with the Target Structure β-Hematin by Means of 2D Raman Correlation Spectroscopy

A thorough understanding of the interaction of endoperoxide antimalarial agents with their biological target structures is of utmost importance for the tailored design of future efficient antimalarials. Detailed insights into molecular interactions between artesunate and β-hematin were derived with a combination of resonance Raman spectroscopy, two-dimensional correlation analysis, and density functional theory calculations. Resonance Raman spectroscopy with three distinct laser wavelengths enabled the specific excitation of different chromophore parts of β-hematin. The resonance Raman spectra of the artesunate-β-hematin complexes were thoroughly analyzed with the help of high-resolution and highly sensitive two-dimensional correlation spectroscopy. Spectral changes in the peak properties were found with increasing artesunate concentration. Changes in the low-frequency, morphology-sensitive Raman bands indicated a loss in crystallinity of the drug-target complexes. Differences in the high-wavenumber region were assigned to increased distortions of the planarity of the structure of the target molecule due to the appearance of various coexisting alkylation species. Evidence for the appearance of high-valent ferryl-oxo species could be observed with the help of differences in the peak properties of oxidation-state sensitive Raman modes. To support those findings, the relaxed ground-state structures of ten possible covalent mono- and di-meso(Cm)-alkylated hematin-dihydroartemisinyl complexes were calculated using density functional theory. A very good agreement with the experimental peak properties was achieved, and the out-of-plane displacements along the lowest-frequency normal coordinates were investigated by normal coordinate structural decomposition analysis. The strongest changes in all data were observed in vibrations with a high participation of Cm-parts of β-hematin.

Investigations on the Novel Antimalarial Ferroquine in Biomimetic Solutions Using Deep UV Resonance Raman Spectroscopy and Density Functional Theory

Deep ultraviolet (DUV) resonance Raman experiments are performed, investigating the novel, promising antimalarial ferroquine (FQ). Two buffered aqueous solutions with pH values of 5.13 and 7.00 are used, simulating the acidic and neutral conditions inside a parasite's digestive vacuole and cytosol, respectively. To imitate the different polarities of the membranes and interior, the buffer's 1,4-dioxane content was increased. These experimental conditions should mimic the transport of the drug inside malaria-infected erythrocytes through parasitophorous membranes. Supporting density functional theory (DFT) calculations on the drug's micro-speciation were performed, which could be nicely assigned to shifts in the peak positions of resonantly enhanced high-wavenumber Raman signals at λ_exc = 257 nm. FQ is fully protonated in polar mixtures like the host interior and the parasite's cytoplasm or digestive vacuole (DV) and is only present as a free base in nonpolar ones, such as the host's and parasitophorous membranes. Additionally, the limit of detection (LoD) of FQ at vacuolic pH values was determined using DUV excitation wavelengths at 244 and 257 nm. By applying the resonant laser line at λ_exc = 257 nm, a minimal FQ concentration of 3.1 μM was detected, whereas the pre-resonant excitation wavelength 244 nm provides an LoD of 6.9 μM. These values were all up to one order of magnitude lower than the concentration found for the food vacuole of a parasitized erythrocyte.

A Review of Pharmaceutical Robot based on Hyperspectral Technology

The quality and safety of medicinal products are related to patients’ lives and health. Therefore, quality inspection takes a key role in the pharmaceutical industry. Most of the previous solutions are based on machine vision, however, their performance is limited by the RGB sensor. The pharmaceutical visual inspection robot combined with hyperspectral imaging technology is becoming a new trend in the high-end medical quality inspection process since the hyperspectral data can provide spectral information with spatial knowledge. Yet, there is no comprehensive review about hyperspectral imaging-based medicinal products inspection. This paper focuses on the pivotal pharmaceutical applications, including counterfeit drugs detection, active component analysis of tables, and quality testing of herbal medicines and other medical materials. We discuss the technology and hardware of Raman spectroscopy and hyperspectral imaging, firstly. Furthermore, we review these technologies in pharmaceutical scenarios. Finally, the development tendency and prospect of hyperspectral imaging technology-based robots in the field of pharmaceutical quality inspection is summarized.

Parallelized Raman Difference Spectroscopy for the Investigation of Chemical Interactions

Raman spectroscopy provides an extremely high chemical selectivity. Raman difference spectroscopy is a technique to reveal even the smallest differences that occur due to weak interactions between substances and changes in the molecular structure. To enable parallelized and highly sensitive Raman difference spectroscopy in a microtiter-array, a diffractive optical element, a lens array, and a fiber bundle were integrated into a Raman spectroscopy setup in a unique fashion. The setup was evaluated with a microtiter-array containing pyridine-water complexes, and subwavenumber changes below the spectrometer's resolution could be resolved. The spectral changes were emphasized with two-dimensional correlation analysis. Density functional theory calculation and "atoms in molecule" analysis were performed to simulate the intermolecular long-range interactions between water and pyridine molecules and to get insight into the involved noncovalent interactions, respectively. It was found that by the addition of pyridine, the energy portion of hydrogen bonds to the total complexation energy between pyridine and water reduces. These results demonstrate the unique abilities of the new setup to investigate subtle changes due to biochemically important molecular interactions and opens new avenues to perform drug binding assays and to monitor highly parallelized chemical reactions.

Extreme Point Sort Transformation Combined With a Long Short-Term Memory Network Algorithm for the Raman-Based Identification of Therapeutic Monoclonal Antibodies

Therapeutic monoclonal antibodies (mAbs) are a new generation of protein-based medicines that are usually expensive and thus represent a target for counterfeiters. In the present study, a method based on Raman spectroscopy that combined extreme point sort transformation with a long short-term memory (LSTM) network algorithm was presented for the identification of therapeutic mAbs. A total of 15 therapeutic mAbs were used in this study. An in-house Raman spectrum dataset for model training was created with 1,350 spectra. The characteristic region of the Raman spectrum was reduced in dimension and then transformed through an extreme point sort transformation into a sequence array, which was fitted for the LSTM network. The characteristic array was extracted from the sequence array using a well-trained LSTM network and then compared with standard spectra for identification. To demonstrate whether the present algorithm was better, ThermoFisher OMNIC 8.3 software (Thermo Fisher Scientific Inc., U.S.) with two matching modes was selected for comparison. Finally, the present method was successfully applied to identify 30 samples, including 15 therapeutic mAbs and 15 other injections. The characteristic region was selected from 100 to 1800 cm⁻¹ of the full spectrum. The optimized dimensional values were set from 35 to 53, and the threshold value range was from 0.97 to 0.99 for 15 therapeutic mAbs. The results of the robustness test indicated that the present method had good robustness against spectral peak drift, random noise and fluorescence interference from the measurement. The areas under the curve (AUC) values of the present method that were analysed on the full spectrum and analysed on the characteristic region by the OMNIC 8.3 software’s built-in method were 1.000, 0.678, and 0.613, respectively. The similarity scores for 15 therapeutic mAbs using OMNIC 8.3 software in all groups compared with that of the relative present algorithm group had extremely remarkable differences (p < 0.001). The results suggested that the extreme point sort transformation combined with the LSTM network algorithm enabled the characteristic extraction of the therapeutic mAb Raman spectrum. The present method is a proposed solution to rapidly identify therapeutic mAbs.

Hydrogen and C2-C6 Alkane Sensing in Complex Fuel Gas Mixtures with Fiber-Enhanced Raman Spectroscopy

Power-to-gas is a heavily discussed option to store surplus electricity from renewable sources. Part of the generated hydrogen could be fed into the gas grid and lead to fluctuations in the composition of the fuel gas. Consequently, both operators of transmission networks and end users would need to frequently monitor the gas to ensure safety as well as optimal and stable operation. Currently, gas chromatography-based analysis methods are the state of the art. However, these methods have several downsides for time-resolved and distributed application and Raman gas spectroscopy is favorable for future point-of-use monitoring. Here, we demonstrate that fiber-enhanced Raman gas spectroscopy (FERS) enables the simultaneous detection of all relevant gases, from major (methane, CH₄; hydrogen, H₂) to minor (C2-C6 alkanes) fuel gas components. The characteristic peaks of H₂ (585 cm^-1), CH₄ (2917 cm^-1), isopentane (765 cm^-1), i-butane (798 cm^-1), n-butane (830 cm^-1), n-pentane (840 cm^-1), propane (869 cm^-1), ethane (993 cm^-1), and n-hexane (1038 cm^-1) are well resolved in the broadband spectra acquired with a compact spectrometer. The fiber enhancement achieved in a hollow-core antiresonant fiber enables highly sensitive measurements with limits of detection between 90 and 180 ppm for different hydrocarbons. Both methane and hydrogen were quantified with high accuracy with average relative errors of 1.1% for CH₄ and 1.5% for H₂ over a wide concentration range. These results show that FERS is ideally suited for comprehensive fuel gas analysis in a future, where regenerative sources lead to fluctuations in the composition of gas.

Fiber-Enhanced Raman Gas Spectroscopy for the Study of Microbial Methanogenesis

Microbial methanogenesis is a key biogeochemical process in the carbon cycle that is responsible for 70% of global emissions of the potent greenhouse gas methane (CH₄). Further knowledge about microbial methanogenesis is crucial to mitigate emissions, increase climate model accuracy, or advance methanogenic biogas production. The current understanding of the substrate use of methanogenic microbes is limited, especially regarding the methylotrophic pathway. Here, we present fiber-enhanced Raman spectroscopy (FERS) of headspace gases as an alternate tool to study methanogenesis and substrate use in particular. The optical technique is nondestructive and sensitive to CH₄, hydrogen (H₂), and carbon dioxide with a large dynamic range from trace levels (demonstrated LoDs: CH₄, 3 ppm; H₂, 49 ppm) to pure gases. In addition, the portable FERS system can provide quantitative information about methanol concentration in the liquid phase of microbial cultures through headspace gas sampling (LoD 25 ppm). We demonstrate how FERS gas sensing could enable us to track substrate and product levels of microbial methanogenesis with just one instrument. The versatility of Raman gas spectroscopy could moreover help us to elucidate links between nitrogen and carbon cycle in microbial communities in the near future.

Rapid Raman Spectroscopic Analysis of Stress Induced Degradation of the Pharmaceutical Drug Tetracycline

Stress factors caused by inadequate storage can induce the unwanted degradation of active compounds in pharmaceutical formulations. Resonance Raman spectroscopy is presented as an analytical tool for rapid monitoring of small concentration changes of tetracycline and the metabolite 4˗epianhydrotetracycline. These degradation processes were experimentally induced by changes in temperature, humidity, and irradiation with visible light over a time period of up to 23 days. The excitation wavelength λ_exc = 413 nm was proven to provide short acquisition times for the simultaneous Raman spectroscopic detection of the degradation of tetracycline and production of its impurity in small sample volumes. Small concentration changes could be detected (down to 1.4% for tetracycline and 0.3% for 4-epianhydrotetracycline), which shows the potential of resonance Raman spectroscopy for analyzing the decomposition of pharmaceutical products.

Highly Sensitive Detection of the Antibiotic Ciprofloxacin by Means of Fiber Enhanced Raman Spectroscopy

Sepsis and septic shock exhibit a rapid course and a high fatality rate. Antibiotic treatment is time-critical and precise knowledge of the antibiotic concentration during the patients’ treatment would allow individual dose adaption. Over- and underdosing will increase the antimicrobial efficacy and reduce toxicity. We demonstrated that fiber enhanced Raman spectroscopy (FERS) can be used to detect very low concentrations of ciprofloxacin in clinically relevant doses, down to 1.5 µM. Fiber enhancement was achieved in bandgap shifted photonic crystal fibers. The high linearity between the Raman signals and the drug concentrations allows a robust calibration for drug quantification. The needed sample volume was very low (0.58 µL) and an acquisition time of 30 s allowed the rapid monitoring of ciprofloxacin levels in a less invasive way than conventional techniques. These results demonstrate that FERS has a high potential for clinical in-situ monitoring of ciprofloxacin levels.

Fiber-Array-Based Raman Hyperspectral Imaging for Simultaneous, Chemically-Selective Monitoring of Particle Size and Shape of Active Ingredients in Analgesic Tablets

The particle shape, size and distribution of active pharmaceutical ingredients (API) are relevant quality indicators of pharmaceutical tablets due to their high impact on the manufacturing process. Furthermore, the bioavailability of the APIs from the dosage form depends largely on these characteristics. Routinely, particle size and shape are only analyzed in the powder form, without regard to the effect of the formulation procedure on the particle characteristics. The monitoring of these parameters improves the understanding of the process; therefore, higher quality and better control over the biopharmaceutical profile can be ensured. A new fiber-array-based Raman hyperspectral imaging technique is presented for direct simultaneous in-situ monitoring of three different active pharmaceutical ingredients- acetylsalicylic acid, acetaminophen and caffeine- in analgesic tablets. This novel method enables a chemically selective, noninvasive assessment of the distribution of the active ingredients down to 1 µm spatial resolution. The occurrence of spherical and needle-like particles, as well as agglomerations and the respective particle size ranges, were rapidly determined for two commercially available analgesic tablet types. Subtle differences were observed in comparison between these two tablets. Higher amounts of acetaminophen were visible, more needle-shaped and bigger acetylsalicylic acid particles, and a higher incidence of bigger agglomerations were found in one of the analgesic tablets.