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Rifampicin (RIF) is an antibiotic used to treat tuberculosis and leprosy. Even though RIF is a market-available drug, it has a low aqueous solubility, hindering its bioavailability. Among the strategies for bioavailability improvement of poorly soluble drugs, coamorphous systems have been revealed as an alternative in the increase of the aqueous solubility of drug systems and at the same time also increasing the amorphous state stability and dissolution rate when compared with the neat drug. In this work, a new coamorphous form from RIF and tromethamine (TRIS) was synthesized by slow evaporation. Structural, electronic, and thermodynamic properties and solvation effects, as well as drug-coformer intermolecular interactions, were studied through density functional theory (DFT) calculations. Powder X-ray diffraction (PXRD) data allowed us to verify the formation of a new coamorphous. In addition, the DFT study indicates a possible intermolecular interaction by hydrogen bonds between the available amino and carbonyl groups of RIF and the hydroxyl and amino groups of TRIS. The theoretical spectra obtained are in good agreement with the experimental data, suggesting the main interactions occurring in the formation of the coamorphous system. PXRD was used to study the physical stability of the coamorphous system under accelerated ICH conditions (40 °C and 75% RH), indicating that the material remained in an amorphous state up to 180 days. The thermogravimetry result of this material showed a good thermal stability up to 153 °C, and differential scanning calorimetry showed that the glass temperature (Tg) was at 70.0 °C. Solubility studies demonstrated an increase in the solubility of RIF by 5.5-fold when compared with its crystalline counterpart. Therefore, this new material presents critical parameters that can be considered in the development of new coamorphous formulations.

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The low solubility of active pharmaceutical ingredients (APIs) is a problem in pharmaceutical development. Several methodologies can be used to improve API solubility, including the use of eutectic systems in which one of the constituents is the API. This class of compounds is commonly called Therapeutic Deep Eutectic Systems (THEDES). THEDES has been gaining attention due to their properties such as non-toxicity, biodegradability, and being non-expensive and easy to prepare. Since the knowledge of the solid liquid diagram of the mixture and the ideal eutectic point is necessary to ascertain if a mixture is a deep eutectic or just a eutectic mixture that is liquid at ambient temperature, the systems studied in this work are called Therapeutic Liquid Eutectic Systems (THELES). Therefore, the strategy proposed in this work is to improve the solubility of chlorpropamide and tolbutamide by preparing THELES. Both APIs are sulfonylurea compounds used for the treatment of type 2 diabetes mellitus and have low solubility in water. To prepare the THELES, several coformers were tested, namely, tromethamine, L(+)-arginine, L-tryptophan, citric acid, malic acid, ascorbic acid, and p-aminobenzoic acid, in molar ratios of 1:1 and 1:2. To improve viscosity, water was added in different molar ratios to all systems. THELES were characterized by mid-infrared spectroscopy (MIR), and differential scanning calorimetry. Their viscosity, solubility, and permeability were also determined. Their stability at room temperature and 40 °C was accessed by MIR. Cytocompatibility was performed by metabolic activity and cell lysis evaluation, according to ISO10993-5:2009, and compared with the crystalline APIs. THELES with TRIS were successfully synthesized for both APIs. Results showed an increased solubility without a decrease in the permeability of the APIs in the THELES when compared with the pure APIs. The THELES were also considered stable for 8 weeks at ambient temperature. The cells studied showed that the THELES were not toxic for the cell lines used.

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In Portugal, publications with mechanochemical methods date back to 2009, with the report on mechanochemical strategies for the synthesis of metallopharmaceuticals. Since then, mechanochemical applications have grown in Portugal, spanning several fields, mainly crystal engineering and supramolecular chemistry, catalysis, and organic and inorganic chemistry. The area with the most increased development is the synthesis of multicomponent crystal forms, with several groups synthesizing solvates, salts, and cocrystals in which the main objective was to improve physical properties of the active pharmaceutical ingredients. Recently, non-crystalline materials, such as ionic liquids and amorphous solid dispersions, have also been studied using mechanochemical methods. An area that is in expansion is the use of mechanochemical synthesis of bioinspired metal-organic frameworks with an emphasis in antibiotic coordination frameworks. The use of mechanochemistry for catalysis and organic and inorganic synthesis has also grown due to the synthetic advantages, ease of synthesis, scalability, sustainability, and, in the majority of cases, the superior properties of the synthesized materials. It can be easily concluded that mechanochemistry is expanding in Portugal in diverse research areas.

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The present work presents an in-depth evaluation of continuously collected data during a twin-screw granulation and drying process performed on a continuous manufacturing line. During operation, the continuous line logs 49 univariate process variables, hence generating a large amount of data. Three identical 5-h continuous manufacturing runs were performed. Multivariate data analysis tools, more specifically latent variable modeling tools such as principal component analysis, were used to extract information from the generated data sets unveiling process trends and drifts. Furthermore, a statistical process monitoring strategy is presented. The approach is based on the application of multivariate statistical process monitoring to model the variables that remain around a steady state.

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A cocrystal of glibenclamide, an antidiabetic drug classified as type II compound according to the Biopharmaceutics Classification System, has been synthesized using tromethamine as coformer in 1:1 molar ratio, by slow solvent evaporation cocrystalization. The cocrystal obtained was characterized by X-ray powder diffraction, differential scanning calorimetry, Raman, mid infrared, and near-infrared spectroscopy. The results consistently show the formation of a cocrystal between active pharmaceutical ingredients and conformer with the synthons corresponding to hydrogen bonding between hydrogen in amines of tromethamine and carbonyl and sulfonyl groups in glibenclamide.

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Cocrystals are defined as crystalline structures composed of two or more compounds that are solid at room temperature held together by noncovalent bonds. Their main advantages are the increase of solubility, bioavailability, permeability, stability, and at the same time retaining active pharmaceutical ingredient bioactivity. The cocrystallization between furosemide and nicotinamide by solvent evaporation was monitored on-line using near-infrared spectroscopy (NIRS) as a process analytical technology tool. The near-infrared spectra were analyzed using principal component analysis. Batch statistical process monitoring was used to create control charts to perceive the process trajectory and define control limits. Normal and non-normal operating condition batches were performed and monitored with NIRS. The use of NIRS associated with batch statistical process models allowed the detection of abnormal variations in critical process parameters, like the amount of solvent or amount of initial components present in the cocrystallization.

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Cocrystals represent a class of crystalline solids consisting of two or more molecular species usually held together by non-covalent bonds. Pharmaceutical cocrystals can alter the physicochemical properties of the active pharmaceutical ingredient to improve solubility, dissolution rate, particle properties and stability. This work presents a process analytical technology (PAT) approach to monitor on-line the cocrystallization of furosemide and adenine by solvent evaporation using near infrared spectroscopy (NIRS). Furosemide and adenine were added to a small volume of methanol in a beaker and stirred on an orbital stirring table during 8h at room temperature. The on-line monitoring was performed with a FT-NIR spectrometer fitted with a reflectance fiber optic probe. Monitoring was performed with the probe tip placed 1cm above the cocrystallization medium to avoid interference with the cocrystallization process. Cocrystals were vacuum dried to remove residual solvent and characterized off-line by NIRS, MIRS, DSC and XRPD. Results demonstrate that it was possible to follow the main cocrystallization events on-line.

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Characterisation of coffee quality based on bean quality assessment is associated with the relative amount of defective beans among non-defective beans. It is therefore important to develop a methodology capable of identifying the presence of defective beans that enables a fast assessment of coffee grade and that can become an analytical tool to standardise coffee quality. In this work, a methodology for quality assessment of green coffee based on near infrared spectroscopy (NIRS) is proposed. NIRS is a green chemistry, low cost, fast response technique without the need of sample processing. The applicability of NIRS was evaluated for Arabica and Robusta varieties from different geographical locations. Partial least squares regression was used to relate the NIR spectrum to the mass fraction of defective and non-defective beans. Relative errors around 5% show that NIRS can be a valuable analytical tool to be used by coffee roasters, enabling a simple and quantitative evaluation of green coffee quality in a fast way.

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This work compares the estimation of the particle size distribution of a pharmaceutical powder using near-infrared spectroscopy (NIRS), powder flowability properties, and components concentration. The estimations were made by considering the former data blocks separately and together using a multi-block approach. The powders were based on a formulation of paracetamol as the pharmaceutical active ingredient. The reference method used to determine particle size distribution was sieving. Partial least squares methods were used to estimate the multivariate regression models, and the results were compared in terms of figures of merit. It was shown that the partial least squares methods gave similar prediction errors. Regarding the data blocks used, the NIRS block was proven the most advantageous to estimate the particle size distribution. The prediction error of the NIRS block was similar to the other data blocks with additional advantages such as less generalization problems and the possibility of its use to predict additional physical and chemical properties with an improvement to analysis time. The multi-block approach produced the worst results but nevertheless allowed a deeper understanding of the individual contributions of the data blocks in the prediction of the particle size distribution.

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The physical properties of pharmaceutical powders are of upmost importance in the pharmaceutical industry. The knowledge of their flow properties is of critical significance in operations such as blending, tablet compression, capsule filling, transportation, and in scale-up operations. Powders flow properties are measured using a number of parameters such as, angle of repose, compressibility index (Carr's index) and Hausner ratio. To estimate these properties, specific and expensive equipment with time-consuming analysis is required. Near infrared spectroscopy is a fast and low-cost analytical technique thoroughly used in the pharmaceutical industry in the quantification and qualification of products. To establish the potential of this technique to determine the parameters associated with the flow properties of pharmaceutical powders, blended powders based on paracetamol as the active pharmaceutical ingredient were constructed in pilot scale. Spectra were recorded on a Fourier-transform near infrared spectrometer in reflectance mode. The parameters studied were the angle of repose, aerated and tapped bulk density. The correlation between the reference method values and the near infrared spectrum was performed by partial least squares and optimized in terms of latent variables using cross-validation. The near infrared based properties predictions were compared with the reference methods results. Prediction errors, which varied between 2.35% for the angle of repose, 2.51% for the tapped density and 3.18% for the aerated density, show the potential of NIR spectroscopy in the determination of physical properties affecting the flowability of pharmaceutical powders.

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The performance of an activated sludge reactor can be significantly enhanced through use of continuous and real-time process-state monitoring, which avoids the need to sample for off-line analysis and to use chemicals. Despite the complexity associated with wastewater treatment systems, spectroscopic methods coupled with chemometric tools have been shown to be powerful tools for bioprocess monitoring and control. Once implemented and optimized, these methods are fast, nondestructive, user friendly, and most importantly, they can be implemented in situ, permitting rapid inference of the process state at any moment. In this work, UV-visible and NIR spectroscopy were used to monitor an activated sludge reactor using in situ immersion probes connected to the respective analyzers by optical fibers. During the monitoring period, disturbances to the biological system were induced to test the ability of each spectroscopic method to detect the changes in the system. Calibration models based on partial least squares (PLS) regression were developed for three key process parameters, namely chemical oxygen demand (COD), nitrate concentration (N-NO(3)(-)), and total suspended solids (TSS). For NIR, the best results were achieved for TSS, with a relative error of 14.1% and a correlation coefficient of 0.91. The UV-visible technique gave similar results for the three parameters: an error of approximately 25% and correlation coefficients of approximately 0.82 for COD and TSS and 0.87 for N-NO(3)(-) . The results obtained demonstrate that both techniques are suitable for consideration as alternative methods for monitoring and controlling wastewater treatment processes, presenting clear advantages when compared with the reference methods for wastewater treatment process qualification.

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