Mechanochemistry in Portugal—A Step towards Sustainable Chemical Synthesis

LA/P/0140/2020 DL 57/2016 Norma transitória.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.publishersversionpublishe

Quantitative monitoring of an activated sludge reactor using on-line UV-visible and near infrared spectroscopy

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-NO3−), 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 ~25% and correlation coefficients of ~0.82 for COD and TSS and 0.87 for N-NO3−. 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.Fundação para a Ciência e Tecnologia (FCT) - PPCDT/AMB/60141/2004, bolsa de doutoramento SFRH/BD/32614/200

Solids Turn into Liquids—Liquid Eutectic Systems of Pharmaceutics to Improve Drug Solubility

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

Evaluation of green coffee beans quality using near infrared spectroscopy: A quantitative approach

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.info:eu-repo/semantics/publishedVersio

Mechanochemistry in Portugal—A Step towards Sustainable Chemical Synthesis

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

Optimization of Experimental Settings for the Assessment of Reactive Oxygen Species Production by Human Blood

The purpose of an experimental design is to improve the productivity of experimentation. It is an efficient procedure for planning experiments, so the data obtained can be analyzed to yield a valid and objective conclusion. This approach has been used as an important tool in the optimization of different analytical approaches. A D-optimal experimental design was used here, for the first time, to optimize the experimental conditions for the detection of reactive oxygen species (ROS) produced by human blood from healthy donors, a biological matrix that better resembles the physiologic environment, following stimulation by a potent inflammatory mediator, phorbol-12-myristate-13-acetate (PMA). For that purpose, different fluorescent probes were used, as 2′,7′-dichlorodihydrofluorescein diacetate (DCFH-DA), 2-[6-(4′-amino)-phenoxy-3H-xanthen-3-on-9-yl] benzoic acid (APF), and 10-acetyl-3,7-dihydroxyphenoxazine (amplex red). The variables tested were the human blood dilution, and the fluorescent probe and PMA concentrations. The experiments were evaluated using the Response Surface Methodology and the method was validated using specific compounds. This model allowed the search for optimal conditions for a set of responses simultaneously, enabling, from a small number of experiments, the evaluation of the interaction between the variables under study. Moreover, a cellular model was implemented and optimized to detect the production of ROS using a yet nonexplored matrix, which is human blood

In-depth evaluation of data collected during a continuous pharmaceutical manufacturing process : a multivariate statistical process monitoring approach

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