ESTiG - Dissertações de Mestrado Alunos
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- Solubility enhancement of antimalarial drugs through eutectic formationPublication . Araújo, Nathalie Ladares de; Martins, Mónia A.R.; Pinho, Simão; Ferreira, Olga; Lima, Mirela Vanin dos SantosMalaria is a potentially fatal disease transmitted by infected mosquitoes and remains a serious public health problem, especially in sub-Saharan Africa, where it causes hundreds of thousands of deaths annually. One of the main treatments for malaria involves artemisinin-based combination therapies, which have proven highly effective in controlling the disease. However, despite their crucial role in treatment, these therapies face a significant challenge due to the low water solubility of the most commonly used active pharmaceutical ingredients (APIs), such as artemisinin. This limits their absorption into the body, also reducing their therapeutic efficacy. The aim of this thesis is to explore greener solvents to enhance the solubility and bioavailability of antimalarial APIs through the formation of eutectic mixtures. Initially, the COSMO-RS predictive tool was employed to investigate the interactions between API molecules and a variety of terpenes and their mixtures. Thymol was selected based on the lower activity coefficient at infinite dilution, indicating strong interactions with the drugs. Subsequently, the solid–liquid equilibria of binary mixtures composed of thymol and artemisinin, artemether, artesunate, quinidine, tetracycline, quinine, dapsone, sulfadoxine or pyrimethamine were experimentally measured. The data revealed a significant reduction in the melting points of the APIs, particularly for artemisinin, quinidine, and quinine. Moreover, for these three systems, notable negative deviations from ideal behavior were observed, suggesting strong drug–thymol interactions. For these cases, the label "deep eutectic systems" may be appropriately applied. The measured phase diagrams were successfully modeled using the COSMO-RS approach, demonstrating excellent agreement with the experimental results and confirming the model's capability to screen and predict suitable solvent candidates for eutectic systems. The methodologies explored in this work are aligned with the principles of green chemistry, promoting more sustainable solutions for the pharmaceutical industry.
