RESUMO
PURPOSE: Antimalarial drug resistance is a global public health problem that leads to treatment failure. Synergistic drug combinations can improve treatment outcomes and delay the development of drug resistance. Here, we describe the implementation of a freely available computational tool, Machine Learning Synergy Predictor (MLSyPred©), to predict potential synergy in antimalarial drug combinations. METHODS: The MLSyPred© synergy prediction method extracts molecular fingerprints from the drugs' biochemical structures to use as features and also cleans and prepares the raw data. Five machine learning algorithms (Logistic Regression, Random Forest, Support vector machine, Ada Boost, and Gradient Boost) were implemented to build prediction models. Implementation and application of the MLSyPred© tool were tested using datasets from 1540 combinations of 79 drugs and compounds biologically evaluated in pairs for three strains of Plasmodium falciparum (3D7, HB3, and Dd2). RESULTS: The best prediction models were obtained using Logistic Regression for antimalarials with the strains Dd2 and HB3 (0.81 and 0.70 AUC, respectively) and Random Forest for antimalarials with 3D7 (0.69 AUC). The MLSyPred© tool yielded 45% precision for synergistically predicted antimalarial drug combinations that were annotated and biologically validated, thus confirming the functionality and applicability of the tool. CONCLUSION: The MLSyPred© tool is freely available and represents a promising strategy for discovering potential synergistic drug combinations for further development as novel antimalarial therapies.
Assuntos
Antimaláricos , Combinação de Medicamentos , Sinergismo Farmacológico , Aprendizado de Máquina , Plasmodium falciparum , Antimaláricos/farmacologia , Plasmodium falciparum/efeitos dos fármacos , Humanos , Quimioterapia Combinada , Malária Falciparum/tratamento farmacológico , Malária Falciparum/parasitologiaRESUMO
En la Academia Nacional de Medicina, el viernes 3 de febrero de 2023 se dieron cita los representantes del grupo Acuerdos Fundamentales, conformado por 14 organizaciones académicas, científicas y gremiales de la salud con la ministra de Salud y Protección Social, Dra. Carolina Corcho Mejía, con el fin de conocer la propuesta del gobierno nacional sobre la reforma al sistema de salud, y a su vez dar respuesta a las inquietudes sobre diferentes temas, para lo cual cada organización tuvo la oportunidad de intervenir.
