Among the chemometric tools used in rational drug design, we find artificial neural network
methods (ANNs), a statistical learning algorithm similar to the human brain, to be quite powerful.
Some ANN applications use biological and molecular data of the training series that are inserted to
ensure the machine learning, and to generate robust and predictive models. In drug discovery,
researchers use this methodology, looking to find new chemotherapeutic agents for various diseases. The neglected
diseases are a group of tropical parasitic diseases that primarily affect poor countries in Africa, Asia, and South America.
Current drugs against these diseases cause side effects, are ineffective during the chronic stages of the disease, and are
often not available to the needy population, have relative high toxicity, and face developing resistance. Faced with so
many problems, new chemotherapeutic agents to treat these infections are much needed. The present review reports on
neural network research, which studies new ligands against Chagas’ disease, sleeping sickness, malaria, tuberculosis, and
leishmaniasis; a few of the neglected diseases.