Schistosomiasis Drug Discovery in the Era of Automation and Artificial Intelligence
José Teófilo Moreira‐Filho, Arthur C. Silva, Rafael Ferreira Dantas, Bárbara Figueira Gomes, Lauro Ribeiro Souza Neto, J. Brandão-Neto, Raymond J. Owens, Nicholas Furnham, Bruno J. Neves, Floriano Paes Silva, Carolina Horta Andrade
Abstract
and affects over 200 million people worldwide. The control and treatment of this neglected tropical disease is based on a single drug, praziquantel, which raises concerns about the development of drug resistance. This, and the lack of efficacy of praziquantel against juvenile worms, highlights the urgency for new antischistosomal therapies. In this review we focus on innovative approaches to the identification of antischistosomal drug candidates, including the use of automated assays, fragment-based screening, computer-aided and artificial intelligence-based computational methods. We highlight the current developments that may contribute to optimizing research outputs and lead to more effective drugs for this highly prevalent disease, in a more cost-effective drug discovery endeavor.