AUTHOR=Moreira-Filho José T. , Silva Arthur C. , Dantas Rafael F. , Gomes Barbara F. , Souza Neto Lauro R. , Brandao-Neto Jose , Owens Raymond J. , Furnham Nicholas , Neves Bruno J. , Silva-Junior Floriano P. , Andrade Carolina H. 

TITLE=Schistosomiasis Drug Discovery in the Era of Automation and Artificial Intelligence

JOURNAL=Frontiers in Immunology

VOLUME=12

YEAR=2021

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2021.642383

DOI=10.3389/fimmu.2021.642383

ISSN=1664-3224

ABSTRACT=<p>Schistosomiasis is a parasitic disease caused by trematode worms of the genus <italic>Schistosoma</italic> 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.</p>