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Parallelized Impedance-Based Platform for Continuous Dose-Response Characterization of Antischistosomal Drugs.

Paolo S RavayniaFlavio C LombardoStefan BiendlMatthias A DupuchJennifer KeiserAndreas HierlemannMario M Modena
Published in: Advanced biosystems (2020)
Schistosomiasis is an acute and chronic disease caused by tropical parasitic worms of the genus Schistosoma, which parasitizes annually over 200 million people worldwide. Screening of antischistosomal compounds is hampered by the low throughput and potential subjectivity of the visual evaluation of the parasite phenotypes, which affects the current drug assays. Here, an impedance-based platform, capable of assessing the viability of Schistosoma mansoni schistosomula exposed to drugs, is presented. This automated and parallelized platform enables unbiased and continuous measurements of dose-response relationships for more than 48 h. The platform performance is established by exposure of schistosomula to three test compounds, praziquantel, oxethazaine, and mefloquine, which are known to affect the larvae phenotypes. The system is thereafter used to investigate the response of schistosomula to methiothepine, an antipsychotic compound, which causes complex drug-induced effects. Continuous monitoring of the parasites reveals transient behavioral phenotypes and allows for extracting temporal characteristics of dose-response curves, which are essential for selecting drugs that feature high activity and fast kinetics of action. These measurements demonstrate that impedance-based detection provides a wealth of information for the in vitro characterization of candidate antischistosomals and, represents a promising tool for the identification of new lead compounds.
Keyphrases
  • drug induced
  • liver injury
  • high throughput
  • machine learning
  • adverse drug
  • deep learning
  • climate change
  • liver failure
  • healthcare
  • zika virus
  • computed tomography
  • sensitive detection