PARC researchers have unveiled a groundbreaking high-throughput method for identifying chemical risk drivers in wastewater, offering significant advancements in both human health surveillance and environmental exposure assessment.

The development and use of effect-directed analysis (EDA) for the identification of risk drivers is a key requirement for monitoring, assessment and mitigation of chemical pollution. Although in individual cases very successful, the broad application of EDA in monitoring is hampered by high complexity and low throughput.

Led by Werner Brack, Professor at the Helmholtz Centre for Environmental Research (UFZ), this research project developed an innovative High-Throughput Effect-Directed Analysis (HT-EDA) approach.  

This method represents a significant leap beyond traditional effect-directed analysis (EDA), combining HT fractionation into microtiter plates for in vitro biotesting with HPLC-HRMS analysis using a high-throughput automated workflow for non-target screening including semi-quantification and the prioritization of effect-drivers in NTS data using supervised-machine-learning based toxicity prediction. The novel approach has been demonstrated for the identification of androgenic risk drivers in hospital wastewater.  

Exploiting the complementary expertise of PARC partners, this work opens new perspectives for risk driver identification in waste and surface water monitoring, as well as being applicable to many other toxicological endpoints” as highlights Werner Brack.