Combining predictive and analytical methods to elucidate pharmaceutical biotransformation in activated sludge.

Area of Science:

• Environmental Chemistry
• Microbiology
• Ecotoxicology

Background:

• Man-made chemicals, including pharmaceuticals, are widespread environmental contaminants.
• Their environmental fate and the ecological impact of biodegradation transformation products (TPs) are often poorly understood.
• Microbial communities drive biodegradation, converting pharmaceuticals into TPs that may pose ecological risks.

Purpose of the Study:

• To review existing TP identification workflows.
• To apply an updated, automated workflow for predicting and identifying TPs from pharmaceutical biodegradation in activated sludge.
• To benchmark different pathway prediction models for their utility in environmental analysis.

Main Methods:

• Review of past TP identification workflow applications.
• Application of an updated workflow to predict TPs for 42 pharmaceuticals undergoing biodegradation in activated sludge.
• Benchmarking of five pathway prediction models, including enviPath and EAWAG systems.
• Automation of previously manual steps in TP identification.

Main Results:

• Tentative identification of 79 TPs for 31 pharmaceutical compounds using the updated workflow.
• Demonstration of the enviPath prediction system's utility for generating suspect lists for screening.
• Successful automation of several manual steps in the TP identification process.
• Proposal of new strategies to enhance the accuracy of pathway prediction models.

Conclusions:

• The developed workflow effectively identifies pharmaceutical TPs in activated sludge.
• The study provides a valuable tool for environmental monitoring and risk assessment of pharmaceutical pollution.
• Benchmarking results offer insights for improving predictive models and their application in environmental studies.