The presence of drugs in the environment is a growing global concern, and selecting molecules for study is challenging. We propose a logical and integrative strategy to prioritize molecules of concern by predicting potential masses entering the environment, followed by a prioritization step. Our strategy was applied to antineoplastics with limited biodegradability, narrow therapeutic-to-dose margins, and significant ecotoxicological effects. As a case study, we used data from 2022 for cities in the Alto Tietê watershed (São Paulo, Brazil), which hosts ∼22 million people. The predicted mass (PM) of antineoplastics potentially introduced into water bodies (807 kg) was calculated using cities sales data (4609 kg), sanitation and pharmacokinetic data, and wastewater treatment plant (WWTP) removal rates obtained from EPISuite™. The prioritization involved molecules accounting for 99% of the PM, using ToxPi™ software to create a Prioritization Index (PI), rose plots, and dendrograms for risk profile evaluation. Without PM data, prioritization relies solely on intrinsic molecular characteristics. Prioritization parameters were categorized into four: Physicochemical Properties (water solubility, KOW, KOC), Environmental Fate (WWTP removal, half-lives), Effects (BCF, ecotoxicity, mutagenicity, chronic toxicity, carcinogenicity, endocrine disruption potential), and Exposure (PM). Different weights were applied to Exposure to ensure higher PM antineoplastics were prioritized without overshadowing other parameters. Obtaining a priority set with the contribution of all parameters was possible. The prioritized antineoplastics were Paclitaxel, Capecitabine, Pemetrexed, Gemcitabine, Cisplatin, 5-Fluorouracil, Mitotane, Imatinib, Cyclophosphamide, and Carboplatin. This strategy can be applied to different contexts to generate appropriate prioritization sets.
Keywords: Antineoplastics; Cytostatic drugs; Emerging contaminants; Pharmaceutical pollution; Prediction; Prioritization.
Copyright © 2024 Elsevier Ltd. All rights reserved.