Advancing component-based mixture risk assessment using new approach methodologies: An environmental case study.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Advancing component-based mixture risk assessment using new approach methodologies: An environmental case study.
Συγγραφείς: Noventa S; Italian Institute for Environmental Protection and Research (ISPRA), Chioggia, 30015, Italy., Moe SJ; Norwegian Institute for Water Research (NIVA), Sognsveien 72, Oslo, 0855, Norway., Tollefsen KE; Norwegian Institute for Water Research (NIVA), Sognsveien 72, Oslo, 0855, Norway., Song Y; Norwegian Institute for Water Research (NIVA), Sognsveien 72, Oslo, 0855, Norway., Manfra L; Italian Institute for Environmental Protection and Research (ISPRA), Roma, 00144, Italy., Lillicrap A; Norwegian Institute for Water Research (NIVA), Sognsveien 72, Oslo, 0855, Norway. Electronic address: adam.lillicrap@niva.no.
Πηγή: Ecotoxicology and environmental safety [Ecotoxicol Environ Saf] 2026 Oct 01; Vol. 324, pp. 120876. Date of Electronic Publication: 2026 Oct 02.
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 7805381 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1090-2414 (Electronic) Linking ISSN: 01476513 NLM ISO Abbreviation: Ecotoxicol Environ Saf Subsets: MEDLINE
Imprint Name(s): Original Publication: Amsterdam, Netherlands : Elsevier
Ιατρικοί όροι (MeSH): Pesticides*/toxicity , Water Pollutants, Chemical*/toxicity , Environmental Monitoring*/methods, Risk Assessment/methods ; Araceae/drug effects ; Araceae/growth & development ; Complex Mixtures/toxicity ; Bayes Theorem ; High-Throughput Screening Assays ; Adverse Outcome Pathways
Περίληψη: The next-generation risk assessment vision promotes mechanism-based hazard assessment using new approach methodologies (NAMs) and the evaluation of chemical mixture exposure. Here, we present a refined component-based mixture risk assessment (CBMRA) approach that integrates a quantitative adverse outcome pathway (qAOP) framework with high-throughput screening (HTS) data. HTS data are used to identify qAOP-active chemicals in mixtures and to scale their toxic contributions based on relative potency within the qAOP applicability domain. The approach was demonstrated with an environmentally relevant case study using a previously published probabilistic Bayesian Network qAOP model from AOP-Wiki AOP#245 ("Reduction in photophosphorylation leading to growth inhibition in aquatic plants"), applied to pesticide mixtures reported in European rivers from the European Environment Agency's Pesticide Indicator Dataset (WISE Statistics - Pesticides, 1990-2021). ToxCast and Tox21 data, in silico gap-filling methods, NAM tools and expert knowledge were used to estimate pesticide relative potency and support its application within the framework. Results indicate that 43% of mixtures contained qAOP-active compounds, but cumulative concentrations remained below the threshold required to impair growth in the model species Lemna minor. Overall, the study presents a methodological framework integrating NAM concepts, existing data and tools for mechanistic mixture risk assessment. Performance depends on HTS data quality, uncertainty in the relative potency application, and qAOP relevance. Continued NAM development is expected to strengthen the scientific basis and practical relevance of NAM-based CBMRA for mechanistically informed mixture risk screening. This framework can help prioritize mixtures for further testing or refine safety factors in risk assessment.
(Copyright © 2026 The Authors. Published by Elsevier Inc. All rights reserved.)
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Contributed Indexing: Keywords: Adverse outcome pathways; Environmental monitoring data; High-throughput screening; Mixture risk assessment; New approach methodologies; Pesticides; Relative potency
Substance Nomenclature: 0 (Pesticides)
0 (Water Pollutants, Chemical)
0 (Complex Mixtures)
Entry Date(s): Date Created: 20261002 Date Completed: 20261010 Latest Revision: 20261010
Update Code: 20261011
DOI: 10.1016/j.ecoenv.2026.120876
PMID: 42826563
Βάση Δεδομένων: MEDLINE
Περιγραφή
ISSN:1090-2414
DOI:10.1016/j.ecoenv.2026.120876