Quantitative prediction of toxicological points of departure using two-stage machine learning models: A new approach methodology (NAM) for chemical risk assessment

Journal of Hazardous Materials, Год журнала: 2025, Номер 487, С. 137071 - 137071

Опубликована: Янв. 10, 2025

Язык: Английский

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Operationalization of the safe and sustainable by design framework for chemicals and materials: challenges and proposed actions

Integrated Environmental Assessment and Management, Год журнала: 2025, Номер 21(2), С. 245 - 262

Опубликована: Янв. 6, 2025

The production and use of chemicals materials have both advantages drawbacks for human ecosystem health. This has led to a demand carefully guided, safe, sustainable innovation in the materials, taking into consideration their entire life cycle. European Commission's Joint Research Centre (JRC) released Safe Sustainable by Design (SSbD) framework, which aims support this objective. SSbD framework consists two components that are intended be iteratively implemented throughout process: (1) application design principles phase, (2) safety sustainability assessment phase. However, operationalization is currently challenging. article maps challenges proposes ways address them effectively. mapping, based on literature review stakeholder opinions, resulted 35 challenges. highest priority challenge "integration process." To begin addressing issue, recommends conducting scoping analysis define study. can achieved through implementing tiered approach aligns with objectives growing expertise comes it. second "data availability, quality uncertainty." supported using Findability, Accessibility, Interoperability, Reuse (FAIR) optimizing silico methods at early stages process. An infrastructure data communication necessary effectively engage value chain. third aspects," requires clear definition how integrate those aspects context, harmonization, as far possible, input data, assumptions, scenario construction. first step accelerating novel concept industrial practice.

Язык: Английский

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Ai-aided chronic mixture risk assessment along a small European river reveals multiple sites at risk and pharmaceuticals being the main risk drivers

Environment International, Год журнала: 2025, Номер 197, С. 109370 - 109370

Опубликована: Март 1, 2025

The vast amount of registered chemicals leads to a high diversity substances occurring in the environment and creation new outpaces chemical risk assessment as well monitoring strategies. Hence, strategies need be modified ensuring that they remain aligned with rapid development marketing substances. Here we performed longitudinal chronic mixture considering real-world case study scenario diverse anthropogenic impact types characterised by different land uses along river Central Germany. We sampled water using large-volume solid phase extraction at six selected sampling sites. Following analysis liquid chromatography-high resolution mass spectrometry, quantified 192 For 34 % them, obtained empirical effect data for freshwater organisms. Furthermore, used open-source artificial intelligence (AI) model TRIDENT predict toxicity all A multi-scenario was conducted three taxonomic groups, concentration-addition concept various hazard exposure scenarios. results showed estimates groups were considerably higher when amended from silico modelling. identified hotspots pollution our indicated fish most vulnerable group, pharmaceuticals being relevant drivers. Our exemplifies application an AI aquatic organisms combination consideration multiple scenarios may complement future

Язык: Английский

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Emission Factor Recommendation for Life Cycle Assessments with Generative AI

Environmental Science & Technology, Год журнала: 2025, Номер unknown

Опубликована: Март 21, 2025

Accurately quantifying greenhouse gas (GHG) emissions is crucial for organizations to measure and mitigate their environmental impact. Life cycle assessment (LCA) estimates the impacts throughout a product's entire lifecycle, from raw material extraction end-of-life. Measuring outside product owner's control challenging, practitioners rely on emission factors (EFs)─estimations of GHG per unit activity─to model estimate indirect impacts. However, current practice manually selecting appropriate EFs databases time-consuming error-prone requires expertise. We present an AI-assisted method leveraging natural language processing machine learning automatically recommend with human-interpretable justifications. Our algorithm can assist experts by providing ranked list or operating in fully automated manner, where top recommendation selected as final. Benchmarks across multiple real-world data sets show our recommends correct EF average precision 86.9% case shows 10 recommendations 93.1%. By streamlining selection, approach enables scalable accurate quantification emissions, supporting organizations' sustainability initiatives progress toward net-zero targets industries.

Язык: Английский

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Quantifying pesticide emissions for drift deposition in comparative risk and impact assessment

Environmental Pollution, Год журнала: 2023, Номер 342, С. 123135 - 123135

Опубликована: Дек. 11, 2023

Estimating emissions of chemical pesticides used in agriculture is an essential component evaluating the potential toxicity-related impacts on humans and ecosystems various comparative risk impact assessment frameworks, such as life cycle assessment, environmental footprinting, absolute sustainability substitution, prioritization. Emissions related to drift deposition-usually derived from experiments-can reach non-target areas, vary a function crop characteristics application technique. We derive cumulative deposition fractions for wide range experimental functions use mass-balanced approaches. clarify that require integrate underlying over relevant area correct ratio treated field arrive at overall mass deposited per unit applied pesticide. Our results show most crops, pesticide are below 0.03 (i.e. 3% mass), except grapes fruit trees, where can 5% when using canon or air blast sprayers. Notably, aerial applications soybeans result significantly higher fractions, ranging 20% 60%. Additionally, varying nozzle position lead factor five differences deposition, establishing buffer zones effectively reduce deposition. To address remaining limitations deriving we discuss possible alternative modelling proposed approach be implemented different quantitative frameworks emission estimates agricultural pesticides, support reducing pollution human health environment.

Язык: Английский

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Two-Stage Machine Learning-Based Approach to Predict Points of Departure for Human Noncancer and Developmental/Reproductive Effects

Environmental Science & Technology, Год журнала: 2024, Номер 58(35), С. 15638 - 15649

Опубликована: Май 2, 2024

Chemical points of departure (PODs) for critical health effects are crucial evaluating and managing human risks impacts from exposure. However, PODs unavailable most chemicals in commerce due to a lack vivo toxicity data. We therefore developed two-stage machine learning (ML) framework predict human-equivalent oral exposure organic based on chemical structure. Utilizing ML-based predictions structural/physical/chemical/toxicological properties OPERA 2.9 as features (Stage 1), ML models using random forest regression were trained with derived data sets general noncancer (n = 1,791) reproductive/developmental 2,228), robust cross-validation feature selection estimating generalization errors 2). These accurately predicted both effect categories cross-validation-based root-mean-squared less than an order magnitude. then applied one or 34,046 expected be the environment, revealing several thousand moderate concern hundred high at estimated median population levels. Further application can expand by orders magnitude coverage that evaluated their impacts.

Язык: Английский

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Probabilistic Reference and 10% Effect Concentrations for Characterizing Inhalation Non-cancer and Developmental/Reproductive Effects for 2,160 Substances

Environmental Science & Technology, Год журнала: 2024, Номер 58(19), С. 8278 - 8288

Опубликована: Май 2, 2024

Chemicals assessment and management frameworks rely on regulatory toxicity values, which are based points of departure (POD) identified following rigorous dose–response assessments. Yet, PODs values for inhalation exposure (i.e., reference concentrations [RfCs]) available only ∼200 chemicals. To address this gap, we applied a workflow to determine surrogate route corresponding where assessments lacking. We curated selected in vivo data from the U.S. EPA's ToxValDB adjusted reported effect chronic human equivalent benchmark (BMCh) WHO/IPCS framework. Using chemicals with existing associated found that 25th %-ile chemical's BMCh distribution (PODp25BMCh) could serve as suitable (Q2 ≥ 0.76, RSE ≤ 0.82 log10 units). approach derive PODp25BMCh 2,095 substances general non-cancer effects 638 reproductive/developmental effects, yielding total coverage 2,160 substances. From these PODp25BMCh, derived probabilistic RfCs population concentrations. With work, have expanded number available, thereby enabling much broader risk impact assessment.

Язык: Английский

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Safe and sustainable-by-design (SSbD): Calling for efficient metrics, biophysical benchmarks, and broader application

Sustainable Chemistry and Pharmacy, Год журнала: 2025, Номер 45, С. 101986 - 101986

Опубликована: Март 11, 2025

Язык: Английский

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Advancing green chemistry performance assessment: the Estée Lauder Companies’ continuing journey towards meaningful transparency

Green Chemistry, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

An enhanced green chemistry performance metric for cosmetic ingredients and formulas is presented, incorporating advanced metrics data sources. This provides formulation design teams with more precise material selection guidance analytics.

Язык: Английский

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Near-field exposures and human health impacts for organic chemicals in interior paints: A high-throughput screening

Journal of Hazardous Materials, Год журнала: 2023, Номер 465, С. 133145 - 133145

Опубликована: Дек. 12, 2023

Interior paints contain organic chemicals that might be harmful to painters and building residents. This study aims develop a high-throughput approach screen near-field human exposures health impacts related in interior paints. We developed mass balance models for both water- solvent-based paints, predicting emissions during wet dry phases. then screened risks, focusing on Sri Lanka where residential houses are frequently repainted. These accurately predict paint drying time indoor air concentrations of chemicals. Exposures painter household resident were estimated 65 water-based 26 considering 12 solvents. Chemicals concerns (CoCs) identified, maximum acceptable chemical contents (MACs) calculated. Water-based generally pose lower risks than but biocides high concern. The total impact one painting event all adults ranges from 1.5 × 10

Язык: Английский

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