Multi-Endpoint Acute Toxicity Assessment of Organic Compounds Using Large-Scale Machine Learning Modeling.

In recent years, alternative animal testing methods such as computational and machine learning approaches have become increasingly crucial for toxicity testing. However, the complexity and scarcity of available biomedical data challenge the development of predictive models. Combining nonlinear machine learning together with multicondition descriptors offers a solution for using data from various assays to create a robust model. This work applies multicondition descriptors (MCDs) to develop a QSTR (Quantitative Structure-Toxicity Relationship) model based on a large toxicity data set comprising more than 80,000 compounds and 59 different end points (122,572 data points). The prediction capabilities of developed single-task multi-end point machine learning models as well as a novel data analysis approach with the use of Convolutional Neural Networks (CNN) are discussed. The results show that using MCDs significantly improves the model and using them with CNN-1D yields the best result (R2train = 0.93, R2ext = 0.70). Several structural features showed a high level of contribution to the toxicity, including van der Waals surface area (VSA), number of nitrogen-containing fragments (nN+), presence of S-P fragments, ionization potential, and presence of C-N fragments. The developed models can be very useful tools to predict the toxicity of various compounds under different conditions, enabling quick toxicity assessment of new compounds.

In Silico Acute Aquatic Hazard Assessment and Prioritization Using a Grouped Target Site Model: A Case Study of Organic Substances Reported in Permian Basin Hydraulic Fracturing Operations.

Hydraulic fracturing (HF) is commonly used to enhance onshore recovery of oil and gas during production. This process involves the use of a variety of chemicals to support the physical extraction of oil and gas, maintain appropriate conditions downhole (e.g., redox conditions, pH), and limit microbial growth. The diversity of chemicals used in HF presents a significant challenge for risk assessment. The objective of the present study is to establish a transparent, reproducible procedure for estimating 5th percentile acute aquatic hazard concentrations (e.g., acute hazard concentration 5th percentiles [HC5s]) for these substances and validating against existing toxicity data. A simplified, grouped target site model (gTSM) was developed using a database (n = 1696) of diverse compounds with known mode of action (MoA) information. Statistical significance testing was employed to reduce model complexity by combining 11 discrete MoAs into three general hazard groups. The new model was trained and validated using an 80:20 allocation of the experimental database. The gTSM predicts toxicity using a combination of target site water partition coefficients and hazard group-based critical target site concentrations. Model performance was comparable to the original TSM using 40% fewer parameters. Model predictions were judged to be sufficiently reliable and the gTSM was further used to prioritize a subset of reported Permian Basin HF substances for risk evaluation. The gTSM was applied to predict hazard groups, species acute toxicity, and acute HC5s for 186 organic compounds (neutral and ionic). Toxicity predictions and acute HC5 estimates were validated against measured acute toxicity data compiled for HF substances. This case study supports the gTSM as an efficient, cost-effective computational tool for rapid aquatic hazard assessment of diverse organic chemicals. Environ Toxicol Chem 2024;43:1161-1172. © 2024 ExxonMobil Petroleum and Chemical BV. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Data driven toxicity assessment of organic chemicals against Gammarus species using QSAR approach.

Nowadays, organic chemicals play an essential role in almost all walks of life and have become indispensable to modern society. However, the continually synthesized chemicals and the numerous potential adverse endpoints against living organisms increasingly promote the regulators regarding the computational approach as a crucial supplement and an alternative to the traditional animal tests in chemical risk assessment. In this present research, we evaluated the ecotoxicity of chemicals against four typical Gammarus species, which constituted a critical element in detritus cycle and also the recommended species for water monitoring. We first screened the molecular descriptors based on the Genetic Algorithm and then developed the Quantitative Structure-Activity Relationship models using the Multiple Linear Regression method. The statistical results from various validation metrics suggested that the obtained models were internally robust and externally predictive. The application domain analysis based on the leverage approach and standardized residual method demonstrated the broad application range of each model. The interpretation of molecular descriptors in each model suggested that the chemicals with higher polarity and hydrophilicity tend to be less toxic, whereas the lipophilic moieties would enhance the chemical toxicity. Meanwhile, the other selected descriptors, such as Chi-cluster, heterocyclic, and distance matrix descriptors, manifested that the chemical toxicity was also affected by molecular branching, connectivity, electrotopological state, and other various properties. In summary, the present work proposed well-performed QSAR models and clarified the possible toxic mechanism of chemicals against Gammarus species. The obtained models could help predict the toxicity data and conduct a preliminary risk assessment, thus guiding the subsequent animal tests and reducing the assessment cost.

Quasi-SMILES: Self-consistent models for toxicity of organic chemicals to tadpoles.

Simplified molecular input-line entry systems (SMILES) are the representation of the molecular structure that can be used to establish quantitative structure-property/activity relationships (QSPRs/QSARs) for various endpoints expressed as mathematical functions of the molecular architecture. Quasi-SMILES is extending the traditional SMILES by means of additional symbols that reflect experimental conditions. Using the quasi-SMILES models of toxicity to tadpoles gives the possibility to build up models by taking into account the time of exposure. Toxic effects of experimental situations expressed via 188 quasi-SMILES (the negative logarithm of molar concentrations which lead to lethal 50% tadpoles effected during 12 h, 24 h, 48 h, 72 h, and 96 h) were modelled with good results (the average determination coefficient for the validation sets is about 0.97). In this way, we developed new models for this amphibian endpoint, which is poorly studied.

Mixture Risk Assessment of Complex Real-Life Mixtures-The PANORAMIX Project.

Humans are involuntarily exposed to hundreds of chemicals that either contaminate our environment and food or are added intentionally to our daily products. These complex mixtures of chemicals may pose a risk to human health. One of the goals of the European Union's Green Deal and zero-pollution ambition for a toxic-free environment is to tackle the existent gaps in chemical mixture risk assessment by providing scientific grounds that support the implementation of adequate regulatory measures within the EU. We suggest dealing with this challenge by: (1) characterising 'real-life' chemical mixtures and determining to what extent they are transferred from the environment to humans via food and water, and from the mother to the foetus; (2) establishing a high-throughput whole-mixture-based in vitro strategy for screening of real-life complex mixtures of organic chemicals extracted from humans using integrated chemical profiling (suspect screening) together with effect-directed analysis; (3) evaluating which human blood levels of chemical mixtures might be of concern for children's development; and (4) developing a web-based, ready-to-use interface that integrates hazard and exposure data to enable component-based mixture risk estimation. These concepts form the basis of the Green Deal project PANORAMIX, whose ultimate goal is to progress mixture risk assessment of chemicals.

Mutagenicity, health risk, and disease burden of exposure to organic micropollutants in water from a drinking water treatment plant in the Yangtze River Delta, China.

A wide variety of organic micropollutants in drinking water pose a serious threat to human health. This study was aimed to reveal the characteristics of organic micropollution profiles in water from a drinking water treatment plant (DWTP) in the Yangtze River Delta, China and investigate the mutagenicity, health risk and disease burden through mixed exposure to micropollutants in water. The presence of organic micropollutants in seven categories in organic extracts (OEs) of water from the DWTP was determined, and Ames test was conducted to test the mutagenic effect of OEs. Meanwhile, health risk of exposure to organic micropollutants in finished water through three exposure routes (ingestion, dermal absorption and inhalation) was assessed with the method proposed by U.S. EPA, and disability-adjusted life years (DALYs) were combined to estimate the disease burden of cancer based on the carcinogenic risk (CR) assessment. The results showed that 28 organic micropollutants were detected in the raw and finished water at total concentrations of 967.28 ng/L and 1073.45 ng/L, respectively, of which phthalate esters (PAEs) were the dominant category (95.79% in the raw water and 96.61% in the finished water). Although the results of the Ames test for OEs were negative and the non-carcinogenic hazard index of the organic micropollutants in the finished water was less than 1 in all age groups, the total CR was 2.17 × 10-5, higher than the negligible risk level (1.00 × 10-6). The total DALYs caused by the organic micropollutants in the finished water was 2945.59 person-years, and the average individual DALYs was 2.21 × 10-6 per person-year (ppy), which was 2.21 times the reference risk level (1.00 × 10-6 ppy) defined by the WHO. Exposure to nitrosamines (NAms) was the major contributor to the total CR (92.06%) and average individual DALYs (94.58%). This study demonstrated that despite the negative result of the mutagenicity test with TA98 and TA100 strains, the health risk of exposure to organic micropollutants in drinking water should not be neglected.

Relevance of In Vitro Transcriptomics for In Vivo Mode of Action Assessment.

Recently, we reported an in vitro toxicogenomics comparison approach to categorize chemical substances according to similarities in their proposed toxicological modes of action. Use of such an approach for regulatory purposes requires, among others, insight into the extent of biological concordance between in vitro and in vivo findings. To that end, we applied the comparison approach to transcriptomics data from the Open TG-GATEs database for 137 substances with diverging modes of action and evaluated the outcomes obtained for rat primary hepatocytes and for rat liver. The results showed that a relatively small number of matches observed in vitro were also observed in vivo, whereas quite a large number of matches between substances were found to be relevant solely in vivo or in vitro. The latter could not be explained by physicochemical properties, leading to insufficient bioavailability or poor water solubility. Nevertheless, pathway analyses indicated that for relevant matches the mechanisms perturbed in vitro are consistent with those perturbed in vivo. These findings support the utility of the comparison approach as tool in mechanism-based risk assessment.

Solvothermal synthesis of facet-dependent BiVO4 photocatalyst with enhanced visible-light-driven photocatalytic degradation of organic pollutant: assessment of toxicity by zebrafish embryo.

The BiVO4 photocatalyst plays a very important role in photocatalytic reactions attributed to its unique crystalline structure, size, morphology and surface area. Herein, we report a facet-dependent monoclinic scheelite BiVO4 (m-BiVO4) photocatalyst with uniform truncated square (18 sided) hexagonal bipyramidal shape synthesized by a template-free and surfactant-free solvothermal method using ethylene glycol solvent under cost-effective and mild reactions. The structural, morphological and optical properties of the m-BiVO4 photocatalyst are widely characterized. The photocatalytic activity of the m-BiVO4 photocatalyst is tested towards 20 ppm methylene blue (MB) dye aqueous solution as a pollutant model under visible light irradiation. Enhanced visible-light driven photoactivity with dye degradation efficiency of approx. 91% at a rate of 0.388 × 10-2 min-1 is obtained, presumably due to the presence of high-active (040) facets. Zebrafish embryo toxicity test of treated MB dye solution reveals the degradation and toxicity reduction of the MB dye. Moreover, the recycling experiment validates that the m-BiVO4 photocatalyst has a great structural stability with reliable performance. This work may provide a lucid and expedient strategy to synthesize highly crystalline (040) facet-dependent semiconductor photocatalyst toward dye degradation and obviously industrial wastewater remediation.

Experimental Exposure Assessment of Ionizable Organic Chemicals in In Vitro Cell-Based Bioassays.

Exposure assessment in in vitro cell-based bioassays is challenging for ionizable organic chemicals (IOCs), because they are present as more than one chemical species in the bioassay medium. Furthermore, compared to neutral organic chemicals, their binding to medium proteins and lipids is driven by more complex molecular interactions. Total medium concentrations (Ctotal,medium) and/or freely dissolved medium concentrations (Cfree,medium) were determined for one neutral chemical and 14 IOCs (acids, bases, multifunctional) at concentrations relevant for determination of cytotoxicity and effect. Cfree,medium was measured in two in vitro bioassays at the time of dosing and after 24 h of incubation using solid-phase microextraction. Cfree,medium was maximally 1.7 times lower than the nominal concentrations (Cnom) for the hydrophilic chemicals (caffeine and lamotrigine). For the organic acids (naproxen, ibuprofen, warfarin, and diclofenac), Cfree,medium was by a factor of 4 lower than Cnom at high concentrations, but the ratio was much higher at low concentrations, indicating a nonlinear binding behavior. The experimental Cfree,medium was also compared with Cfree,medium predicted with a mass balance model accounting for binding to medium proteins and lipids. The mass balance model performed well for five of the test chemicals (within a factor of 10), but it underestimated Cfree,medium by up to a factor of 1200 for chemicals that showed nonlinear binding to medium components. These findings emphasize that experimental exposure assessment is required for improved understanding of in vitro toxicity data.

Clustering a Chemical Inventory for Safety Assessment of Fragrance Ingredients: Identifying Read-Across Analogs to Address Data Gaps.

A valuable approach to chemical safety assessment is the use of read-across chemicals to provide safety data to support the assessment of structurally similar chemicals. An inventory of over 6000 discrete organic chemicals used as fragrance materials in consumer products has been clustered into chemical class-based groups for efficient search of read-across sources. We developed a robust, tiered system for chemical classification based on (1) organic functional group, (2) structural similarity and reactivity features of the hydrocarbon skeletons, (3) predicted or experimentally verified Phase I and Phase II metabolism, and (4) expert pruning to consider these variables in the context of specific toxicity end points. The systematic combination of these data yielded clusters, which may be visualized as a top-down hierarchical clustering tree. In this tree, chemical classes are formed at the highest level according to organic functional groups. Each subsequent subcluster stemming from classes in this hierarchy of the cluster is a chemical cluster defined by common organic functional groups and close similarity in the hydrocarbon skeleton. By examining the available experimental data for a toxicological endpoint within each cluster, users can better identify potential read-across chemicals to support safety assessments.

A Toxicokinetic Framework and Analysis Tool for Interpreting Organisation for Economic Co-operation and Development Guideline 305 Dietary Bioaccumulation Tests.

The Organisation for Economic Co-operation and Development guideline 305 for bioaccumulation testing in fish includes the option to conduct a dietary test for assessing a chemical's bioaccumulation behavior. However, the one-compartment toxicokinetic model that is used in the guidelines to analyze the results from dietary bioaccumulation tests is not consistent with the current state of the science, experimental practices, and information needs for bioaccumulation and risk assessment. The present study presents 1) a 2-compartment toxicokinetic modeling framework for describing the bioaccumulation of neutral hydrophobic organic chemicals in fish and 2) an associated toxicokinetic analysis tool (absorption, distribution, metabolism, and excretion [ADME] B calculator) for the analysis and interpretation of dietary bioaccumulation test data from OECD-305 dietary tests. The model framework and ADME-B calculator are illustrated by analysis of fish dietary bioaccumulation test data for 238 substances representing different structural classes and susceptibilities to biotransformation. The ADME of the chemicals is determined from dietary bioaccumulation tests and bioconcentration factors, biomagnification factors, and somatic and intestinal biotransformation rates. The 2-compartment fish toxicokinetic model can account for the effect of the exposure pathway on bioaccumulation, which the one-compartment model cannot. This insight is important for applying a weight-of-evidence approach to bioaccumulation assessment where information from aqueous and dietary test endpoints can be integrated to improve the evaluation of a chemical's bioaccumulation potential. Environ Toxicol Chem 2019;39:171-188. © 2019 SETAC.

Recommendations for Improving Methods and Models for Aquatic Hazard Assessment of Ionizable Organic Chemicals.

Ionizable organic chemicals (IOCs) such as organic acids and bases are an important substance class requiring aquatic hazard evaluation. Although the aquatic toxicity of IOCs is highly dependent on the water pH, many toxicity studies in the literature cannot be interpreted because pH was not reported or not kept constant during the experiment, calling for an adaptation and improvement of testing guidelines. The modulating influence of pH on toxicity is mainly caused by pH-dependent uptake and bioaccumulation of IOCs, which can be described by ion-trapping and toxicokinetic models. The internal effect concentrations of IOCs were found to be independent of the external pH because of organisms' and cells' ability to maintain a stable internal pH milieu. If the external pH is close to the internal pH, existing quantitative structure-activity relationships (QSARs) for neutral organics can be adapted by substituting the octanol-water partition coefficient by the ionization-corrected liposome-water distribution ratio as the hydrophobicity descriptor, demonstrated by modification of the target lipid model. Charged, zwitterionic and neutral species of an IOC can all contribute to observed toxicity, either through concentration-additive mixture effects or by interaction of different species, as is the case for uncoupling of mitochondrial respiration. For specifically acting IOCs, we recommend a 2-step screening procedure with ion-trapping/QSAR models used to predict the baseline toxicity, followed by adjustment using the toxic ratio derived from in vitro systems. Receptor- or plasma-binding models also show promise for elucidating IOC toxicity. The present review is intended to help demystify the ecotoxicity of IOCs and provide recommendations for their hazard and risk assessment. Environ Toxicol Chem 2020;39:269-286. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Idealization of correlations between optimal simplified molecular input-line entry system-based descriptors and skin sensitization.

The Index of Ideality of Correlation (IIC) is a new criterion of the predictive potential for quantitative structure-property/activity relationships. The value of the IIC is a mathematical function sensitive to the value of the correlation coefficient and dispersion (expressed via mean absolute error). The IIC has been applied to develop QSAR models for skin sensitization achieving good predictive potential. The 'ideal correlation' is based on elementary fragments of simplified molecular input-line entry system (SMILES) and on the taking into account of the total numbers of nitrogen, oxygen, sulphur and phosphorus in the molecule.

Insight into removal of dissolved organic matter in post pharmaceutical wastewater by coagulation-UV/H2O2.

The removal of four dissolved organic matter (DOM) fractions, non-acid hydrophobics, hydrophobic acids, hydrophilics and transphilics, was achieved by coagulation-UV/H2O2 oxidation in post-pharmaceutical wastewater (PhWW). Coagulation with Polyferric chloride (PFC), Polymeric ferric sulfate (PFS) and Polymeric aluminum ferric chloride (PAFC) was studied separately to evaluate the effects of the initial pH and coagulant dosage. The coagulation-UV/H2O2 oxidation method resulted in much higher reduction rates for dissolved organic carbon (DOC) (by 75%) and UV254 (by 92%) than coagulation or UV/H2O2 oxidation alone. The proportion of non-acid hydrophobics, hydrophobic acids, transphilics and hydrophilics removed by coagulation was 54%, 49%, 27% and 12 %, while the combined treatment removed 92%, 87%, 70% and 39%, respectively. Parallel factor analysis (PARAFAC) of fluorescence measurements revealed that the humic-like fluorescent component C4 showed the highest removal (by 44%) during the coagulation stage. After coagulation-UV/H2O2 treatment, the humic-like fluorescent component C3 had the highest removal (by 72%), whereas xenobiotic organic fluorescent components C1 and C4 remained recalcitrant to decomposition. Significant correlations (R2 > 0.8) between C1 and the hydrophobic acids and non-acid hydrophobics suggested the possibility of using fluorescence spectroscopy as an effective tool to assess variations in DOM fraction treatment efficacy in coagulation-UV/H2O2 systems. After the combined treatment, toxic inhibition of cellular activity by post PhWW decreased from 88% to 47% and biodegradability increased from 0.1 to 0.52.

Persistent organic pollutants, pesticides, and the risk of thyroid cancer: systematic review and meta-analysis.

Previous epidemiological studies have reported persistent organic pollutants (POPs) and some nonpersistent pesticides and the risk of thyroid cancer. The aim of this study was to assess the association between exposure to POPs, pesticides, and thyroid cancer by carrying out a meta-analysis. Literature searches were performed using PubMed, Embase, and reference lists of relevant articles. Summary risk estimates for thyroid cancer were calculated using fixed-effects and random-effects models. In addition, several subgroup and sensitivity analyses were carried out. Fifteen studies were reviewed, and eight studies were included in the meta-analysis. Pesticide exposure showed positive, statistically significant associations with thyroid cancer [odds ratio (OR)=1.48, 95% confidence interval (CI)=1.15-1.91, I=48%, Pheterogenetiy=0.05]. After subgroup analysis, herbicide exposure (OR=3.00, 95% CI=1.38-6.54) and agricultural exposure to pesticides (OR=1.86, 95% CI=1.04-3.32) was associated with an increased risk of thyroid cancer. A sensitivity analysis showed that the results were robust. Exposure to pesticides was associated with an increased risk of thyroid cancer in this meta-analysis. Future studies should investigate exposure to POPs or pesticides with controls for potential confounders using biological samples.

Toxicity assessment of sediments from the Liaohe River Protected Area (China) under the influence of ammonia nitrogen, heavy metals and organic contaminants.

The aim of this study was to evaluate the toxicity of ammonia nitrogen, metals and organic contaminants in sediment collected from the Liaohe River Protected Areas. The TIE was applied to 16 samples. The zeolite, resin, and coconut charcoal were used to mask toxicity of the three kinds of pollutants, respectively. Then quantitative analyses together with a battery of bioassays were performed to evaluate toxic effects. At last, the spiking tests were used to confirm the major contributors to toxicity. The results of toxicity identification showed the ammonia nitrogen, γ-HCHs, As and Cd may cause toxic hazards to benthic organisms. The significant correlation between the survival and volume ratio of the sediment and overlying water confirmed ammonia nitrogen and Cd were the major toxic pollutants that cause the biological toxicity. We confirmed bioassays combined with masking agent, spiking tests and quantitative analyses were suitable tools for detecting toxicity.

Accelerating the Pace of Chemical Risk Assessment.

Changes in chemical regulations worldwide have increased the demand for new data on chemical safety. New approach methodologies (NAMs) are defined broadly here as including in silico approaches and in chemico and in vitro assays, as well as the inclusion of information from the exposure of chemicals in the context of hazard [European Chemicals Agency, " New Approach Methodologies in Regulatory Science ", 2016]. NAMs for toxicity testing, including alternatives to animal testing approaches, have shown promise to provide a large amount of data to fill information gaps in both hazard and exposure. In order to increase experience with the new data and to advance the applications of NAM data to evaluate the safety of data-poor chemicals, demonstration case studies have to be developed to build confidence in their usability. Case studies can be used to explore the domains of applicability of the NAM data and identify areas that would benefit from further research, development, and application. To ensure that this science evolves with direct input from and engagement by risk managers and regulatory decision makers, a workshop was convened among senior leaders from international regulatory agencies to identify common barriers for using NAMs and to propose next steps to address them. Central to the workshop were a series of collaborative case studies designed to explore areas where the benefits of NAM data could be demonstrated. These included use of in vitro bioassays data in combination with exposure estimates to derive a quantitative assessment of risk, use of NAMs for updating chemical categorizations, and use of NAMs to increase understanding of exposure and human health toxicity of various chemicals. The case study approach proved effective in building collaborations and engagement with regulatory decision makers and to promote the importance of data and knowledge sharing among international regulatory agencies. The case studies will be continued to explore new ways of describing hazard (i.e., pathway perturbations as a measure of adversity) and new ways of describing risk (i.e., using NAMs to identify protective levels without necessarily being predictive of a specific hazard). Importantly, the case studies also highlighted the need for increased training and communication across the various communities including the risk assessors, regulators, stakeholders (e.g., industry, non-governmental organizations), and the general public. The development and application of NAMs will play an increasing role in filling important data gaps on the safety of chemicals, but confidence in NAMs will only come with learning by doing and sharing in the experience.

Environmental risk assessment of selected organic chemicals based on TOC test and QSAR estimation models.

Environmental risks of organic chemicals have been greatly determined by their persistence, bioaccumulation, and toxicity (PBT) and physicochemical properties. Major regulations in different countries and regions identify chemicals according to their bioconcentration factor (BCF) and octanol-water partition coefficient (Kow), which frequently displays a substantial correlation with the sediment sorption coefficient (Koc). Half-life or degradability is crucial for the persistence evaluation of chemicals. Quantitative structure activity relationship (QSAR) estimation models are indispensable for predicting environmental fate and health effects in the absence of field- or laboratory-based data. In this study, 39 chemicals of high concern were chosen for half-life testing based on total organic carbon (TOC) degradation, and two widely accepted and highly used QSAR estimation models (i.e., EPI Suite and PBT Profiler) were adopted for environmental risk evaluation. The experimental results and estimated data, as well as the two model-based results were compared, based on the water solubility, Kow, Koc, BCF and half-life. Environmental risk assessment of the selected compounds was achieved by combining experimental data and estimation models. It was concluded that both EPI Suite and PBT Profiler were fairly accurate in measuring the physicochemical properties and degradation half-lives for water, soil, and sediment. However, the half-lives between the experimental and the estimated results were still not absolutely consistent. This suggests deficiencies of the prediction models in some ways, and the necessity to combine the experimental data and predicted results for the evaluation of environmental fate and risks of pollutants.

Can the Stockholm convention address the spectrum of chemicals currently under regulatory scrutiny? Advocating a more prominent role for modeling in POP screening assessment.

Frameworks for chemical regulation are based on the science at the time they were written. Today some regulations are being applied to a much broader spectrum of chemicals than we had knowledge of when the regulations were written. This entails a risk that the regulations are being used outside of their chemical application domain. This question is explored using the POP screening assessment in the Stockholm convention, which was developed 20 years ago. Using perfluorinated alkyl acids (PFAAs) as an example, it is shown that the assessment can lead to false negative conclusions. A second case study using octamethylcyclotetrasiloxane (D4) illustrates that there is also a risk of false positives. The risk for false negative classification of PFAAs is due to the inclusion of a screening criterion - bioaccumulation - that is not a requirement for adverse effects of chemicals in remote regions. For D4 the risk of false positive classification stems from the four screening criteria (persistence, bioaccumulation, long-range transport, and adverse effects) applying to different environmental media/compartments. The major lesson is that applying the POP screening procedure to the broad spectrum of chemicals in modern commerce will require that we rely less on the individual screening criteria and more on the comparison of estimated exposure and the thresholds for effects stipulated in Annex D, paragraph 2 of the convention. Models have an important role to play in this context and should become more strongly integrated into the POP screening process.