Automated read-across workflow for predicting acute oral toxicity: I. The decision scheme in the QSAR toolbox

A decision-scheme outlining the steps for identifying the appropriate chemical category and subsequently appropriate tested source analog(s) for data gap filling of a target chemical by read-across is described. The primary features used in the grouping of the target chemical with source analogues within a database of 10,039 discrete organic substances include reactivity mechanisms associated with protein interactions and specific-acute-oral-toxicity-related mechanisms (e.g., mitochondrial uncoupling). Additionally, the grouping of chemicals making use of the in vivo rat metabolic simulator and neutral hydrolysis. Subsequently, a series of structure-based profilers are used to narrow the group to the most similar analogues. The scheme is implemented in the OECD QSAR Toolbox, so it automatically predicts acute oral toxicity as the rat oral LD50 value in log [1/mol/kg]. It was demonstrated that due to the inherent variability in experimental data, classification distribution should be employed as more adequate in comparison to the exact classification. It was proved that the predictions falling in the adjacent GSH categories to the experimentally-stated ones are acceptable given the variation in experimental data. The model performance estimated by adjacent accuracy was found to be 0.89 and 0.54 while based on R². The mechanistic and predictive coverages were >0.85.

Computational material flow analysis for thousands of chemicals of emerging concern in European waters

Knowledge of exposure to a wide range of chemicals, and the spatio-temporal variability thereof, is urgently needed in the context of protecting and restoring aquatic ecosystems. This paper discusses a computational material flow analysis to predict the occurrence of thousands of man-made organic chemicals on a European scale, based on a novel temporally and spatially resolved modelling framework. The goal was to increase understanding of pressures by emerging chemicals and to complement surface water monitoring data. The ambition was to provide a first step towards a "real-life" mixture exposure situation accounting for as many chemicals as possible. Comparison of simulated concentrations and chemical monitoring data for 226 substance/basin combinations showed that the simulated concentrations were accurate on average. For 65% and 90% of substance/basin combinations the error was within one and two orders of magnitude respectively. An analysis of the relative importance of uncertainties revealed that inaccuracies in use volume or use type information contributed most to the error for individual substances. To resolve this, we suggest better registration of use types of industrial chemicals, investigation of presence/absence of industrial chemicals in wastewater and runoff samples and more scientific information exchange.

Exposure and ecotoxicological risk assessment of mixtures of top prescribed pharmaceuticals in Swedish freshwaters

Surface water concentrations of 54 pharmaceuticals were predicted for seven major Swedish rivers and the Stockholm City area basins using the STREAM-EU model. These surface water concentrations were used to predict the ecotoxicological impact resulting from the exposure of aquatic organisms to this mixture of 54 pharmaceuticals. STREAM-EU model results indicated that <10 substances were present at median annual water concentrations greater than 10 ng/L with highest concentrations occurring mostly in the more densely populated area of the capital city, Stockholm. There was considerable spatial and temporal variability in the model predictions (1-3 orders of magnitude) due to natural variability (e.g. hydrology, temperature), variations in emissions and uncertainty sources. Local mixture ecotoxicological pressures based on acute EC50 data as well as on chronic NOEC data, expressed as multi-substance potentially affected fraction of species (msPAF), were quantified in 114 separate locations in the waterbodies. It was estimated that 5% of the exposed aquatic species would experience exposure at or above their acute EC50 concentrations (so-called acute hazardous concentration for 5% of species, or aHC5) at only 7% of the locations analyzed (8 out of 114 locations). For the evaluation based on chronic NOEC concentrations, the chronic HC5 (cHC5) is exceeded at 27% of the locations. The acute mixture toxic pressure was estimated to be predominantly caused by only three substances in all waterbodies: Furosemide, Tramadol and Ibuprofen. A similar evaluation of chronic toxic pressure evaluation logically demonstrates that more substances play a significant role in causing a higher chronic toxic pressure at more sites as compared to the acute toxic pressure evaluation. In addition to the three substances contributing most to acute effects, the chronic effects are predominantly caused by another five substances: paracetamol, diclofenac, ethinylestradiol, erythromycin and ciprofloxacin. This study provides regulatory authorities and companies responsible for water quality valuable information for targeting remediation measures and monitoring on a substance and location basis.

Model-predicted occurrence of multiple pharmaceuticals in Swedish surface waters and their flushing to the Baltic Sea

An exposure assessment for multiple pharmaceuticals in Swedish surface waters was made using the STREAM-EU model. Results indicate that Metformin (27 ton/y), Paracetamol (6.9 ton/y) and Ibuprofen (2.33 ton/y) were the drugs with higher amounts reaching the Baltic Sea in 2011. 35 of the studied substances had more than 1 kg/y of predicted flush to the sea. Exposure potential given by the ratio amount of the drug exported to the sea/amount emitted to the environment was higher than 50% for 7 drugs (Piperacillin, Lorazepam, Metformin, Hydroxycarbamide, Hydrochlorothiazide, Furosemide and Cetirizine), implying that a high proportion of them will reach the sea, and below 10% for 27 drugs, implying high catchment attenuation. Exposure potentials were found to be dependent of persistency and hydrophobicity of the drugs. Chemicals with Log D > 2 had exposure potentials <10% regardless of their persistence. Chemicals with Log D  <  -2 had exposure potentials >35% with higher ratios typically achieved for longer half-lives. For Stockholm urban area, 17 of the 54 pharmaceuticals studied had calculated concentrations higher than 10 ng/L. Model agreement with monitored values had an r² = 0.62 for predicted concentrations and an r² = 0.95 for predicted disposed amounts to sea.

Mutagenicity in Surface Waters: Synergistic Effects of Carboline Alkaloids and Aromatic Amines

For decades, mutagenicity has been observed in many surface waters with a possible link to the presence of aromatic amines. River Rhine is a well-known example of this phenomenon but responsible compound(s) are still unknown. To identify the mutagenic compounds, we applied effect-directed analysis (EDA) utilizing novel analytical and biological approaches to a water sample extract from the lower Rhine. We could identify 21 environmental contaminants including two weakly mutagenic aromatic amines, and the known alkaloid comutagen norharman along with two related β-carboline alkaloids, carboline, and 5-carboline, which were reported the first time in surface waters. Results of mixture tests showed a strong synergism of the identified aromatic amines not only with norharman, but also with carboline and 5-carboline. Additionally, other nitrogen-containing compounds also contributed to the mutagenicity when aromatic amines were present. Thus, comutagenicity of β-carboline alkaloids with aromatic amines is shown to occur in surface waters. These results strongly suggest that surface water mutagenicity is highly complex and driven by synergistic mechanisms of a complex compound mixture (of which many are yet unidentified) rather than by single compounds. Therefore, mixture effects should be considered not only from mutagens alone, but also including possible comutagens and nonmutagenic compounds.