External validation of EPIWIN biodegradation models

Water, Water Everywhere, but Every Drop Unique: Challenges in the Science to Understand the Role of Contaminants of Emerging Concern in the Management of Drinking Water Supplies

The protection and management of water resources continues to be challenged by multiple and ongoing factors such as shifts in demographic, social, economic, and public health requirements. Physical limitations placed on access to potable supplies include natural and human-caused factors such as aquifer depletion, aging infrastructure, saltwater intrusion, floods, and drought. These factors, although varying in magnitude, spatial extent, and timing, can exacerbate the potential for contaminants of concern (CECs) to be present in sources of drinking water, infrastructure, premise plumbing and associated tap water. This monograph examines how current and emerging scientific efforts and technologies increase our understanding of the range of CECs and drinking water issues facing current and future populations. It is not intended to be read in one sitting, but is instead a starting point for scientists wanting to learn more about the issues surrounding CECs. This text discusses the topical evolution CECs over time (Section 1), improvements in measuring chemical and microbial CECs, through both analysis of concentration and toxicity (Section 2) and modeling CEC exposure and fate (Section 3), forms of treatment effective at removing chemical and microbial CECs (Section 4), and potential for human health impacts from exposure to CECs (Section 5). The paper concludes with how changes to water quantity, both scarcity and surpluses, could affect water quality (Section 6). Taken together, these sections document the past 25 years of CEC research and the regulatory response to these contaminants, the current work to identify and monitor CECs and mitigate exposure, and the challenges facing the future.

Safe and sustainable by design: A computer-based approach to redesign chemicals for reduced environmental hazards

Persistency of chemicals in the environment is seen a pressing issue as it results in accumulation of chemicals over time. Persistent chemicals can be an asset in a well-functioning circular economy where products are more durable and can be reused or recycled. This objective can however not always be fulfilled as release of chemicals from products into the environment can be inherently coupled to their use. In these situations, chemicals should be designed for degradation. In this study, a systematic and computer-aided workflow was developed to facilitate the chemical redesign for reduced persistency. The approach includes elements of Essential Use, Alternatives Assessment and Green and Circular Chemistry and ties into goals recently formulated in the context of the EU Green Deal. The organophosphate chemical triisobutylphosphate (TiBP) was used as a case study for exploration of the approach, as its emission to the environment was expected to be inevitable when used as a flame retardant. Over 6.3 million alternative structures were created in silico and filtered based on QSAR outputs to remove potentially non-readily biodegradable structures. With a multi-criteria analysis based on predicted properties and synthesizability a top 500 of most desirable structures was identified. The target structure (di-n-butyl (2-hydroxyethyl) phosphate) was manually selected and synthesized. The approach can be expanded and further verified to reach its full potential in the mitigation of chemical pollution and to help enable a safe circular economy.

Multi-Strategy Assessment of Different Uses of QSAR under REACH Analysis of Alternatives to Advance Information Transparency

Under the Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH) analysis of alternatives (AoA) process, quantitative structure–activity relationship (QSAR) models play an important role in expanding information gathering and organizing frameworks. Increasingly recognized as an alternative to testing under registration. QSARs have become a relevant tool in bridging data gaps and supporting weight of evidence (WoE) when assessing alternative substances. Additionally, QSARs are growing in importance in integrated testing strategies (ITS). For example, the REACH ITS framework for specific endpoints directs registrants to consider non-testing results, including QSAR predictions, when deciding if further animal testing is needed. Despite the raised profile of QSARs in these frameworks, a gap exists in the evaluation of QSAR use and QSAR documentation under authorization. An assessment of the different uses (e.g., WoE and ITS) in which QSAR predictions play a role in evidence gathering and organizing remains unaddressed for AoA. This study approached the disparity in information for QSAR predictions by conducting a substantive review of 24 AoA through May 2017, which contained higher-tier endpoints under REACH. Understanding the manner in which applicants manage QSAR prediction information in AoA and assessing their potential within ITS will be valuable in promoting regulatory use of QSARs and building out future platforms in the face of rapidly evolving technology while advancing information transparency.

Modelling of ready biodegradability based on combined public and industrial data sources

The European Registration, Evaluation, Authorization and Restriction of Chemical Substances Regulation, requires marketed chemicals to be evaluated for Ready Biodegradability (RB), considering in silico prediction as valid alternative to experimental testing. However, currently available models may not be relevant to predict compounds of industrial interest, due to accuracy and applicability domain restriction issues. In this work, we present a new and extended RB dataset (2830 compounds), issued by the merging of several public data sources. It was used to train classification models, which were externally validated and benchmarked against already-existing tools on a set of 316 compounds coming from the industrial context. New models showed good performances in terms of predictive power (Balance Accuracy (BA) = 0.74-0.79) and data coverage (83-91%). The Generative Topographic Mapping approach identified several chemotypes and structural motifs unique to the industrial dataset, highlighting for which chemical classes currently available models may have less reliable predictions. Finally, public and industrial data were merged into global dataset containing 3146 compounds. This is the biggest dataset reported in the literature so far, covering some chemotypes absent in the public data. Thus, predictive model developed on the Global dataset has larger applicability domain than the existing ones.

Potential emerging chemical risks in the food chain associated with substances registered under REACH

A screening procedure for the identification of potential emerging chemical risks in the food and feed chain developed in a previous EFSA-sponsored pilot study was applied to 15021 substances registered under the REACH Regulation at the time of evaluation. Eligible substances were selected from this dataset by excluding (a) intermediates handled under strictly controlled conditions, (b) substances lacking crucial input data and (c) compounds considered to be outside the applicability domain of the models used. Selection of eligible substances resulted in a considerable reduction to 2336 substances. These substances were assessed and scored for environmental release (tonnage and use information from REACH registration dossiers), biodegradation (predictions from BIOWIN models 3, 5 and 6 evaluated in a battery approach), bioaccumulation in food/feed (ACC-HUMANsteady modelling) and chronic human health hazards (classification according to the CLP Regulation for carcinogenicity, mutagenicity, reproductive toxicity and repeated dose toxicity as well as IARC classification for carcinogenicity). Prioritisation based on the scores assigned and additional data curation steps identified 212 substances that are considered potential emerging risks in the food chain. Overall, 53% of these substances were prioritised due to chronic hazards identified in REACH registrations dossiers only (i.e. hazards not identified in classifications from other sources). Bioaccumulation in food and feed predicted on the basis of ACC-HUMANsteady modelling identified many substances that are not considered bioaccumulative in aquatic or terrestrial organisms based on screening criteria of the relevant ECHA guidance documents. Furthermore, 52% of the priority substances have not yet been assessed for their presence in food/feed by EU regulatory agencies. This finding and illustrative examples suggest that the screening procedure identified substances that have the potential to be emerging chemical risks in the food chain. Future research should investigate whether they actually represent emerging chemical risks as defined in EFSA's mandate.

A review of quantitative structure-property relationships for the fate of ionizable organic chemicals in water matrices and identification of knowledge gaps

Many organic chemicals are ionizable by nature. After use and release into the environment, various fate processes determine their concentrations, and hence exposure to aquatic organisms. In the absence of suitable data, such fate processes can be estimated using Quantitative Structure-Property Relationships (QSPRs). In this review we compiled available QSPRs from the open literature and assessed their applicability towards ionizable organic chemicals. Using quantitative and qualitative criteria we selected the 'best' QSPRs for sorption, (a)biotic degradation, and bioconcentration. The results indicate that many suitable QSPRs exist, but some critical knowledge gaps remain. Specifically, future focus should be directed towards the development of QSPR models for biodegradation in wastewater and sediment systems, direct photolysis and reaction with singlet oxygen, as well as additional reactive intermediates. Adequate QSPRs for bioconcentration in fish exist, but more accurate assessments can be achieved using pharmacologically based toxicokinetic (PBTK) models. No adequate QSPRs exist for bioconcentration in non-fish species. Due to the high variability of chemical and biological species as well as environmental conditions in QSPR datasets, accurate predictions for specific systems and inter-dataset conversions are problematic, for which standardization is needed. For all QSPR endpoints, additional data requirements involve supplementing the current chemical space covered and accurately characterizing the test systems used.

Evaluation of the persistence of transformation products from ozonation of trace organic compounds - a critical review

Ozonation is an efficient treatment system to reduce the concentration of trace organic compounds (TrOCs) from technical aquatic systems such as drinking water, wastewater and industrial water, etc. Although it is well established that ozonation generally improves the removal of organic matter in biological post-treatment, little is known about the biodegradability of individual transformation products resulting from ozonation of TrOCs. This publication provides a qualified assessment of the persistence of ozone-induced transformation products based on a review of published product studies and an evaluation of the biodegradability of transformation products with the biodegradability probability program (BIOWIN) and the University of Minnesota Pathway Prediction System (UM-PPS). The oxidation of TrOCs containing the four major ozone-reactive sites (olefins, amines, aromatics and sulfur-containing compounds) follows well described reaction pathways leading to characteristic transformation products. Assessment of biodegradability revealed a high sensitivity to the formed products and hence the ozone-reactive site present in the target compound. Based on BIOWIN, efficient removal can be expected for products from cleavage of olefin groups and aromatic rings. In contrast, estimations and literature indicate that hydroxylamines and N-oxides, the major products from ozonation of secondary and tertiary amines are not necessarily better removed in biological post-treatment. According to UM-PPS, degradation of these products might even occur via reformation of the corresponding amine. Some product studies with sulfide-containing TrOCs showed a stoichiometric formation of sulfoxides from oxygen transfer reactions. However, conclusions on the fate of transformation products in biological post-treatment cannot be drawn based on BIOWIN and UM-PPS.

Effect of alkyl side chain location and cyclicity on the aerobic biotransformation of naphthenic acids

Aerobic biodegradation of naphthenic acids is of importance to the oil industry for the long-term management and environmental impact of process water and wastewater. The effect of structure, particularly the location of the alkyl side chain as well as cyclicity, on the aerobic biotransformation of 10 model naphthenic acids (NAs) was investigated. Using an aerobic, mixed culture, enriched with a commercial NA mixture (NA sodium salt; TCI Chemicals), batch biotransformation assays were conducted with individual model NAs, including eight 8-carbon isomers. It was shown that NAs with a quaternary carbon at the α- or β-position or a tertiary carbon at the β- and/or β'-position are recalcitrant or have limited biodegradability. In addition, branched NAs exhibited lag periods and lower degradation rates than nonbranched or simple cyclic NAs. Two NA isomers used in a closed bottle, aerobic biodegradation assay were mineralized, while 21 and 35% of the parent compound carbon was incorporated into the biomass. The NA biodegradation probability estimated by two widely used models (BIOWIN 2 and 6) and a recently developed model (OCHEM) was compared to the biodegradability of the 10 model NAs tested in this study as well as other related NAs. The biodegradation probability estimated by the OCHEM model agreed best with the experimental data and was best correlated with the measured NA biodegradation rate.

An assessment of biodegradability of quaternary carbon-containing fragrance compounds: comparison of experimental OECD screening test results and in silico prediction data

An assessment of biodegradability was carried out for fragrance substances containing quaternary carbons by using data obtained from Organisation for Economic Co-operation and Development (OECD) 301F screening tests for ready biodegradation and from Biowin and Catalogic prediction models. Despite an expected challenging profile, a relatively high percentage of common-use fragrance substances showed significant biodegradation under the stringent conditions applied in the OECD 301F test. Among 27 test compounds, 37% met the pass level criteria after 28 d, while another 26% indicated partial breakdown (≥20% biodegradation). For several compounds for which structural analogs were available, the authors found that structures that were rendered less water soluble by either the presence of an acetate ester or the absence of oxygen tended to degrade to a lesser extent compared to the primary alcohols or oxygenated counterparts under the test conditions applied. Difficulties were encountered when attempting to correlate experimental with in silico data. Whereas the Biowin model combinations currently recommended by regulatory agencies did not allow for a reliable discrimination between readily and nonbiodegradable compounds, only a comparably small proportion of the chemicals studied (30% and 63% depending on the model) fell within the applicability domain of Catalogic, a factor that critically reduced its predictive power. According to these results, currently neither Biowin nor Catalogic accurately reflects the potential for biodegradation of fragrance compounds containing quaternary carbons.

Evaluation of a model for the removal of pharmaceuticals, personal care products, and hormones from wastewater

Current wastewater treatment processes are insufficient at removing many pharmaceutical and personal care products (PPCPs) from wastewater and it is necessary to identify the chemical characteristics that determine their fate. Models that predict the fate of various chemicals lack verification using in situ data, particularly for PPCPs. BIOWIN4 is a quantitative structure-activity relationship (QSAR) model that has been proposed to estimate the removal of PPCPs from wastewater, but data verifying the accuracy of its predictions is limited. In this study, the in situ soluble and suspended solid concentrations were assessed from raw influent, primary effluent, secondary effluent, and final effluent for 54 PPCPs and hormones over six dates. When assessing the removal efficiency across the different stages of the WWTP, the majority of the removal occurred across the secondary treatment process for the majority of the compounds. The primary treatment and disinfection process had limited impacts on the removal of most PPCPs. Sorption to solids was found to influence the removal for compounds with a log octanol-water partitioning coefficient greater than 4.5 across the secondary treatment process. For other compounds, the removal of PPCPs across the secondary treatment process was significantly correlated with the biodegradation predicted by BIOWIN4. Removal efficiencies across the aerobic secondary treatment process were predicted by integrating BIOWIN4 into pseudo-first order kinetics of PPCPs and these predicted values were compared to the in situ data. This study determines that under a certain set of operating conditions, two chemical characteristics - the expected hydrophobic interaction and the modeled biological degradation from BIOWIN4 - were found to predict the removal of highly degradable and recalcitrant PPCPs from a wastewater secondary treatment process.

External validation of structure-biodegradation relationship (SBR) models for predicting the biodegradability of xenobiotics

Biodegradation is an important mechanism for eliminating xenobiotics by biotransforming them into simple organic and inorganic products. Faced with the ever growing number of chemicals available on the market, structure-biodegradation relationship (SBR) and quantitative structure-biodegradation relationship (QSBR) models are increasingly used as surrogates of the biodegradation tests. Such models have great potential for a quick and cheap estimation of the biodegradation potential of chemicals. The Estimation Programs Interface (EPI) Suite™ includes different models for predicting the potential aerobic biodegradability of organic substances. They are based on different endpoints, methodologies and/or statistical approaches. Among them, Biowin 5 and 6 appeared the most robust, being derived from the largest biodegradation database with results obtained only from the Ministry of International Trade and Industry (MITI) test. The aim of this study was to assess the predictive performances of these two models from a set of 356 chemicals extracted from notification dossiers including compatible biodegradation data. Another set of molecules with no more than four carbon atoms and substituted by various heteroatoms and/or functional groups was also embodied in the validation exercise. Comparisons were made with the predictions obtained with START (Structural Alerts for Reactivity in Toxtree). Biowin 5 and Biowin 6 gave satisfactorily prediction results except for the prediction of readily degradable chemicals. A consensus model built with Biowin 1 allowed the diminution of this tendency.

The application of a simplified method to map the aerobic acetate mineralization rates at the groundwater table of the Netherlands

A simplified method is used to assess the microbial activity of subsoils and soils across a broad geographic scale. Acetate was selected because it is a major intermediate in catabolic biochemical pathways. In order to get minimal disturbance, only a small amount of tritium labelled acetate and water is added to the subsoil material. After an incubation time, the subsoil material is separated from the water by centrifugation and the formed tritium labelled water is separated from the remaining acetate by evaporation. The data of 128 locations in the Netherlands were plotted in a soil map and were also compared with the depth, dry weight, electric conductivity, pH and nitrate concentration. The peat areas consisted of limed meadows with a high groundwater level whereas the sand areas often showed deeper groundwater levels and a lower pH. The subsoils at the groundwater table of the peat areas, which are in contact with soil air, showed a higher mineralization rate compared with the surface soils in our study. In contrast, the mineralization rate of the subsoil at the groundwater table of sandy soils showed on average a factor 30 lower rate. Nevertheless, the self purification capacity of the subsoil can be vital under weather conditions where the surface soil becomes less active.

Structural alerts for estimating the carcinogenicity of pesticides and biocides

More than 20 years ago, Ashby and Tennant showed the interest of structural alerts for the prediction of the carcinogenicity of chemicals. These structural alerts are functional groups or structural features of various sizes that are linked to the level of carcinogenicity of chemicals. Since this pioneering work it has been possible to refine the alerts over time, as more experimental results have become available and additional mechanistic insights have been gained. To date, one of the most advanced lists of structural alerts for evaluating the carcinogenic potential of chemicals is the list proposed by Benigni and Bossa and that is implemented as a rule-based system in Toxtree and in the OECD QSAR Application Toolbox. In order to gain insight into the applicability of this system to the detection of potential carcinogens we screened about 200 pesticides and biocides showing a high structural diversity. Prediction results were compared with experimental data retrieved from an extensive bibliographical review. The prediction correctness was only equal to 60.14%. Attempts were made to analyse the sources of mispredictions.

Multivariate chemical mapping of antibiotics and identification of structurally representative substances

Antibiotics used in human and veterinary medicine have been found in samples from diverse environments in many parts of the world. To assess the environmental risks associated with them, data regarding their toxicity, occurrence, and fate are needed, but gathering such data is time-consuming and expensive. An efficient approach to address these difficulties would be to select a small subset of antibiotics with a wide variation in chemical characteristics, perform experimental tests on this subset, and then extrapolate the results to larger numbers of antibiotics, including the most potentially hazardous compounds. To assess the potential utility of such an approach, a set of 92 antibiotics for human use was studied and their structural properties were described with 24 chemical descriptors that included information on their steric, lipophilic, and electronic properties. Principal component analysis in combination with statistical experimental design was used to map the chemical diversity of the antibiotics and to select a small subset, a "training set", of 20 antibiotics. The chemical representativity of the training set was assessed in a quantitative structure-activity model established to predict ultimate biodegradation. The selected antibiotics showed to cover the chemical variation of the studied antibiotics and are suggested for use in future testing programs to assess antibiotics' fate and effects in the environment.

Evolution of the international workshops on quantitative structure-activity relationships (QSARs) in environmental toxicology

This presentation will review the evolution of the workshops from a scientific and personal perspective. From their modest beginning in 1983, the workshops have developed into larger international meetings, regularly held every two years. Their initial focus on the aquatic sphere soon expanded to include properties and effects on atmospheric and terrestrial species, including man. Concurrent with this broadening of their scientific scope, the workshops have become an important forum for the early dissemination of all aspects of qualitative and quantitative structure-activity research in ecotoxicology and human health effects. Over the last few decades, the field of quantitative structure/activity relationships (QSARs) has quickly emerged as a major scientific method in understanding the properties and effects of chemicals on the environment and human health. From substances that only affect cell membranes to those that bind strongly to a specific enzyme, QSARs provides insight into the biological effects and chemical and physical properties of substances. QSARs are useful for delineating the quantitative changes in biological effects resulting from minor but systematic variations of the structure of a compound with a specific mode of action. In addition, more holistic approaches are being devised that result in our ability to predict the effects of structurally unrelated compounds with (potentially) different modes of action. Research in QSAR environmental toxicology has led to many improvements in the manufacturing, use, and disposal of chemicals. Furthermore, it has led to national policies and international agreements, from use restrictions or outright bans of compounds, such as polychlorinated biphenyls (PCBs), mirex, and highly chlorinated pesticides (e.g. DDT, dieldrin) for the protection of avian predators, to alternatives for ozone-depleting compounds, to better waste treatment systems, to more powerful and specific acting drugs. Most of the recent advances in drug development could not have been achieved without the use of QSARs in one form or another. The pace of such developments is rapid and QSARs are the keystone to that progress. These workshops have contributed to this progress and will continue to do so in the future.