Simulation of chemical metabolism for fate and hazard assessment. III. New developments of the bioconcentration factor base-line model

Comparative in vitro hepatic clearances of commonly used antidepressants, antipsychotics, and anti-inflammatory agents in rainbow trout liver S9 fractions

Residues of human pharmaceuticals are widely detected in surface waters and can be taken up by and bioaccumulate in aquatic organisms, especially fish. One of the key challenges in assessing the bioaccumulation potential of ionizable organic compounds, such as the pharmaceuticals, is the lack of empirical data for biotransformation. In the present study, we assessed the in vitro intrinsic clearances (CLINT) of twelve pharmaceuticals, individually and some additionally as mixtures, in rainbow trout (Oncorhynchus mykiss) liver S9 fractions (RT-S9) adhering to the OECD test guidance 319B. The test substances included four anti-inflammatory agents (diclofenac, ibuprofen, ketoprofen, naproxen), seven antidepressants/antipsychotics (citalopram, haloperidol, levomepromazine, mirtazapine, risperidone, sertraline, venlafaxine) and the O-desmethyl metabolite of venlafaxine. Quantifiable intrinsic clearances were detected for diclofenac, ibuprofen, naproxen, levomepromazine, and sertraline. Apart from diclofenac, the in vitro clearances of the other four pharmaceuticals were shown to be critically dependent on the cytochrome P450 (CYP) metabolism. Therefore, we also determined the half-maximal inhibitory concentrations (IC50) of the same twelve pharmaceuticals toward CYP1A-like (7-ethoxyresorufin-O-deethylation, EROD) and CYP3A-like (benzyloxy-4-trifluoromethylcoumarin-O-debenzyloxylation, BFCOD) activities in RT-S9 using IC50 shift assay. As a result, levomepromazine and sertraline were identified as the most potent inhibitors of both EROD and BFCOD activity (unbound IC50 < 10 µM each), followed by citalopram and haloperidol (10 µM < IC50 < 100 µM). Additionally, mirtazapine was a selective EROD inhibitor (IC50 ∼ 30 µM). The inhibitory impacts of haloperidol and sertraline were indicatively time dependent. Finally, we carried out intrinsic clearance assays with mixtures of diclofenac, ibuprofen, naproxen, levomepromazine, and sertraline to examine the impacts of EROD and BFCOD inhibitions on their in vitro CLINT in RT-S9. Our in vitro data suggests that the intrinsic clearances of ibuprofen, levomepromazine, and sertraline in rainbow trout can be significantly reduced as the result of P450 inhibition by pharmaceutical mixtures, whereas the clearances of diclofenac and naproxen are less impacted.

Are current regulatory log Kow cut-off values fit-for-purpose as a screening tool for bioaccumulation potential in aquatic organisms?

Persistent, Bioaccumulative and Toxic (PBT) and very Persistent and very Bioaccumulative (vPvB) are regulatory hazard categories that have been set to manage the possible risks to humans and the environment from these chemicals. In industrial chemicals regulations, their aquatic Bioaccumulation potential is usually assessed first with a screening based on the octanol/water partition coefficient (Kow). However, current log Kow cut-off values triggering classification, categorisation and/or further fish bioconcentration testing are not harmonised worldwide, and they have never been assessed for their regulatory relevance. In this study, the experimentally determined log Kow and fish bioconcentration factors (BCF) of 532 chemicals were compared. While the analysis underlined the robustness of using log Kow as a screening tool (5/532 were false negatives; log Kow: non-bioaccumulative, but BCF: bioaccumulative), it also demonstrated the conservatism of the cut-offs used worldwide. Indeed, many chemicals were deemed potentially Bioaccumulative based on log Kow when a fish bioaccumulation test showed no concern (false positives), therefore, leading to unnecessary use of vertebrate animals. Our analysis shows that the log Kow cut-off could be increased to 4.5 in all regions for all purposes without leading to a reduced protection of humans and the environment.

Modeling of Environmental Fate and Effects of Oil Leakages from Abandoned Subsea Wells Using an Environmental Impact Factor Tool

Potential environmental consequences of oil leakages (i.e., continuous uncontrolled releases at low flow rate over a long period of time) need to be taken into consideration in the ongoing development of plug and abandonment (P&A) activities on the Norwegian continental shelf. Regulations of P&A wells employ a "zero leakage" target; however, environmental risk monitoring strategies for permanent abandonment are not yet in place. Predicting and estimating the consequences of adverse environmental impacts through a modeling approach can play a key role in evaluating and monitoring environmental risk. In this paper, we present a modeling study of the fate and effects of an oil leakage from abandoned wells using a theoretical scenario on the Norwegian continental shelf. Environmental impact factors (EIFs) derived from the Dose related Risk and Effect Assessment Model (DREAM), previously designed to characterize the effects of produced water discharges, were used to assess impacts of leakages from abandoned wells. Exposure assessments for the EIFs were modified to include specific hydrocarbon contributions derived from different sized oil droplets from the leakages. Because DREAM is not generally used for chronic low-rate oil releases, an update of the database with chronic predicted no-effect concentrations, as input data for effects modeling, was conducted. In general, EIFs became stable after simulations of 30 d. The area from the release site and up to a few hundred meters southward had the most locations of high impact. Chronic exposure and effects on organisms potentially occurred as a steady-state effect over a long period. Risks, at which more than 95% of species will be negatively affected, appeared surrounding the release site, indicating a need for mitigation measures. These results show that the EIF tool can be used for risk management and P&A regulation by identifying potentially harmful leakages. Integr Environ Assess Manag 2021;17:626-638. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Exploring QSPR models for predicting PUF-air partition coefficients of organic compounds with linear and nonlinear approaches

Partition coefficients are important parameters for measuring the concentration of chemicals by passive sampling devices. Considering the wide application of the polyurethane foam (PUF) in passive air sampling, an attempt for developing several quantitative structure-property relationship (QSPR) models was made in this work, to predict PUF-air partition coefficients (K_PUF-air) using linear (multiple linear regression, MLR) and non-linear (artificial neural network, ANN and support vector machine, SVM) methods by machine learning. All of the developed models were performed on a dataset of 170 compounds comprising 9 distinct classes. A series of statistical parameters and validation results showed that models had good prediction ability, robustness and goodness-of-fit. Furthermore, the underlying mechanisms of molecular descriptors emphasized that ionization potential, molecular bond, hydrophilicity, size of molecule and valence electron number had dominating influence on the adsorption process of chemicals. Overall, the obtained models were all established on the extensive applicability domains, and thus can be used as effective tools to predict the K_PUF-air of new organic compounds or those have not been synthesized yet which, in turn, could help researchers better understand the mechanistic basis of adsorption behavior of PUF.

In Vitro Biotransformation Assays Using Liver S9 Fractions and Hepatocytes from Rainbow Trout (Oncorhynchus mykiss): Overcoming Challenges with Difficult to Test Fragrance Chemicals

In vitro metabolic stability assays using rainbow trout (Oncorhynchus mykiss) isolated hepatocytes (RT-HEP) or hepatic S9 fractions (RT-S9) were introduced to provide biotransformation rate data for the assessment of chemical bioaccumulation in fish. The present study explored the suitability of the RT-HEP and RT-S9 assays for difficult test chemicals, and the in vitro-based predictions were compared to in silico-based predictions and in vivo-measured bioconcentration factors (BCFs). The results show that volatile or reactive chemicals can be tested with minor modifications of the in vitro protocols. For hydrophobic chemicals, a passive dosing technique was developed. Finally, a design-of-experiment approach was used to identify optimal in vitro assay conditions. The modified assay protocols were applied to 10 fragrances with diverse physicochemical properties. The in vitro intrinsic clearance rates were higher in the S9 than in the hepatocyte assay, but the in vitro-in vivo (IVIV) predictions were comparable between the 2 assays. The IVIV predictions classified the test chemicals as nonbioaccumulative (BCF < 2000), which was in agreement with the in vivo data but in contrast to the in silico-based predictions. The findings from the present study provide strong evidence that the RT-HEP and RT-S9 assays can provide reliable estimates of in vivo biotransformation rates for test chemicals with difficult physicochemical properties. Environ Toxicol Chem 2020;39:2396-2408. © 2020 SETAC.

Mechanistic relationship between biodegradation and bioaccumulation. Practical outcomes

According to the REACH Regulation, for all substances manufactured or imported in amounts of 10 or more tons per year, that are not exempted from the registration requirement, a Chemical Safety Assessment (CSA) must be conducted. According to CSA criteria, for these substances persistent, bioaccumulative and toxic (PBT), and very persistent and very bioaccumulative (vPvB) assessment is requested. In order to reduce the number of applications of the expensive bioaccumulation test it seems useful to search thresholds for other related parameters above which no bioaccumulation is observed. Given the known relationship between ready biodegradability and bioaccumulation, one such parameter is biodegradation. This article addresses this relationship in searching for BOD threshold above which no vB and B chemicals could be observed. It was found that the regulatory criteria for persistency could be used for identification of not vB and B chemicals. In addition, fish liver metabolism is determined as the most significant factor in reducing of maximum bioaccumulation potential of the chemicals. It was found that parameters associated with the models simulating fish metabolism could be also used for identification of not vB and B chemicals.

In Silico Prediction of Organ Level Toxicity: Linking Chemistry to Adverse Effects

In silico methods to predict toxicity include the use of (Quantitative) Structure-Activity Relationships ((Q)SARs) as well as grouping (category formation) allowing for read-across. A challenging area for in silico modelling is the prediction of chronic toxicity and the No Observed (Adverse) Effect Level (NO(A)EL) in particular. A proposed solution to the prediction of chronic toxicity is to consider organ level effects, as opposed to modelling the NO(A)EL itself. This review has focussed on the use of structural alerts to identify potential liver toxicants. In silico profilers, or groups of structural alerts, have been developed based on mechanisms of action and informed by current knowledge of Adverse Outcome Pathways. These profilers are robust and can be coded computationally to allow for prediction. However, they do not cover all mechanisms or modes of liver toxicity and recommendations for the improvement of these approaches are given.

Development of human biotransformation QSARs and application for PBT assessment refinement

Toxicokinetics heavily influence chemical toxicity as the result of Absorption, Distribution, Metabolism (Biotransformation) and Elimination (ADME) processes. Biotransformation (metabolism) reactions can lead to detoxification or, in some cases, bioactivation of parent compounds to more toxic chemicals. Moreover, biotransformation has been recognized as a key process determining chemical half-life in an organism and is thus a key determinant for bioaccumulation assessment for many chemicals. This study addresses the development of QSAR models for the prediction of in vivo whole body human biotransformation (metabolism) half-lives measured or empirically-derived for over 1000 chemicals, mainly represented by pharmaceuticals. Models presented in this study meet regulatory standards for fitting, validation and applicability domain. These QSARs were used, in combination with literature models for the prediction of biotransformation half-lives in fish, to refine the screening of the potential PBT behaviour of over 1300 Pharmaceuticals and Personal Care Products (PPCPs). The refinement of the PBT screening allowed, among others, for the identification of PPCPs, which were predicted as PBTs on the basis of their chemical structure, but may be easily biotransformed. These compounds are of lower concern in comparison to potential PBTs characterized by large predicted biotransformation half-lives.

Assessing the bioaccumulation potential of ionizable organic compounds: Current knowledge and research priorities

The objective of the present study was to review the current knowledge regarding the bioaccumulation potential of ionizable organic compounds (IOCs), with a focus on the availability of empirical data for fish. Aspects of the bioaccumulation potential of IOCs in fish that can be characterized relatively well include the pH dependence of gill uptake and elimination, uptake in the gut, and sorption to phospholipids (membrane-water partitioning). Key challenges include the lack of empirical data for biotransformation and binding in plasma. Fish possess a diverse array of proteins that may transport IOCs across cell membranes. Except in a few cases, however, the significance of this transport for uptake and accumulation of environmental contaminants is unknown. Two case studies are presented. The first describes modeled effects of pH and biotransformation on the bioconcentration of organic acids and bases, while the second employs an updated model to investigate factors responsible for accumulation of perfluorinated alkyl acids. The perfluorinated alkyl acid case study is notable insofar as it illustrates the likely importance of membrane transporters in the kidney and highlights the potential value of read-across approaches. Recognizing the current need to perform bioaccumulation hazard assessments and ecological and exposure risk assessment for IOCs, the authors provide a tiered strategy that progresses (as needed) from conservative assumptions (models and associated data) to more sophisticated models requiring chemical-specific information. Environ Toxicol Chem 2017;36:882-897. © 2016 SETAC.

QSAR models for bioconcentration: is the increase in the complexity justified by more accurate predictions?

This study compares nine QSAR models for the prediction of BCF on fish: four KOW based models (Veith, Mackay, Bintein and TGD equations) and five complex models (EPI Suite BCFBAF, VEGA CAESAR, VEGA Meylan, VEGA Read-across and VEGA consensus). The aim is to test if increasing complexity leads to predictions that are more accurate than those based only on KOW are. To this end, experimental BCF data for 1056 compounds, along with experimental and predicted KOW values, were collected and used for the comparison. A particular focus has been placed on compounds for which metabolism, elimination and specific interactions with tissues can be hypothesized. VEGA Read-across improved global predictions with respect to the KOW based models and resulted to be a good approach to take into account metabolism and interactions with tissues. For the other complex models, several drawbacks were highlighted. Finally, for different classes of compounds (i.e. Perfluorinated Compounds, Organophosphorous Compounds, Synthetic Pyrethroids and Polychlorinated Biphenyls) results confirmed the mechanistic interpretation of the processes involved in their bioconcentration.

Development of a list of reference chemicals for evaluating alternative methods to in vivo fish bioaccumulation tests

The aim to reduce the number of animals in experiments has highlighted the need to develop and validate nonanimal methods as alternatives to bioaccumulation studies using fish. The present study details a novel 3-tier approach to develop a list of reference compounds to aid this process. The approach was based on 1) the inclusion of relevant chemical classes supported by high-quality in vivo data for the bioconcentration factor (BCF), whole-body biotransformation rates (K(met)), and metabolism characterization for rainbow trout (Oncorhynchus mykiss) and common carp (Cyprinus carpio) (tiers I and II); and 2) the refinement to ensure a broad coverage of hydrophobicity, bioconcentration potential, molecular weight, maximum molecular diameter, whole-body biotransformation half-lives, and metabolic pathways (tier III). In silico techniques were employed to predict maximal log BCF and molecular and metabolic properties. Of the 157 compounds considered as reference compounds, 144 were supported by high-quality BCF data, 8 were supported by K(met) data, and 5 were supported by in vivo metabolism data. Additional criteria for refinement of the list of reference compounds were suggested to aid practical implementation in experimental efforts. The present list of reference compounds is anticipated to facilitate the development of alternative approaches, enhance understanding of in vivo and in vitro bioaccumulation relationships, and refine in silico BCF and metabolism predictions.

Qualitative environmental risk assessment of photolytic transformation products of iodinated X-ray contrast agent diatrizoic acid

Recent studies have confirmed that the aquatic ecosystem is being polluted with an unknown cocktail of pharmaceuticals, their metabolites and/or their transformation products (TPs). Although individual chemicals are typically present at low concentrations, they can interact with each other resulting in additive or potentially even synergistic mixture effects. Therefore it is necessary to assess the environmental risk caused by these chemicals. Data on exposure is required for quantitative risk assessment of TPs and/or metabolites. Such data are mostly missing because of the non-availability of TPs and very often metabolites for experimental testing. This study demonstrates the application of different in silico tools for qualitative risk assessment using the example of photodegradation TPs (photo-TPs) of diatrizoic acid (DIAT), which itself is not readily biodegradable. Its photolytic transformation was studied and the photodegradation pathway was established. The aerobic biodegradability of photo-TPs under the conditions of an aquatic environment was assessed using standardized OECD tests. The qualitative risk assessment of DIAT and selected photo-TPs was performed by the PBT approach (i.e. Persistence, Bioaccumulation and Toxicity), using experimental biodegradation test assays, applying different QSAR models with several different toxicological endpoints and in silico read-across approaches. The qualitative risk assessment pointed out that the photo-TPs were less persistent compared to DIAT and none of them possessed any bioaccumulation threat. However, a few photo-TPs were predicted to be active for mutagenicity and genotoxicity, which indicate the need for further testing to confirm these predictions. The present study demonstrates that in silico qualitative risk assessment analysis can increase the knowledge space about the environmental fate of TPs.

Development of ecotoxicity QSAR models based on partial charge descriptors for acrylate and related compounds

Using Gasteiger's partial equalization of orbital electronegativity (PEOE) method, we constructed ecotoxicity prediction equations based on two-dimensional descriptors for α,β-unsaturated carbonyl compounds. After examining electrostatic effects on the calculated ecotoxicities of 10 α,β-unsaturated ketones and aldehydes (A-group compounds) by using the Mulliken atomic charges on the carbonyl oxygen atoms, we investigated the efficacy of the PEOE descriptors for the same 10 compounds and the correlation between the PEOE descriptors and the Mulliken charge. We then constructed QSAR models for acute fish and Daphnia toxicities by using the PEOE descriptors for acrylic acids and compounds with acrylate-like substructures (CH-group compounds). In the constructed models, the adjusted squared correlation coefficients between measured and calculated toxicities with the lowest Akaike information criterion were 0.77 and 0.79, respectively. The applicability of the constructed models was then evaluated for various methacrylates and similar compounds (CH(3)-group compounds). Both the fish and the Daphnia toxicities of some of the CH(3)-group compounds were underestimated by these models. Nevertheless, we concluded that the QSAR models based on the PEOE descriptors were practical for predicting acute toxicity, especially for α,β-unsaturated carbonyl compounds with an α-hydrogen. Combining hydrophobicity and PEOE descriptors led to accurate predictions for fish toxicity.

Simulation of chemical metabolism for fate and hazard assessment. V. Mammalian hazard assessment

Animals and humans are exposed to a wide array of xenobiotics and have developed complex enzymatic mechanisms to detoxify these chemicals. Detoxification pathways involve a number of biotransformations, such as oxidation, reduction, hydrolysis and conjugation reactions. The intermediate substances created during the detoxification process can be extremely toxic compared with the original toxins, hence metabolism should be accounted for when hazard effects of chemicals are assessed. Alternatively, metabolic transformations could detoxify chemicals that are toxic as parents. The aim of the present paper is to describe specificity of eukaryotic metabolism and its simulation and incorporation in models for predicting skin sensitization, mutagenicity, chromosomal aberration, micronuclei formation and estrogen receptor binding affinity implemented in the TIMES software platform. The current progress in model refinement, data used to parameterize models, logic of simulating metabolism, applicability domain and interpretation of predictions are discussed. Examples illustrating the model predictions are also provided.