QSARs for identifying and prioritizing substances with persistence and bioconcentration potential

From the 8511 chemicals with 1998 production volumes reported to the U.S. Environmental Protection Agency (U.S. EPA), the TSCA Interagency Testing Committee's (ITC's) Degradation Effects Bioconcentration Information Testing Strategies (DEBITS) was used to identify 56 chemicals. The DEBITS Quantitative Structure-Activity Relationships (QSARs) and the U.S. EPA's PBT profiler QSARs were used to predict the persistence and bioconcentration factors of these 56 chemicals. Partial order ranking was used to prioritise the chemicals based on persistence and bioconcentration potential.     

U.S. EPA Regulatory Perspectives on the Use of QSAR for New and Existing Chemical Evaluations

Abstract

As testing is not required, ecotoxicity or fate data are available for ≈ 5% of the approximately 2,300 new chemicals/year (26,000 + total) submitted to the US-EPA. The EPA's Office of Pollution Prevention and Toxics (OPPT) regulatory program was forced to develop and rely upon QSARs to estimate the ecotoxicity and fate of most of the new chemicals evaluated for hazard and risk assessment. QSAR methods routinely result in ecotoxicity estimations of acute and chronic toxicity to fish, aquatic invertebrates, and algae, and in fate estimations of physical/chemical properties, degradation, and bioconcentration. The EPA's Toxic Substances Control Act (TSCA) Inventory of existing chemicals currently lists over 72,000 chemicals. Most existing chemicals also appear to have little or no ecotoxicity or fate data available and the OPPT new chemical QSAR methods now provide predictions and cross-checks of test data for the regulation of existing chemicals. Examples include the Toxics Release Inventory (TRI), the Design for the Environment (DfE), and the OECD/SIDS/HPV Programs. QSAR screening of the TSCA Inventory has prioritized thousands of existing chemicals for possible regulatory testing of: 1) persistent bioaccumulative chemicals, and 2) the high ecotoxicity of specific discrete organic chemicals.     

Global Government applications of analogues,SAR s and QSAR s to predict aquatic toxicity,chemical or physical properties,environmental fate parameters and health effects of organic chemicals

Faced with the need to predict physical and chemical properties, environmental fate, ecological effects and health effects of organic chemicals in the absence of experimental data, several Government organizations have been applying analogues, Structure Activity Relationships (SARs) and Quantitative Structure Activity Relationships (QSARs) to develop those predictions. To establish some benchmarks for monitoring future increases in applications of analogues, SARs and QSARs by global Government organizations, this paper describes the current applications of analogues, SARs and QSARs by Australian, Canadian, Danish, European, German, Japanese, Netherlands, and United States Government organizations to predict physical and chemical properties, environmental fate, ecological effects and health effects of organic chemicals.     

SAR—The U.S. Regulatory Perspective

Abstract

Structure-Activity Relationships (SAR) have been used for over a decade by the U.S. EPA's Office of Pollution Prevention and Toxics (OPPT) in their new chemicals program. The development and use of SAR resulted from the need to make rapid risk-based decisions on thousands of new chemicals per year while seldom receiving data on chemical properties, potential exposures, or hazards to humans or organisms in the environment. Qualitative SAR and quantitative SAR methods (QSAR) have been used to fill some of these data gaps by estimating the potential properties and hazards of such chemicals. SAR has been used to assess chemical hazards, identify testing needs, and set priorities. Validation of these SAR assessment tools is an ongoing process.     

Molecular Lipophilicity Calculations of Chemically Heterogeneous Chemicals and Drugs on the Basis of Structural Similarity and Physicochemical Parameters

Abstract

QSARs based on molecular polarizability (α) and H-bond acceptor factors (∑C_a) as independent variables provided good predictability of octanol/water partition coefficients (P) for chemicals and drugs. However, for some molecules containing few functional groups, the calculated values deviated significantly from those observed. This approach gave good results when applied to a set of 138 chemicals and drugs previously studied by Mannhold and Dross who compared other methods to calculate log P values.

At the same time, three variations on a molecular similarity approach were pursued. In this study, a large training set with experimentally determined octanol/water partition coefficients (P) was searched for structures closely related to the compound-of-interest. The most successful of these variations took the mean log P value of few most closely related compounds after each was adjusted for differences between their and the compound-of-interest's polarizabilities (α) and H-bond acceptor capacities (∑C_a).     

Evaluation of Critical Body Residue QSARS for Predicting Organic Chemical Toxicity to Aquatic Organisms

Abstract

The critical body residue (CBR) is the concentration of chemical bioaccumulated in an aquatic organism that corresponds to a defined measure of toxicity (e.g., mortality). The CBR can provide an alternative measure of toxicity to traditional waterborne concentration measurements (e.g., concentration in water causing 50% mortality). The CBR has been suggested as a better estimator of dose than the external water concentration and has been postulated to be constant for chemicals with the same mode of action. CBR QSARs have both theoretical and experimental support, developed primarily from studies on the acute toxicity of narcotic chemicals to small fish. CBR QSARs are less well developed for the aquatic toxicity of non-narcotic chemicals. CBRs vary substantially with the mode of action and toxicity endpoint, and may be affected by genetic, hormonal or environmental variation. CBR QSARs may not be applicable to very hydrophobic chemicals, chemicals with specific modes of action, or those with toxicity controlled by kinetic processes such as biotransformation. CBRs models have not been developed or evaluated for sediment and dietary exposure routes. Application of CBR QSARs to contaminated site assessments will require further research and development.     

Evaluation of the Use of QSARS for Priority Setting and Risk Assessment

Abstract

Impending changes in EEC legislation have accelerated the need to define the principles and practical considerations of the use of QSARs in priority setting and risk assessment. It is important to delineate the limitations of this approach and to review whether and how this information should be used in the risk assessment. The value and limitations of QSARs for use in priority setting and risk assessment will not be discussed in detail since the European Chemical Industry Ecology and Toxicology Centre (ECETOC) has only recently established a Task Force to tackle this issue. The terms of reference of the Task Force are: (1) compare the predictions obtained with QSARs to measured data using ECETOC databases and other sources of data and comment on the validity and applicability of such QSARs; (2) identify and review software packages which are available for accessing and using appropriate QSARs; (3) identify those aspects of environmental distribution, fate and effects where the further development of QSARs is desirable and feasible; and (4) provide a scientific basis for ECETOC's contribution to the activities of the European Chemicals Bureau (ECB) in this area. In this short paper, only an initial and personal evaluation is made of when and where to use QSARs in the priority setting and risk assessment process within the regulatory framework. Some critical remarks and suggestions are provided to guide future developments and integration of QSARs in the risk assessment process.     

Comparison of three fish bioaccumulation models for ecological and human risk assessment and validation with field data

This article compares two bioconcentration Quantitative Structure Activity Relationships (QSARs) for fish applied in human risk assessments with the mechanistic bioaccumulation model OMEGA and field data. It was found that all models are virtually similar up to a Kow of 10(6). For substances with a Kow higher than 10(6), the fish bioconcentration curve in the risk assessment model EUSES decreases parabolically. In contrast, OMEGA bioaccumulation outcomes approximately show a linear increase, based on mechanistic bioconcentration and biomagnification properties of chemicals. The OMEGA-outcomes are close to the fish bioconcentration outcomes of the risk assessment model CalTOX. For very hydrophobic substances, field accumulation data in freshwater and marine fish species are closer to OMEGA- and CalTOX-outcomes compared to EUSES. The results also show that it is important to include biomagnification in fish and lipid content of fish in human exposure models.     

The Application of Structure-Activity Relationships (SARs) in the Aquatic Toxicity Evaluation of Discrete Organic Chemicals

Abstract

The Office of Pollution Prevention and Toxics (OPPT), United States Environmental Protection Agency (USEPA) routinely uses structure-activity relationships (SAR) for the aquatic hazard assessment of new chemicals submitted under Section 5 of the Toxic Substances Control Act (TSCA). With 15 years of experience and the general acceptance of toxicity predictions based on SARs, OPPT has expanded the use and application of the methodology to include existing chemicals used in printing, dry cleaning, and paint stripping. SAR analysis has also been used in the hazard evaluation of the U.S. and EU/OECD high production volume (HPV) chemicals. This paper describes the assumptions, limitations, and methodology for the use of SARs to evaluate large sets of discrete organic chemicals.     

Uses and limitations of quantitative structure-activity relationships (QSARs) to categorize substances on the Canadian domestic substance list as persistent and/or bioaccumulative,and inherently toxic to non-human organisms

Under sections 73 and 74 of the revised Canadian Environmental Protection Act (CEPA 1999) , Environment Canada and Health Canada must "categorize" and "screen" about 23,000 substances on the Domestic Substances List (DSL) for persistence (P), bioaccumulation (B), and inherently toxic (iT) properties. Since experimental data for P, B and iT are only available for a few DSL substances, a workshop was held to address issues associated with the use of Quantitative Structure-Activity Relationships (QSARs) to categorize these substances. This paper describes the results of an 11-12 November 1999 International Workshop sponsored by Environment Canada to discuss potential uses and limitations of QSARs to categorize DSL substances as either persistent or bioaccumulative and iT to non-human organisms and to recommend future research needed to develop methods for predicting the P, B and iT of difficult-to-model substances.     

Nonlinear Dependence of Fish Bioconcentration on n-Octanol/Water Partition Coefficient

Abstract

The log-log relationship between the bioconcentration tendency of organic chemicals in fish and the n?octanol/water partition coefficients breaks down for very hydrophobic compounds. The use of parabolic and bilinear models allows this problem to be overcome. The QSAR equation log BCF = 0.910 log P - 1.975 log (6.8 10^?7 P + 1) - 0.786 (n = 154; r = 0.950; s = 0.347; F = 463.51) was found to be a good predictor of bioconcentration in fish.     

A perspective on environmental models and QSARs

A general review is presented of the roles of QSARs and mass balance models as tools for assessing the environmental fate and effects of chemicals of commerce. It is argued that all such chemicals must be assessed using a consistent and transparent methodology that uses chemical property data derived from QSARs, or experimental determinations when possible and applies evaluative or region-specific environmental models. These data and models enable an assessment to be made of the key chemical features of persistence, bioaccumulation, potential for long-range transport and toxicity. The other key feature is quantity used or discharged to the environment. A taxonomy of environmental models is presented in which it is suggested that rather than develop a single comprehensive model, the aim should be to establish a set of coordinated and consistent models treating evaluative and real environmental systems at a variety of scales from local to global and including food web models, organism-specific models and human exposure and pharmacokinetic models. The concentrations derived from these models can then be compared with levels judged to be of toxic significance. A brief account is given of perceived QSAR needs in terms of partitioning, reactivity, transport and toxicity data to support these models.