Uncertainty in the results from oral repeated dose toxicity tests: Impact on regulatory classifications.

The Lowest Observed (Adverse) Effect Level (LO(A)EL) values are point-of-departure (PoD) values that quantify repeat dose toxicity (RDT). Here, the uncertainty in the regulatory classification of these PoDs is investigated. In the application stage, the dose-response was approximated for a large set of series, giving an account of the possible presence of a hormesis zone.

Estimating uncertainty in LLNA EC3 data and its impact on regulatory classifications.

The murine Local Lymph Node Assay (LLNA) is a test that produces numerical results (EC3 values) quantifying the sensitization potency of chemicals. These results are broadly used in toxicology and serve as a basis for various classifications, which determine subsequent regulatory decisions. The continuing interest in LLNA data and the diminished likelihood of new experimental EC3 data being generated sparked this investigation of uncertainty.

Selection of Representative Constituents for Unknown, Variable, Complex, or Biological Origin Substance Assessment Based on Hierarchical Clustering.

Many of the newly produced and registered substances are complex mixtures or substances of unknown or variable composition, complex reaction products, and biological materials (UVCBs). The latter often consist of a large number of constituents, some of them difficult-to-identify constituents, which complicates their (eco)toxicological assessment. In the present study, through a series of examples, different scenarios for selection of representatives via hierarchical clustering of UVCB constituents are exemplified.

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.

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.

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.

CATALOGIC 301C model - validation and improvement.

In Europe, REACH legislation encourages the use of alternative in silico methods such as (Q)SAR models. According to the recent progress of Chemical Substances Control Law (CSCL) in Japan, (Q)SAR predictions are also utilized as supporting evidence for the assessment of bioaccumulation potential of chemicals along with read across. Currently, the effective use of read across and QSARs is examined for other hazards, including biodegradability.

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.

Evaluation of human pharmaceutical emissions and concentrations in Swedish river basins.

An emissions inventory for top consumed human pharmaceuticals in Sweden was done based on national consumption data, human metabolic rates and wastewater treatment removal rates. Concentrations of pharmaceuticals in surface waters in Swedish river basins were predicted using estimated emissions from the inventory and river discharges. Our findings indicate that the top ten emitted pharmaceuticals in our study set of 54 substances are all emitted in amounts above 0.

Accounting for data variability, a key factor in in vivo/in vitro relationships: application to the skin sensitization potency (in vivo LLNA versus in vitro DPRA) example.

When searching for alternative methods to animal testing, confidently rescaling an in vitro result to the corresponding in vivo classification is still a challenging problem. Although one of the most important factors affecting good correlation is sample characteristics, they are very rarely integrated into correlation studies. Usually, in these studies, it is implicitly assumed that both compared values are error-free numbers, which they are not.

QSAR Toolbox - workflow and major functionalities.

The OECD QSAR Toolbox is a software application intended to be used by governments, the chemical industry and other stakeholders in filling gaps in (eco)toxicity data needed for assessing the hazards of chemicals. The development and release of the Toolbox is a cornerstone in the computerization of hazard assessment, providing an 'all inclusive' tool for the application of category approaches, such as read-across and trend analysis, in a single software application, free of charge. The Toolbox incorporates theoretical knowledge, experimental data and computational tools from various sources into a logical workflow.

Towards AOP application--implementation of an integrated approach to testing and assessment (IATA) into a pipeline tool for skin sensitization.

Since the OECD published the Adverse Outcome Pathway (AOP) for skin sensitization, many efforts have focused on how to integrate and interpret nonstandard information generated for key events in a manner that can be practically useful for decision making. These types of frameworks are known as Integrated Approaches to Testing and Assessment (IATA). Here we have outlined an IATA for skin sensitization which focuses on existing information including non testing approaches such as QSAR and read-across.

A mechanistic approach to modeling respiratory sensitization.

Chemical respiratory sensitization is an important occupational health problem which may lead to severely incapacitated human health, yet there are currently no validated or widely accepted models for identifying and characterizing the potential of a chemical to induce respiratory sensitization. This is in part due to the ongoing uncertainty about the immunological mechanisms through which respiratory sensitization may be acquired. Despite the lack of test method, regulations such as REACH still require an assessment of respiratory sensitization for risk assessment and/or for the purposes of classification and labeling.

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.

Simulation of chemical metabolism for fate and hazard assessment. IV. Computer-based derivation of metabolic simulators from documented metabolism maps.

Computer simulation of xenobiotic metabolism and degradation is usually performed proceeding from a set of expert-developed rules modelling the actual enzyme-driven chemical reactions. With the accumulation of extensive metabolic pathway data, the analysis required to derive such chemical reaction patterns has become more objective, but also more convoluted and demanding. Herein we report on our computer-based approach for the analysis of metabolic maps, leading to the construction of reaction rules statistically suitable for simulation purposes.

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

The new development of the bioconcentration factor (BCF) base-line model of Dimitrov et al. [SAR QSAR Environ. Res.

Use of genotoxicity information in the development of integrated testing strategies (ITS) for skin sensitization.

Skin sensitization is an end point of concern for various legislation in the EU, including the seventh Amendment to the Cosmetics Directive and Registration Evaluation, Authorisation and Restriction of Chemicals (REACH). Since animal testing is a last resort for REACH or banned (from 2013 onward) for the Cosmetics Directive, the use of intelligent/integrated testing strategies (ITS) as an efficient means of gathering necessary information from alternative sources (e.g.

Development of a biodegradation model for the prediction of metabolites in soil.

The awareness of air, soil and water pollution has driven the search for better methods for the assessment of the environmental fate of industrial chemicals. This paper is focused on the simulation of formation and transformation of metabolites in soil. The key challenges in the development of a simulator for predicting metabolic fate of chemicals in soil are the complexity of the soil compartment and incompleteness of metabolic information.

Elimination kinetic model for organic chemicals in earthworms.

Mechanistic understanding of bioaccumulation in different organisms and environments should take into account the influence of organism and chemical depending factors on the uptake and elimination kinetics of chemicals. Lipophilicity, metabolism, sorption (bioavailability) and biodegradation of chemicals are among the important factors that may significantly affect the bioaccumulation process in soil organisms. This study attempts to model elimination kinetics of organic chemicals in earthworms by accounting for the effects of both chemical and biological properties, including metabolism.

Conformational coverage by a genetic algorithm: saturation of conformational space.

The molecular modeling is traditionally based on analysis of minimum energy conformers. Such simplifying assumptions could doom to failure the modeling studies given the significant variation of the geometric and electronic characteristics across the multitude of energetically reasonable conformers representing the molecules. Moreover, it has been found that the lowest energy conformers of chemicals are not necessarily the active ones with respect to various endpoints.

Identification of the structural requirements for mutagencitiy, by incorporating molecular flexibility and metabolic activation of chemicals. II. General Ames mutagenicity model.

The tissue metabolic simulator (TIMES) modeling approach is a hybrid expert system that couples a metabolic simulator together with structure toxicity rules, underpinned by structural alerts, to predict interaction of chemicals or their metabolites with target macromolecules. Some of the structural alerts representing the reactivity pattern-causing effect could interact directly with the target whereas others necessitated a combination with two- or three-dimensional quantitative structure-activity relationship models describing the firing of the alerts from the rest of the molecules. Recently, TIMES has been used to model bacterial mutagenicity [Mekenyan, O.

Quantitative structure-activity relationship modeling of dermatomyositis activity of drug chemicals.

Dermatomyositis (DM) is an idiopathic inflammatory disorder consisting of skin and skeletal muscle involvement. Some drugs induce DM or dermatomyositis-like syndrome (DM-LS), the others provoke polymoysitis (PM) or cause elevation of serum levels of muscle enzymes (SE) or give muscle damage (M). The unexpected adverse reactions to drugs causing myositis are not a solved contemporary problem.

Base-line model for identifying the bioaccumulation potential of chemicals.

The base-line modeling concept presented in this work is based on the assumption of a maximum bioconcentration factor (BCF) with mitigating factors that reduce the BCF. The maximum bioconcentration potential was described by the multi-compartment partitioning model for passive diffusion. The significance of different mitigating factors associated either with interactions with an organism or bioavailability were investigated.

Skin sensitization: modeling based on skin metabolism simulation and formation of protein conjugates.

A quantitative structure-activity relationship (QSAR) system for estimating skin sensitization potency has been developed that incorporates skin metabolism and considers the potential of parent chemicals and/or their activated metabolites to react with skin proteins. A training set of diverse chemicals was compiled and their skin sensitization potency assigned to one of three classes. These three classes were, significant, weak, or nonsensitizing.

A stepwise approach for defining the applicability domain of SAR and QSAR models.

A stepwise approach for determining the model applicability domain is proposed. Four stages are applied to account for the diversity and complexity of the current SAR/QSAR models, reflecting their mechanistic rationality (including metabolic activation of chemicals) and transparency. General parametric requirements are imposed in the first stage, specifying in the domain only those chemicals that fall in the range of variation of the physicochemical properties of the chemicals in the training set.