read-across

/Tag:read-across

Development of an In Silico Profiler for Respiratory Sensitisation

Steven J. Enoch, David W. Roberts, Judith C. Madden and Mark T.D. Cronin

In this article, we outline work that led the QSAR and Molecular Modelling Group at Liverpool John Moores University to be jointly awarded the 2013 Lush Science Prize. Our research focuses around the development of in silico profilers for category formation within the Adverse Outcome Pathway paradigm. The development of a well-defined chemical category allows toxicity to be predicted via read-across. This is the central approach used by the OECD QSAR Toolbox. The specific work for which we were awarded the Lush Prize was for the development of such an in silico profiler for respiratory sensitisation. The profiler was developed by an analysis of the mechanistic chemistry associated with covalent bond formation in the lung. The data analysed were collated from clinical reports of occupational asthma in humans. The impact of the development of in silico profilers on the Three Rs is also discussed.
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An Overall Strategy for the Testing of Chemicals for Human Hazard and Risk Assessment under the EU REACH System

Robert Combes, Martin Barratt and Michael Balls

In its White Paper, Strategy for a Future Chemicals Policy, published in 2001, the European Commission (EC) proposed the REACH (Registration, Evaluation and Authorisation of CHemicals) system to deal with both existing and new chemical substances. This system is based on a top-down approach to toxicity testing, in which the degree of toxicity information required is dictated primarily by production volume (tonnage). If testing is to be based on traditional methods, very large numbers of laboratory animals could be needed in response to the REACH system, causing ethical, scientific and logistical problems that would be incompatible with the time-schedule envisaged for testing. The EC has emphasised the need to minimise animal use, but has failed to produce a comprehensive strategy for doing so. The present document provides an overall scheme for predictive toxicity testing, whereby the non-animal methods identified and discussed in a recent and comprehensive ECVAM document, could be used in a tiered approach to provide a rapid and scientifically justified basis for the risk assessment of chemicals for their toxic effects in humans. The scheme starts with a preliminary risk assessment process (involving available information on hazard and exposure), followed by testing, based on physicochemical properties and (Q)SAR approaches. (Q)SAR analyses are used in conjunction with expert system and biokinetic modelling, and information on metabolism and identification of the principal metabolites in humans. The resulting information is then combined with production levels and patterns of use to assess potential human exposure. The nature and extent of any further testing should be based strictly on the need to fill essential information gaps in order to generate adequate risk assessments, and should rely on non-animal methods, as far as possible. The scheme also includes a feedback loop, so that new information is used to improve the predictivity of computational expert systems. Several recommendations are made, the most important of which is that the European Union (EU) should actively promote the improvement and validation of (Q)SAR models and expert systems, and computer-based methods for biokinetic modelling, since these offer the most realistic and most economical solution to the need to test large numbers of chemicals.
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Intelligent Testing Strategies for Chemicals Testing — A Case of More Haste, Less Speed?

Robert Combes and Michael Balls

The prospects for using (Q)SAR modelling, read-across (chemical) and other non-animal approaches as part of integrated testing strategies for chemical risk assessment, within the framework of the EU REACH legislation, are considered. The potential advantages and limitations of (Q)SAR modelling and read-across methods for chemical regulatory risk assessment are reviewed. It is concluded that it would be premature to base a testing strategy on chemical-based computational modelling approaches, until such time as criteria to validate them for their reliability and relevance by using independent and transparent procedures, have been agreed. This is mainly because of inherent problems in validating and accepting (Q)SARs for regulatory use in ways that are analogous to those that have been developed and applied for in vitro tests. Until this issue has been resolved, it is recommended that testing strategies should be developed which comprise the integrated use of computational and read-across approaches. These should be applied in a cautious and judicious way, in association with available tissue culture methods, and in conjunction with metabolism and biokinetic studies. Such strategies should be intelligently applied by being driven by exposure information (based on bioavailability, not merely on production volume) and hazard information needs, in preference to a tick-box approach. In the meantime, there should be increased efforts to develop improved (Q)SARs, expert systems and new in vitro methods, and, in particular, ways to expedite their validation and acceptance must be found and prospectively agreed with all major stakeholders.
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An Overall Strategy for the Testing of Chemicals for Human Hazard and Risk Assessment under the EU REACH System

Robert Combes, Martin Barratt and Michael Balls

In its White Paper, Strategy for a Future Chemicals Policy, published in 2001, the European Commission (EC) proposed the REACH (Registration, Evaluation and Authorisation of CHemicals) system to deal with both existing and new chemical substances. This system is based on a top-down approach to toxicity testing, in which the degree of toxicity information required is dictated primarily by production volume (tonnage). If testing is to be based on traditional methods, very large numbers of laboratory animals could be needed in response to the REACH system, causing ethical, scientific and logistical problems that would be incompatible with the time-schedule envisaged for testing. The EC has emphasised the need to minimise animal use, but has failed to produce a comprehensive strategy for doing so. The present document provides an overall scheme for predictive toxicity testing, whereby the non-animal methods identified and discussed in a recent and comprehensive ECVAM document, could be used in a tiered approach to provide a rapid and scientifically justified basis for the risk assessment of chemicals for their toxic effects in humans. The scheme starts with a preliminary risk assessment process (involving available information on hazard and exposure), followed by testing, based on physicochemical properties and (Q)SAR approaches. (Q)SAR analyses are used in conjunction with expert system and biokinetic modelling, and information on metabolism and identification of the principal metabolites in humans. The resulting information is then combined with production levels and patterns of use to assess potential human exposure. The nature and extent of any further testing should be based strictly on the need to fill essential information gaps in order to generate adequate risk assessments, and should rely on non-animal methods, as far as possible. The scheme also includes a feedback loop, so that new information is used to improve the predictivity of computational expert systems. Several recommendations are made, the most important of which is that the European Union (EU) should actively promote the improvement and validation of (Q)SAR models and expert systems, and computer-based methods for biokinetic modelling, since these offer the most realistic and most economical solution to the need to test large numbers of chemicals.
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A Critical Evaluation of the 2011 ECHA Reports on Compliance with the REACH and CLP Regulations and on the Use of Alternatives to Testing on Animals for Compliance with the REACH Regulation

Horst Spielmann, Ursula G. Sauer and Ovanes Mekenyan

On 30 June 2011, the European Chemicals Agency published two reports, one on the functioning of the REACH system, the other on the use of alternatives to animal testing in compliance with that system. The data presented are based on information gained during the first registration period under the REACH system, which included high production volume chemicals and substances of very high concern, which have the most extensive information requirements. A total of 25,460 registration dossiers were received, covering 3,400 existing, so-called ‘phase-in’, substances, and 900 new, so-called ‘non-phase-in’, substances. Data sharing and the joint submission of data are reported to have worked successfully. In the registration dossiers for these substances, results from new animal tests were included for less than 1% of all the endpoints; testing proposals (required for ‘higher-tier’ information requirements) were submitted for 711 in vivo tests involving vertebrate animals. The registrants mainly used old, existing experimental data, or options for the adaptation (waiving) of information requirements, before collecting new information. For predicting substance toxicity, ‘read-across’ was the second most-used approach, followed by ‘weight-of-evidence’. In vitro toxicity tests played a minor role, and were only used when the respective test methods had gained the status of regulatory acceptance. All in all, a successful start to the REACH programme was reported, particularly since, in contrast to most predictions, it did not contribute to a significant increase in toxicity testing in animals.
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Read-across Estimates of Aquatic Toxicity for Selected Fragrances

Emiel Rorije, Tom Aldenberg and Willie Peijnenburg

Read-across as a non-animal testing alternative for the generation of risk assessment data can be useful in those cases where quantitative structure–activity relationship (QSAR) models are not available, or are less well developed. This paper provides read-across case studies for the estimation of the aquatic toxicity of five different fragrance substances, and proposes a pragmatic approach for expressing uncertainty in read-across estimates. The aquatic toxicity estimates and their uncertainties are subsequently used to estimate fresh water compartment Predicted No-Effect Concentrations (PNECs), with their two-sided 90% Confidence Intervals (CIs). These PNECs can be used directly in risk assessment. The results of the musk fragrance read-across cases (musk xylene, musk ketone and galaxolide) are compared to experimentally derived PNEC values. The read-across estimates made by using similarity in a hypothesised mechanism of action for (acute) toxicity of musk xylene gave a PNEC of 2μg/L (90% CI 0.0004–13.5μg/L) with the Species Sensitivity Distribution (SSD) approach. This estimated value is 1.8 times above the experimentally-based fresh water PNEC of 1.1μg/L. For musk ketone and galaxolide, the PNEC values based on the SSD approach and employing a toxicity mechanism-based read-across were 2.0 times greater, and 4.9 times below the experimentally derived PNEC values, respectively.
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