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- Bassan, A
- Cronin, M
- Hardy, B
- Helma, C
- Hopfinger, T
- Judson, P
- Leahy, D
- Madden, J
- Michielan, L
- Narayanan, D
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- Thomas, S
- Zamora, I
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Arianna Bassan received her undergraduate degree in chemistry at the University of Padova (Italy). In 2004, she received her PhD degree in computational chemistry at Stockholm University (Sweden). Afterwards she was a research fellow at Stockholm University and then in 2005 she joined the European Commission as Scientific Officer in the computational toxicology group at the Joint Research Centre (Ispra, Italy). Her work at the European Commission involved the development of a step-wise approach for the generation and use of in silico data in a regulatory framework. She also was involved in a number of projects aimed at implementing novel (Q)SAR IT tools for toxicity predictions. At the end of 2007 she joined the Merck Research Laboratories (Pomezia, Italy) as Project Information Officer, liaising between scientists and IT to set-up data analysis, and to check and clear all their chemical and biological information. At the end of 2008, she started to work for S-IN (Vicenza, Italy), a company that provides customised computer-assisted solutions in chemistry-related frameworks, where she is responsible for services aimed at profiling chemical hazards in regulatory frameworks. S-IN expertise lies both in the use (and knowledge) of a wide array of in silico methodologies, approaches and tools and in the development of algorithms, interfaces, tools, automated procedures and databases for specific chemistry-related needs. S-IN offers a variety of software solutions and services in several areas of Research, Development and Production, including: cheminformatics, info- and chemo-metrics, and bioinformatics.
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Application of Structure-Activity Relationships in REACH-compliant Chemical Hazard Assessment
Arianna Bassan (S-IN)
This training session focuses on the possible use of non-testing methods in the regulatory assessment of chemicals especially in relation to the REACH legislation, which came into force in Europe on 1st June 2007. This new EU regulatory framework aims at improving the protection of human health and environment through the better and earlier identification of the properties of chemical substances.
In the regulatory framework there is a growing need for in silico methods that can be used to gain information about the environmental fate and ecological and health effects of chemicals. The different techniques that are used to derive non-testing information include (quantitative) structure-activity relationship models, expert systems, and read-across/category approaches. National and international agencies have a number of reasons to encourage the use of in silico methods. First of all, computational methods are faster and cheaper compared to empirical testing methods, and their use results in considerable savings of time and money during the assessment of chemical hazard. To limit the cost and the number of animals used for testing, REACH explicitly encourages the use of computer-aided methods such as (Q)SAR methods and category/read-across approaches for filling in the enormous knowledge gap of chemical information. In order to be used in place of experimental data, REACH requires that the in silico methods meet certain conditions. For example, in the case of (Q)SARs, these requirements include: 1) the model has to be valid; 2) the substance has to fall within the applicability domain; 3) the prediction has to be adequate for the regulatory purpose; 4) the applied method has to be provided with adequate and reliable documentation.
The use of in silico methods, and in particular, (Q)SARs, as valuable components of the regulatory assessment strategy is hampered by two major factors. First, model estimations can be properly interpreted only by specialists with specific expertise in the field of computational toxicology, and this factor certainly limits the widespread use of in silico approaches for regulatory purposes. Second, for a method to be accepted in a regulatory framework, its scientific validity has to be established in accordance with internationally agreed validation principles. At present the scientific validity of many models is not documented, which then limits their regulatory acceptance.
In this training session, the following topics will be presented and discussed:
* Introduction on the REACH regulation (and in particular Annex XI) and the OECD Principles for (Q)SAR Validation.
* Regulatory use of QSARs in the REACH framework
* Reporting Formats (e.g. QSAR Model Reporting Format, QMRF) for providing adequate documentation about the models.
* Structured workflow that assists users all the way through the generation of reliable non-testing data and by aiding the following processes:
- Retrieving existing physicochemical properties and (eco)toxicological information for a given chemical.
- Selecting relevant in silico approaches for predicting individual toxic endpoints.
- Generating endpoint predictions.
- Providing information on the reliability of the estimates.
- Exploiting the capability of various in silico methodologies.
- Integrating results.
- Compiling robust summaries that document in a transparent way the use of the methods.
* Review of computational tools for applying (Q)SARs.
* Hands-on session (e.g. use of selected tools such as Toxmatch).
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