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|Title:||Computational Tools for Regulatory Needs|
|Authors:||WORTH ANDREW; BASSAN Arianna|
|Type:||Articles in periodicals and books|
|Abstract:||In the regulatory framework there is a growing need for in silico methods that can be used to gain information about environmental fate, and ecological and health effects of chemicals. Computer-aided toxicity prediction mainly makes use of the relationship between chemical structure and biological activity to compute (eco)toxicity and fate of chemicals (e. g., physicochemical properties, toxicological activity, distribution, and fate), thus generating non-testing data regarding the effects of the chemicals on man and the environment. The different techniques that are used to derive non-testing information include (Quantitative) Structure Activity Relationship models, expert systems, and read-across/category approaches. These “non-testing methods” rely on the idea that the biological activity of the chemical depends on its intrinsic nature and it can be directly inferred from its molecular structure and the properties of similar compounds whose activities are known. In principle, non-testing methods can be applied at different stages in the development and registration of chemicals, from in-house research and development to the compilation of dossiers on chemical safety for submission to regulatory authorities. In practise, the ways in which these approaches are used depends on the requirements of the specific legislation and the possibilities offered by regulatory authorities. This chapter focuses on the use of non-testing methods in the regulatory assessment of chemicals. A brief explanation is provided of the main types of non-testing methods, and reference is made to the use these methods in the European Union (EU), as foreseen by the REACH legislation. The uptake of non-testing methods in the EU is an example of a trend across many countries within the Organisation for Economic Cooperation and Development (OECD).The need to use non-testing methods has led to the development and implementation of Integrated Testing Strategies (ITS) based as far as possible on the use of non-testing data . The use of non-testing methods within such strategies implies the need for computational tools to facilitate the entire workflow. This chapter presents the views of the authors on the main functionalities that should be incorporated into a Decision Support System (DSS), to facilitate the implementation of this workflow. Such a DSS is intended to be useful in any regulatory context.|
|JRC Institute:||Institute for Health and Consumer Protection Historical Collection|
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