By Mark T D Cronin; Judith C Madden
ISBN-10: 1849730040
ISBN-13: 9781849730044
ISBN-10: 1849732094
ISBN-13: 9781849732093
Content material: creation; part 1: Compiling the version; assets of Toxicity facts for In Silico Toxicology; Calculation of Physico-Chemical homes; Calculation of Theoretical 2-D Descriptors; Calculation of Molecular Orbital Descriptors; QSAR tools: Receptor Modelling in Toxicology; comparing information caliber; part 2: info Integration, research and Utilisation; QSAR equipment: Statistical Methodologies; Characterisation, assessment and attainable Validation of a QSAR; Applicability area Mechanisms of poisonous motion in In Silico Toxicology; Formation of different types; Read-Across Endpoint-Based Extrapolation; position of publicity in Modelling; professional platforms instruments for type Formation and Read-Across; part three: program of In Silico Toxicology to possibility review; Weight of facts in Toxicity Prediction; built-in checking out innovations; Case learn: Predicting Environmental Toxicity; Case examine: Predicting Human future health; In Silico Toxicology in chance overview
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Additional info for In silico toxicology : principles and applications
Example text
SARs and categories will be well-supported and populated, and may even allow for local models and read-across to be performed.
In the context of in silico approaches to predict toxicity, data are required to develop and evaluate models. The purpose of this chapter is to inform the reader how to compile toxicological data and information for the development of in silico models for toxicity prediction. 2 Which Data Can be Used for In Silico Modelling? Two types of data are usually required to develop an in silico model for the effect of a chemical: Data relating to the description of chemical structure and/or properties.
The factors that dictate its toxicokinetic profile). Many models exist to predict oral, dermal or inhalational uptake of compounds to determine whether or not they are likely to enter the body; there are also a small number of models to predict distribution. Metabolism is the most studied of all ADME endpoints as it plays a central role in determining biological effects. Metabolism may render a potentially toxic parent compound non-toxic or may convert a non-toxic parent into a highly reactive or toxic metabolite, the toxicity of which will need additional consideration.
In silico toxicology : principles and applications by Mark T D Cronin; Judith C Madden
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