Informationen zum Autor Mark Cronin is Professor of Predictive Toxicology at the Liverpool John Moores University. He has a BSc in Applied Biology and a PhD in Environmental QSAR and has co-edited 1 book and over 150 papers. He was the co-organiser of the 11th International Workshop on the Human Health and Environmental Sciences, Liverpool, May 2004 as well as a number of one day meetings at the Society of Chemical Industry, London. Judith Madden is a Senior Lecturer in Pharmaceutical and Chemical Sciences at the Liverpool John Moores University. She has a BSc in Chemistry and Pharmacology and a PhD in QSAR and Drug Design and over 25 publications to her name. She was the co-organiser of the 11th International Workshop on the Human Health and Environmental Sciences, Liverpool, May 2004 and the SETAC-UK Annual Meeting, Liverpool, September 2006. Klappentext In silico methods to predict toxicity are becoming increasingly important, particularly in light of European legislation such as REACH and the Cosmetics Regulation. They are also being used extensively worldwide e.g. in the USA, Canada, Japan and Australia. The objective of In Silico Toxicology: Principles and Applications is to enable the reader to develop new, and use existing, in silico methods to predict the toxicity and fate of chemicals. It develops the theme in a logical sequence leading the user through the retrieval, and assessment of quality, of toxicological data and information; the calculation of descriptors and properties; the basis of statistical techniques for quantitative structure-activity relationships (QSARs); the interpretation and validation of models for regulatory use; the mechanistic basis to modelling; as well as chemical grouping approaches and application of the models for risk assessment. The book also addresses other aspects of in silico toxicology including how to predict both external and internal exposure and the role of in silico approaches in integrated testing strategies. The contributions from recognised leaders in each of these areas include evidence of the use and applicability of approaches using real world case studies concerning both environmental and human health effects. The book is relevant to toxicologists and modellers using in silico toxicological approaches to perform risk assessment for regulatory purposes and product development. Zusammenfassung This book defines the use of computational approaches to predict the environmental toxicity and human health effects of organic chemicals. Inhaltsverzeichnis Introduction; Section 1: Compiling the Model; Sources of Toxicity Data for In Silico Toxicology; Calculation of Physico-Chemical Properties; Calculation of Theoretical 2-D Descriptors; Calculation of Molecular Orbital Descriptors; QSAR Methods: Receptor Modelling in Toxicology; Evaluating Data Quality; Section 2: Data Integration, Analysis and Utilisation; QSAR Methods: Statistical Methodologies; Characterisation, Evaluation and Possible Validation of a QSAR; Applicability Domain Mechanisms of Toxic Action in In Silico Toxicology; Formation of Categories; Read-Across Endpoint-Based Extrapolation; Role of Exposure in Modelling; Expert Systems Tools for Category Formation and Read-Across; Section 3: Application of In Silico Toxicology to Risk Assessment; Weight of Evidence in Toxicity Prediction; Integrated Testing Strategies; Case Study: Predicting Environmental Toxicity; Case Study: Predicting Human Health; In Silico Toxicology in Risk Assessment...

Klappentext

In silico methods to predict toxicity are becoming increasingly important, particularly in light of European legislation such as REACH and the Cosmetics Regulation. They are also being used extensively worldwide e.g. in the USA, Canada, Japan and Australia. The objective of In Silico Toxicology: Principles and Applications is to enable the reader to develop new, and use existing, in silico methods to predict the toxicity and fate of chemicals. It develops the theme in a logical sequence leading the user through the retrieval, and assessment of quality, of toxicological data and information; the calculation of descriptors and properties; the basis of statistical techniques for quantitative structure-activity relationships (QSARs); the interpretation and validation of models for regulatory use; the mechanistic basis to modelling; as well as chemical grouping approaches and application of the models for risk assessment. The book also addresses other aspects of in silico toxicology including how to predict both external and internal exposure and the role of in silico approaches in integrated testing strategies. The contributions from recognised leaders in each of these areas include evidence of the use and applicability of approaches using real world case studies concerning both environmental and human health effects. The book is relevant to toxicologists and modellers using in silico toxicological approaches to perform risk assessment for regulatory purposes and product development.

Zusammenfassung
This book defines the use of computational approaches to predict the environmental toxicity and human health effects of organic chemicals.

Inhalt

Introduction; Section 1: Compiling the Model; Sources of Toxicity Data for In Silico Toxicology; Calculation of Physico-Chemical Properties; Calculation of Theoretical 2-D Descriptors; Calculation of Molecular Orbital Descriptors; QSAR Methods: Receptor Modelling in Toxicology; Evaluating Data Quality; Section 2: Data Integration, Analysis and Utilisation; QSAR Methods: Statistical Methodologies; Characterisation, Evaluation and Possible Validation of a QSAR; Applicability Domain Mechanisms of Toxic Action in In Silico Toxicology; Formation of Categories; Read-Across Endpoint-Based Extrapolation; Role of Exposure in Modelling; Expert Systems Tools for Category Formation and Read-Across; Section 3: Application of In Silico Toxicology to Risk Assessment; Weight of Evidence in Toxicity Prediction; Integrated Testing Strategies; Case Study: Predicting Environmental Toxicity; Case Study: Predicting Human Health; In Silico Toxicology in Risk Assessment