472 pages | 80 B/W Illus.
Quantitative Structure-Activity Relationships (QSARs) are increasingly used to predict the harmful effects of chemicals to humans and the environment. The increased use of these methods in a variety of areas (academic, industrial, regulatory) results from a realization that very little toxicological or fate data is available on the vast amount of chemicals to which humans and the environment are exposed.
Predicting Chemical Toxicity and Fate provides a comprehensive explanation of the state-of-the-art methods that are available to predict the effects of chemicals on humans and the environment. It describes the use of predictive methods to estimate the physiochemical properties, biological activities, and fate of chemicals. The methods described may be used to predict the properties of drugs before their development, and to predict the environmental effects of chemicals. These methods also reduce the cost of product development and the need for animal testing.
This book fills an obvious need by providing a comprehensive explanation of these prediction methods. It is a practical book that illustrates the use of these techniques in real life scenarios. This book will demystify QSARs for those students unsure of them, and professionals in environmental toxicology and chemistry will find this a useful reference in their everyday working lives.
"This book provides a comprehensive explanation of the state-of-the-art methods that are available to predict the effects of chemicals on humans and the environment. … The book fills an obvious need by providing a comprehensive explanation of these prediction methods. It is a practical book that illustrates the use of these techniques in real life scenarios. It will demystify QSARs for those students unsure of the them, and professionals in environmental toxicology and chemistry will find this a useful reference in their everyday working lives."
- International Pest Control, Vol. 47, No. 2, March/April 2005
"The authors and editors have done a fine job in presenting a well balanced view of the early development, current status and future uses of predictive models/(Q)SARs for use in both human health assessments and environmental assessments. … Anyone interested in predictive modelling of mammalian toxicity and environmental effects should consider this book … ."
- BTS Newsletter, Winter 2004, Issue 25
"This choice [of contributors] provides a refreshing outlook on certain topics… we learn what research has been done, what needs most to be done, and why successes have been limited. This is exactly the sort of state-of-the-art description an overview volume should provide."
- Journal of Medicinal Chemistry, Vol. 48, No. 13, 2005
Predicting Chemical Toxicity and Fate in Humans and the Environment - An Introduction
Toxicity Data Sources
Calculation of Physicochemical Properties
Good Practice in Physicochemical Property Prediction
Whole Molecule and Atom Based Topological Descriptors
Quantum Chemical Descriptors in Structure-Activity Relationships - Calculation, Interpretation and comparison of Methods
Building QSAR Models - A Practical Guide
QSARs FOR HUMAN HEALTH ENDPOINTS
Prediction of Human Health Endpoints: Mutagenicity and Carcinogenicity
The Use of Expert Systems for Toxicity Prediction - Illustrated with Reference to the DEREK Program
Computer-Based Methods for the Prediction of Chemical Metabolism and Biotransformation within Biological Organisms
Prediction of Pharmacokinetic Parameters in Drug Design and Toxicology
QSARs FOR ENVIRONMENTAL TOXICITY AND FATE
An Exercise in External Validation: The Benzene Response-Surface Model for Tetrahymena Toxicity
Receptor-Mediated Toxicity: QSARs for Oestrogen Receptor Binding and Priority Setting of Potential Oestrogenic Endocrine Disruptors
Prediction of Persistence
QSAR Modelling of Bioaccumulation
QSAR Modelling of Soil Sorption
Application of Catabolic-Based Biosensors to Develop QSARs for Degradation
The Tiered Approach to Toxicity Assessment Based on the Integrated Use of Alternative (Non-Animal) Tests
The Use of Quantitative Structure-Activity Relationships and Expert Systems to Predict Toxicity by Governmental Regulatory Agencies
A Framework for Promoting the Acceptance and Regulatory Use of (Quantitative) Structure-Activity Relationships.