This book provides a comprehensive review of both traditional and cutting-edge methodologies that are currently used in computational toxicology and specifically features its application in regulatory decision making. The authors from various government agencies such as FDA, NCATS and NIEHS industry, and academic institutes share their real-world experience and discuss most current practices in computational toxicology and potential applications in regulatory science. Among the topics covered are molecular modeling and molecular dynamics simulations, machine learning methods for toxicity analysis, network-based approaches for the assessment of drug toxicity and toxicogenomic analyses. Offering a valuable reference guide to computational toxicology and potential applications in regulatory science, this book will appeal to chemists, toxicologists, drug discovery and development researchers as well as to regulatory scientists, government reviewers and graduate students interested in this field.

This book provides a comprehensive review of both traditional and cutting-edge methodologies that are currently used in computational toxicology and specifically features its application in regulatory decision making. The authors from various government agencies such as FDA, NCATS and NIEHS industry, and academic institutes share their real-world experience and discuss most current practices in computational toxicology and potential applications in regulatory science. Among the topics covered are molecular modeling and molecular dynamics simulations, machine learning methods for toxicity analysis, network-based approaches for the assessment of drug toxicity and toxicogenomic analyses. Offering a valuable reference guide to computational toxicology and potential applications in regulatory science, this book will appeal to chemists, toxicologists, drug discovery and development researchers as well as to regulatory scientists, government reviewers and graduate students interested in this field.

Rapid advances in computer science, biology, chemistry, and other disciplines are enabling powerful new computational tools and models for toxicology and pharmacology. These computational tools hold tremendous promise for advancing science, from streamlining drug efficacy and safety testing, to increasing the efficiency and effectiveness of risk assessment for environmental chemicals. Computational Toxicology provides biomedical and quantitative scientists with essential background, context, examples, useful tips, and an overview of current developments in the field. Divided into four sections, Volume I covers a wide array of methodologies and topics. Opening with an introduction to the field of computational toxicology and its current and potential applications, the volume continues with 'best practices' in mathematical and computational modeling, followed by chemoinformatics and the use of computational techniques and databases to predict chemical properties and toxicity, as well as an overview of molecular dynamics. The final section is a compilation of the key elements and main approaches used in pharmacokinetic and pharmacodynamic modeling, including the modeling of absorption, compartment and non-compartmental modeling, physiologically based pharmacokinetic modeling, interspecies extrapolation, and population effects. Written in the successful Methods in Molecular BiologyTM series format where possible, chapters include introductions to their respective topics, lists of the materials and software tools used, methods, and notes on troubleshooting. Authoritative and easily accessible, Computational Toxicology will allow motivated readers to participate in this exciting field and undertake a diversity of realistic problems of interest.

This resource features essential background, context, examples, useful tips, and an overview of current developments in the field. It includes cutting-edge methods and protocols as well as implementation advice from the experts.

Rapid advances in computer science, biology, chemistry, and other disciplines are enabling powerful new computational tools and models for toxicology and pharmacology. These computational tools hold tremendous promise for advancing science, from streamlining drug efficacy and safety testing, to increasing the efficiency and effectiveness of risk assessment for environmental chemicals. Computational Toxicology provides biomedical and quantitative scientists with essential background, context, examples, useful tips, and an overview of current developments in the field. Divided into four sections, Volume I covers a wide array of methodologies and topics. Opening with an introduction to the field of computational toxicology and its current and potential applications, the volume continues with ’best practices’ in mathematical and computational modeling, followed by chemoinformatics and the use of computational techniques and databases to predict chemical properties and toxicity, as well as an overview of molecular dynamics. The final section is a compilation of the key elements and main approaches used in pharmacokinetic and pharmacodynamic modeling, including the modeling of absorption, compartment and non-compartmental modeling, physiologically based pharmacokinetic modeling, interspecies extrapolation, and population effects. Written in the successful Methods in Molecular BiologyTM series format where possible, chapters include introductions to their respective topics, lists of the materials and software tools used, methods, and notes on troubleshooting. Authoritative and easily accessible, Computational Toxicology will allow motivated readers to participate in this exciting field and undertake a diversity of realistic problems of interest.

A comprehensive analysis of state-of-the-art molecular modeling approaches and strategies applied to risk assessment for pharmaceutical and environmental chemicals This unique volume describes how the interaction of molecules with toxicologically relevant targets can be predicted using computer-based tools utilizing X-ray crystal structures or homology, receptor, pharmacophore, and quantitative structure activity relationship (QSAR) models of human proteins. It covers the in vitro models used, newer technologies, and regulatory aspects. The book offers a complete systems perspective to risk assessment prediction, discussing experimental and computational approaches in detail, with: * An introduction to toxicology methods and an explanation of computational methods * In-depth reviews of QSAR methods applied to enzymes, transporters, nuclear receptors, and ion channels * Sections on applying computers to toxicology assessment in the pharmaceutical industry and in the environmental arena * Chapters written by leading international experts * Figures that illustrate computational models and references for further information This is a key resource for toxicologists and scientists in the pharmaceutical industry and environmental sciences as well as researchers involved in ADMET, drug discovery, and technology and software development.

CHEMOMETRICS AND CHEMINFORMATICS IN AQUATIC TOXICOLOGY Explore chemometric and cheminformatic techniques and tools in aquatic toxicology Chemometrics and Cheminformatics in Aquatic Toxicology delivers an exploration of the existing and emerging problems of contamination of the aquatic environment through various metal and organic pollutants, including industrial chemicals, pharmaceuticals, cosmetics, biocides, nanomaterials, pesticides, surfactants, dyes, and more. The book discusses different chemometric and cheminformatic tools for non-experts and their application to the analysis and modeling of toxicity data of chemicals to various aquatic organisms. You’ll learn about a variety of aquatic toxicity databases and chemometric software tools and webservers as well as practical examples of model development, including illustrations. You’ll also find case studies and literature reports to round out your understanding of the subject. Finally, you’ll learn about tools and protocols including machine learning, data mining, and QSAR and ligand-based chemical design methods. Readers will also benefit from the inclusion of: A thorough introduction to chemometric and cheminformatic tools and techniques, including machine learning and data mining An exploration of aquatic toxicity databases, chemometric software tools, and webservers Practical examples and case studies to highlight and illustrate the concepts contained within the book A concise treatment of chemometric and cheminformatic tools and their application to the analysis and modeling of toxicity data Perfect for researchers and students in chemistry and the environmental and pharmaceutical sciences, Chemometrics and Cheminformatics in Aquatic Toxicology will also earn a place in the libraries of professionals in the chemical industry and regulators whose work involves chemometrics.