Computational Toxicology

A key resource for toxicologists across a broad spectrum of fields, this book offers a comprehensive analysis of molecular modelling approaches and strategies applied to risk assessment for pharmaceutical and environmental chemicals. • Provides a perspective of what is currently achievable with computational toxicology and a view to future developments • Helps readers overcome questions of data sources, curation, treatment, and how to model / interpret critical endpoints that support 21st century hazard assessment • Assembles cutting-edge concepts and leading authors into a unique

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

This volume explores techniques that are currently used to understand solid target-specific models in computational toxicology. The chapters are divided into four sections and discuss topics such as molecular descriptors, QSAR and read-across; molecular and data modeling techniques to comply with both scientific and regulatory sides; computational toxicology in drug discovery; and strategies on how to predict various human-health toxicology endpoints. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists

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

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

The network approaches of systems pharmacology and toxicology serve as early predictors of the most relevant screening approach to pursue both in drug discovery and development and ecotoxicological assessments. Computational approaches have the potential to improve toxicological experimental design, enable more rapid drug efficacy and safety testing and also reduce the number of animals used in experimentation. Rapid advances in availability of computing technology hold tremendous promise for advancing applied and basic science and increasing the efficiency of risk assessment.

Computational Toxicology: Methods and Applications for Risk Assessment is an essential reference on the translation of computational toxicology data into information that can be used for more informed risk assessment decision-making. This book is authored by leading international investigators who have real-world experience in relating computational toxicology methods to risk assessment. Key topics of interest include QSAR modeling, chemical mixtures, applications to metabolomic and metabonomic data sets, toxicogenomic analyses, applications to REACH informational strategies and much more. The examples provided

Computational Toxicology: Methods and Applications for Risk Assessment is an essential reference on the translation of computational toxicology data into information that can be used for more informed risk assessment decision-making. This book is authored by leading international investigators who have real-world experience in relating computational toxicology methods to risk assessment. Key topics of interest include QSAR modeling, chemical mixtures, applications to metabolomic and metabonomic data sets, toxicogenomic analyses, applications to REACH informational strategies and much more. The examples provided

The focus of the chapter is on the development and application of computational toxicology methods to human risk assessment. The various CompTox methods are defined, and a brief history of their development and applications in risk assessment is provided. The technological, economic, and public health concerns driving the development of the methods are described, along with how the specific forces shaped the historical and current use of CompTox methods in risk assessment. Translation research programs in the United States and

The remarkable advances of high-performance computing to facilitate and increase efficiency in helping to resolve or support assessments on the toxic effects of chemicals on tissues and genomic material have led to development of novel in silico methods. These methods can support risk assessment via integration of study data that can be translated into meaningful predictive information. This chapter describes some methods in computational toxicology and how to integrate experimental data with computational assessments for supporting risk assessment.

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