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Computational Toxicology: Risk Assessment for Pharmaceutical and Environmental Chemicals, 2nd Edition
Ekins
ISBN: 978-1-119-28256-3
Hardcover
608 pages
November 2018, ©2017
This is an out of stock title.
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Praise for the first edition:

Computational Toxicology brings together, in an organized and competent manner, the current state of quantitative experimental toxicology.” - International Journal of Toxicology

“…an excellent resource on state-of-art and emerging computer-based technologies for the assessment of toxicity via pharmaceutical or environmental agents." - Journal of Medicinal Chemistry

"This is an impressive and timely contribution to an important medical and environmental field." - Computing Reviews

Continuing and enhancing the legacy of its predecessor, the 2nd edition of Computational Toxicology: Risk Assessment for Pharmaceutical and Environmental Chemicals offers a comprehensive analysis of applied approaches and strategies. The book begins with an introduction to toxicology and relevant technologies and then addresses the most advanced currently avail­able molecular-modelling software and its role in toxicity testing.

As in the first edition, the chapters feature in-depth looks at QSAR models, physicochemical drug properties, structure-based drug targeting, chemical mixture assessments, and environmental modelling. Additional coverage new to this edition includes consumer product safety assessment and chemical defense, along with chapters on open source toxicology and big data.

An important resource for researchers and regulators involved in toxicology and risk assessment, Computational Toxicology, 2nd Edition :

•          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 and powerful single-source reference
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