£125.91

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Springer Advances in Computational Toxicology - Regulatory Science Methods

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Description

This comprehensive book from Springer explores both established and innovative methodologies in computational toxicology, with a specific focus on regulatory decision-making applications. Written by experts from leading organisations including the FDA, NCATS, and NIEHS, alongside industry professionals and academic researchers, the volume delivers real-world insights into current computational toxicology practices. The book covers molecular modelling, molecular dynamics simulations, and machine learning methods for toxicity analysis, providing practical knowledge for regulatory scientists, researchers, and professionals seeking to understand how computational approaches are applied in toxicological assessment and compliance frameworks.

Key Features

Comprehensive review of traditional and cutting-edge computational toxicology methodologies applicable to regulatory science.

Real-world experience shared by contributing authors from FDA, NCATS, NIEHS and leading academic and industry institutions.

Covers molecular modelling and molecular dynamics simulations as core computational toxicology techniques.

Includes machine learning methods for toxicity analysis and predictive modelling in regulatory contexts.

Part of Springer's Challenges and Advances in Computational Chemistry and Physics series, volume 30.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
14 August 2020
Listed Since
09 July 2020

Barcode

No barcode data available

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