Advances in Computational Toxicology: Methodologies and Applications in Regulatory Science

Description

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. Front Matter ....Pages i-xvii Computational Toxicology Promotes Regulatory Science (Rebecca Kusko, Huixiao Hong)....Pages 1-11 Front Matter ....Pages 13-13 Background, Tasks, Modeling Methods, and Challenges for Computational Toxicology (Zhongyu Wang, Jingwen Chen)....Pages 15-36 Modelling Simple Toxicity Endpoints: Alerts, (Q)SARs and Beyond (Richard Williams, Martyn Chilton, Donna Macmillan, Alex Cayley, Lilia Fisk, Mukesh Patel)....Pages 37-55 Matrix and Tensor Factorization Methods for Toxicogenomic Modeling and Prediction (Suleiman A. Khan, Tero Aittokallio, Andreas Scherer, Roland Grafström, Pekka Kohonen)....Pages 57-74 Cardio-oncology: Network-Based Prediction of Cancer Therapy-Induced Cardiotoxicity (Feixiong Cheng)....Pages 75-97 Mode-of-Action-Guided, Molecular Modeling-Based Toxicity Prediction: A Novel Approach for In Silico Predictive Toxicology (Ping Gong, Sundar Thangapandian, Yan Li, Gabriel Idakwo, Joseph Luttrell IV, Minjun Chen et al.)....Pages 99-118 A Review of Feature Reduction Methods for QSAR-Based Toxicity Prediction (Gabriel Idakwo, Joseph Luttrell IV, Minjun Chen, Huixiao Hong, Ping Gong, Chaoyang Zhang)....Pages 119-139 An Overview of National Toxicology Program’s Toxicogenomic Applications: DrugMatrix and ToxFX (Daniel L. Svoboda, Trey Saddler, Scott S. Auerbach)....Pages 141-157 A Pair Ranking (PRank) Method for Assessing Assay Transferability Among the Toxicogenomics Testing Systems (Zhichao Liu, Brian Delavan, Liyuan Zhu, Ruth Robert, Weida Tong)....Pages 159-180 Applications of Molecular Dynamics Simulations in Computational Toxicology (Sugunadevi Sakkiah, Rebecca Kusko, Weida Tong, Huixiao Hong)....Pages 181-212 Front Matter ....Pages 213-213 Applicability Domain: Towards a More Formal Framework to Express the Applicability of a Model and the Confidence in Individual Predictions (Thierry Hanser, Chris Barber, Sébastien Guesné, Jean François Marchaland, Stéphane Werner)....Pages 215-232 Application of Computational Methods for the Safety Assessment of Food Ingredients (Patra Volarath, Yu (Janet) Zang, Shruti V. Kabadi)....Pages 233-257 Predicting the Risks of Drug-Induced Liver Injury in Humans Utilizing Computational Modeling (Minjun Chen, Jieqiang Zhu, Kristin Ashby, Leihong Wu, Zhichao Liu, Ping Gong et al.)....Pages 259-278 Predictive Modeling of Tox21 Data (Ruili Huang)....Pages 279-297 In Silico Prediction of the Point of Departure (POD) with High-Throughput Data (Dong Wang)....Pages 299-313 Molecular Modeling Method Applications: Probing the Mechanism of Endocrine Disruptor Action (Xianhai Yang, Huihui Liu, Rebecca Kusko)....Pages 315-335 Xenobiotic Metabolism by Cytochrome P450 Enzymes: Insights Gained from Molecular Simulations (Zhiqiang Fu, Jingwen Chen)....Pages 337-364 Integrating QSAR, Read-Across, and Screening Tools: The VEGAHUB Platform as an Example (Emilio Benfenati, Alessandra Roncaglioni, Anna Lombardo, Alberto Manganaro)....Pages 365-381 OpenTox Principles and Best Practices for Trusted Reproducible In Silico Methods Supporting Research and Regulatory Applications in Toxicological Science (Barry Hardy, Daniel Bachler, Joh Dokler, Thomas Exner, Connor Hardy, Weida Tong et al.)....Pages 383-403 Back Matter ....Pages 405-412