In Silico Methods for Predicting Drug Toxicity

by Emilio Benfenati

Overview

This detailed volume explores in silico methods for pharmaceutical toxicity by combining the theoretical advanced research with the practical application of the tools. Beginning with a section covering sophisticated models addressing the binding to receptors, pharmacokinetics and adsorption, metabolism, distribution, and excretion, the book continues with chapters delving into models for specific toxicological and ecotoxicological endpoints, as well as broad views of the main initiatives and new perspectives which will very likely improve our way of modelling pharmaceuticals. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that is key for achieving successful research results.

Authoritative and practical, In Silico Methods for Predicting Drug Toxicity offers the advantage of incorporating data and knowledge from different fields, such as chemistry, biology, -omics, and pharmacology, to achieve goals in this vital area of research.

Product Details

ISBN-13:	9781493980932
Publisher:	Springer New York
Publication date:	05/30/2018
Series:	Methods in Molecular Biology , #1425
Edition description:	Softcover reprint of the original 1st ed. 2016
Pages:	534
Product dimensions:	7.01(w) x 10.00(h) x (d)

Table of Contents

QSAR Methods.- PBPK Modeling to Simulate the Fate of Compounds in Living Organisms.- Pharmacokinetic Tools and Applications.- In Silico Tools and Software to Predict ADMET of New Drug Candidates.- Development of In Silico Methods for Toxicity Prediction in Collaboration between Academia and the Pharmaceutical Industry.- Emerging Bioinformatics Methods and Resources in Drug Toxicology.- In Silico Prediction of Chemically-Induced Mutagenicity: A Weight of Evidence Approach Integrating Information from QSAR Models and Read-Across Predictions.- In Silico Methods for Chromosome Damage.- In Silico Methods for Carcinogenicity Assessment.- In Silico Models for Developmental Toxicity.- In Silico Models for Repeated-Dose Toxicity (RDT): Prediction of the No Observed Adverse Effect Level (NOAEL) and Lowest Observed Adverse Effect Level (LOAEL) for Drugs.- In Silico Models for Predicting Acute Systemic Toxicity.- In Silico Models for Skin Sensitization and Irritation.- In Silico Models for Hepatotoxicity.- Machine Learning Models for Predicting Liver Toxicity.- Implementation of In Silico Toxicology Prools in Leadscope.- Use of Lhasa Limited Products for the In Silico Prediction of Drug Toxicity.- Using VEGAHUB within a Weight-of-Evidence Strategy.- MultiCASE Platform for In Silico Toxicology.- Adverse Outcome Pathways as Versatile Tools in Liver Toxicity Testing.- The Use of In Silico Methods for the Regulatory Toxicological Assessment of Pharmaceutical Impurities.- Computational Modeling of Mixture Toxicity.- In Silico Methods for Ecological Risk Assessment: Principles, Tiered Approaches, Applications, and Future Perspectives.- Increasing the Value of Data within a Large Pharmaceutical Company through In Silico Models.