Benfenati In Silico Methods for Predicting Drug Toxicity

1. Auflage 2016
ISBN: 978-1-4939-3609-0
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 1425, 534 Seiten, eBook

Reihe: Methods in Molecular Biology

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.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Benfenati, Emilio

Inhaltsverzeichnis

QSAR Methods.- In
Silico 3D-Modelling of Binding Activities.- Modeling Pharmacokinetics.- Modeling
ADMET.- In Silico Prediction of Chemically-Induced Mutagenicity: How to Use
QSAR Models and Interpret Their Results.- In Silico Methods for Carcinogenicity
Assessment.- VirtualToxLab: Exploring the Toxic Potential of Rejuvenating
Substances Found in Traditional Medicines.- In Silico Model for Developmental
Toxicity: How to Use QSAR Models and Interpret Their Results.- 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 Acute Systemic Toxicity.- In Silico Models forHepatotoxicity.-
In Silico Models for Ecotoxicity of Pharmaceuticals.- Use of Read-Across Tools.-
Adverse Outcome Pathways as Tools to Assess Drug-Induced Toxicity.- A Systems
Biology Approach for Identifying Hepatotoxicant Groups Based on Similarity in
Mechanisms of Action and Chemical Structure.- In Silico Study of In Vitro GPCR
Assays by QSAR Modeling.- Taking Advantage of Databases.- QSAR Models at the
United States FDA/NCTR.- A Round Trip from Medicinal Chemistry to Predictive
Toxicology.- The Use of In Silico Models Within a Large Pharmaceutical Company.-
The Consultancy Activity on In Silico Models for Genotoxic Prediction of
Pharmaceutical Impurities.