In Silico Methods for Predicting Drug Toxicity / edited by Emilio Benfenati.

Format:

Book

Contributor:

Benfenati, Emilio, Editor.

SpringerLink (Online service)

Series:

Springer Protocols (Springer-12345)

Methods in molecular biology 1940-6029 ; 2425

Methods in Molecular Biology, 1940-6029 ; 2425

Language:

English

Subjects (All):

Toxicology.

Pharmacology.

Computer simulation.

Computer Modelling.

Local Subjects:

Toxicology.

Pharmacology.

Computer Modelling.

Physical Description:

1 online resource (XIV, 680 pages) : 244 illustrations, 215 illustrations in color.

Edition:

2nd ed. 2022.

Contained In:

Springer Nature eBook

Place of Publication:

New York, NY : Springer US : Imprint: Humana, 2022.

System Details:

text file PDF

Summary:

This fully updated book explores all-new and revised protocols involving the use of in silico models, particularly with regard to pharmaceuticals. Divided into five sections, the volume covers the modeling of pharmaceuticals in the body, toxicity data for modeling purposes, in silico models for multiple endpoints, a number of platforms for evaluating pharmaceuticals, as well as an exploration of challenges, both scientific and sociological. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detail and implementation advice necessary for successful results. Authoritative and comprehensive, In Silico Methods for Predicting Drug Toxicity, Second Edition aims to guide the reader through the correct procedures needed to harness in silico models, a field which now touches a wide variety of research specialties.

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 Protocols 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.

Other Format:

Printed edition:

ISBN:

978-1-0716-1960-5

9781071619605

Access Restriction:

Restricted for use by site license.