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In Silico Methods for Predicting Drug Toxicity

  • Fester Einband
  • 534 Seiten
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This detailed volume explores in silico methods for pharmaceutical toxicity by combining the theoretical advanced research with th... Weiterlesen
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Beschreibung

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.

Includes cutting-edge methods and protocols involving in silico techniques

Provides step-by-step detail essential for reproducible results

Contains key notes and implementation advice from the experts



Inhalt
1. QSAR Methods Giuseppina Gini Part I: Modeling a Pharmaceutical in the Human Body 2. In Silico 3D-Modelling of Binding Activities Stefano Moro, Mattia Sturlese, Antonella Ciancetta, and Matteo Floris 3. Modeling Pharmacokinetics Frederic Y. Bois and Céline Brochot 4. Modeling ADMET Jayeeta Ghosh, Michael S. Lawless, Marvin Waldman, Vijay Gombar, and Robert Fraczkiewicz Part II: The Applications of In Silico Models for the Different Endpoints 5. In Silico Prediction of Chemically-Induced Mutagenicity: How to Use QSAR Models and Interpret Their Results Enrico Mombelli, Giuseppa Raitano, and Emilio Benfenati 6. In Silico Methods for Carcinogenicity Assessment Azadi Golbamaki and Emilio Benfenati 7. VirtualToxLab: Exploring the Toxic Potential of Rejuvenating Substances Found in Traditional Medicines Martin Smieko and Angelo Vedani 8. In Silico Model for Developmental Toxicity: How to Use QSAR Models and Interpret Their Results Marco Marzo, Alessandra Roncaglioni, Sunil Kulkarni, Tara S. Barton-Maclaren, and Emilio Benfenati 9. 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 Fabiola Pizzo and Emilio Benfenati 10. In Silico Models for Acute Systemic Toxicity Julien Burton, Andrew P. Worth, Ivanka Tsakovska, and Antonia Diukendjieva 11. In Silico Models for Hepatotoxicity Mark Hewitt and Katarzyna Przybylak 12. In Silico Models for Ecotoxicity of Pharmaceuticals Kunal Roy and Supratik Kar 13. Use of Read-Across Tools Serena Manganelli and Emilio Benfenati Part III: The Scientific and Society Challenges 14. Adverse Outcome Pathways as Tools to Assess Drug-Induced Toxicity Mathieu Vinken 15. A Systems Biology Approach for Identifying Hepatotoxicant Groups Based on Similarity in Mechanisms of Action and Chemical Structure Dennie G.A.J. Hebels, Axel Rasche, Ralf Herwig, Gerard J.P. van Westen, Danyel G.J. Jennen, and Jos C.S. Kleinjans 16. In Silico Study of In Vitro GPCR Assays by QSAR Modeling Kamel Mansouri and Richard S. Judson 17. Taking Advantage of Databases Glenn J. Myatt and Donald P. Quigley 18. QSAR Models at the United States FDA/NCTR Huixiao Hong, Minjun Chen, Hui Wen Ng, and Weida Tong 19. A Round Trip from Medicinal Chemistry to Predictive Toxicology Giuseppe Felice Mangiatordi, Angelo Carotti, Ettore Novellino, and Orazio Nicolotti 20. The Use of In Silico Models Within a Large Pharmaceutical Company Alessandro Brigo and Wolfgang Muster 21. The Consultancy Activity on In Silico Models for Genotoxic Prediction of Pharmaceutical Impurities Manuela Pavan, Simona Kovarich, Arianna Bassan, Lorenza Broccardo, Chihae Yang, and Elena Fioravanzo

Produktinformationen

Titel: In Silico Methods for Predicting Drug Toxicity
Editor:
EAN: 9781493936076
ISBN: 978-1-4939-3607-6
Format: Fester Einband
Herausgeber: Springer, Berlin
Genre: Medizin
Anzahl Seiten: 534
Gewicht: g
Größe: H34mm x B259mm x T185mm
Jahr: 2016
Auflage: 1st ed. 2016

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