Muutke küpsiste eelistusi

E-raamat: In Silico Methods for Predicting Drug Toxicity

Teised raamatud teemal:
  • Formaat - EPUB+DRM
  • Hind: 122,88 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.
Teised raamatud teemal:

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

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.
Preface v
Contributors ix
1 QSAR Methods
1(22)
Giuseppina Gini
Part I Modeling a Pharmaceutical in the Human Body
2 In Silico 3D Modeling of Binding Activities
23(14)
Stefano Moro
Mattia Sturlese
Antonella Ciancetta
Matteo Floris
3 Modeling Pharmacokinetics
37(26)
Frederic Y. Bois
Celine Brochot
4 Modeling ADMET
63(24)
Jayeeta Ghosh
Michael S. Lawless
Marvin Waldman
Vijay Gombar
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
87(20)
Enrico Mombelli
Giuseppa Raitano
Emilio Benfenati
6 In Silico Methods for Carcinogenicity Assessment
107(14)
Azadi Golbamaki
Emilio Benfenati
7 VirtualToxLab: Exploring the Toxic Potential of Rejuvenating Substances Found in Traditional Medicines
121(18)
Martin Smiesko
Angelo Vedani
8 In Silico Model for Developmental Toxicity: How to Use QSAR Models and Interpret Their Results
139(24)
Marco Marzo
Alessandra Roncaglioni
Sunil Kulkarni
Tara S. Barton-Maclaren
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
163(14)
Fabiola Pizzo
Emilio Benfenati
10 In Silico Models for Acute Systemic Toxicity
177(24)
Julien Burton
Andrew P. Worth
Ivanka Tsakovska
Antonia Diukendjieva
11 In Silico Models for Hepatotoxicity
201(36)
Mark Hewitt
Katarzyna Przybylak
12 In Silico Models for Ecotoxicity of Pharmaceuticals
237(68)
Kunal Roy
Supratik Kar
13 Use of Read-Across Tools
305(20)
Serena Manganelli
Emilio Benfenati
Part III The Scientific and Society Challenges
14 Adverse Outcome Pathways as Tools to Assess Drug-Induced Toxicity
325(14)
Mathieu Vinken
15 A Systems Biology Approach for Identifying Hepatotoxicant Groups Based on Similarity in Mechanisms of Action and Chemical Structure
339(22)
Dennie G. A. J. Hebels
Axel Rasche
Ralf Herwig
Gerard J. P. van Westen
Danyel G. J. Jennen
Jos C. S. Kleinjans
16 In Silico Study of In Vitro GPCR Assays by QSAR Modeling
361(22)
Kamel Mansouri
Richard S. Judson
17 Taking Advantage of Databases
383(48)
Glenn J. Myatt
Donald P. Quigley
18 QSAR Models at the US FDA/NCTR
431(30)
Huixiao Hong
Minjun Chen
Hui Wen Ng
Weida Tong
19 A Round Trip from Medicinal Chemistry to Predictive Toxicology
461(14)
Giuseppe Felice Mangiatordi
Angelo Carotti
Ettore Novellino
Orazio Nicolotti
20 The Use of In Silico Models Within a Large Pharmaceutical Company
475(36)
Alessandro Brigo
Wolfgang Muster
21 The Consultancy Activity on In Silico Models for Genotoxic Prediction of Pharmaceutical Impurities
511(20)
Manuela Pavan
Simona Kovarich
Arianna Bassan
Lorenza Broccardo
Chihae Yang
Elena Fioravanzo
Index 531