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Predictive ADMET : integrative approaches in drug discovery and development / edited by Jianling Wang, Laszlo Urban.

Contributor(s): Material type: TextTextPublisher: Hoboken, New Jersey : Wiley, [2014]Description: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781118783405
  • 1118783409
  • 9781118783306
  • 1118783301
  • 9781118783269
  • 1118783263
  • 9781118783344
  • 1118783344
  • 1118299922
  • 9781118299920
Subject(s): Genre/Form: Additional physical formats: Print version:: Predictive ADMET.DDC classification:
  • 615.1/9 23
LOC classification:
  • RM301.25
NLM classification:
  • QV 745
Online resources: Summary: "By guiding in the application of techniques and tools for predicting ADMET outcomes in drug candidates, Predictive ADMET offers a road map for drug discovery scientists to generate effective and safe drugs for unmet medical needs. Featuring case studies and lessons learned from real drug discovery and development, the text: helps users diagnose ADMET problems; presents appropriate recommendations; introduces the current clinical practice for drug discovery and development; and consolidates the tools and models to intelligently integrate existing in silico, in vitro and in vivo ADMET data"--Provided by publisher.
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Includes bibliographical references and index.

"By guiding in the application of techniques and tools for predicting ADMET outcomes in drug candidates, Predictive ADMET offers a road map for drug discovery scientists to generate effective and safe drugs for unmet medical needs. Featuring case studies and lessons learned from real drug discovery and development, the text: helps users diagnose ADMET problems; presents appropriate recommendations; introduces the current clinical practice for drug discovery and development; and consolidates the tools and models to intelligently integrate existing in silico, in vitro and in vivo ADMET data"--Provided by publisher.

Print version record and CIP data provided by publisher.