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Quantitative Molecular Pharmacology and Informatics in Drug Discovery
Book Details
Author(s)Michael Lutz, Terry Kenakin
PublisherWiley
ISBN / ASIN0471988618
ISBN-139780471988618
AvailabilityUsually ships in 24 hours
Sales Rank4,719,693
CategoryMedical
MarketplaceUnited States 🇺🇸
Description
Quantitative Molecular Pharmacology and Informatics in Drug Discovery Michael Lutz, Section Head, Cheminformatics Group and Terry Kenakin, Principal Research Scientist, Glaxo Wellcome Research and Development, Research Triangle Park, NC, USA Quantitative Molecular Pharmacology and Informatics in Drug Discovery combines pharmacology, genetics and statistics to provide a complete guide to the modern drug discovery process. The book discusses the pharmacology of drug testing and provides a detailed description of the statistical methods used to analyze the resulting data. Application of genetic and genomic tools for identification of biological targets is reviewed in the context of drug discovery projects. Covering both the theoretical principles upon which the techniques are based and the practicalities of drug discovery, this informative guide.
* outlines in step-by-step detail the advantages and disadvantages of each technology and approach and links these to the type of chemical target being sought after in the drug discovery process; and,
* provides excellent demonstrations of how to use powerful pharmacological and statistical tools to optimize high-throughput screening assays.
Written by two internationally known and well-regarded experts, this book is an essential reference for research and development scientists working in the pharmaceutical and biotechnology industries. It will also be useful for postgraduates studying pharmacology and applied statistics.
* outlines in step-by-step detail the advantages and disadvantages of each technology and approach and links these to the type of chemical target being sought after in the drug discovery process; and,
* provides excellent demonstrations of how to use powerful pharmacological and statistical tools to optimize high-throughput screening assays.
Written by two internationally known and well-regarded experts, this book is an essential reference for research and development scientists working in the pharmaceutical and biotechnology industries. It will also be useful for postgraduates studying pharmacology and applied statistics.










