Quantitative molecular pharmacology and informatics in drug discovery

著者

書誌事項

Quantitative molecular pharmacology and informatics in drug discovery

Michael Lutz and Terry Kenakin

Wiley, c1999

  • alk. paper

大学図書館所蔵 件 / 全2件

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

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.

目次

Drug Discovery. Measurement of Drug Affinity. Efficacy. Pharmacological Assays Used in Screening for Therapeutic Ligands. Finding the Optimal Assay Format for the Chemical Target. Mathematical and Statistical Framework for Problems in Drug Discovery. Statistical Methods for Target Identification and Validation. Experimental Design. Analysis and Interpretation of Data. Index.

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