Pharmaceutical Data Mining Approaches and Applications for Drug Discovery

by Balakin, Konstantin V.; Ekins, Sean

• ISBN13: 9780470196083
• ISBN10: 0470196084
• Edition: 1st
• Format: Hardcover
• Copyright: 2009-12-21
• Publisher: Wiley

Summary

Extracting and applying knowledge from chemical, biological, and clinical data is one of the biggest problems for the pharmaceutical industry. Focusing on diverse data mining approaches for drug discovery, including chemogenomics, toxicogenomics, and individual drug response prediction, Pharmaceutical Data Mining links theory to applications to illustrate how sophisticated computational data mining techniques can impact contemporary drug discovery and development. The book is of vital interest to pharmaceutical scientists, principal investigators and scientists, research directors, industrial and academic research libraries, and graduate students.

Author Biography

Konstantin V. Balakin is Head of the Laboratory of information Technology in Medicinal Chemistry at the Institute of physiologically Active Compounds at the Russian Academy of Science. He is also Director of the scientific consortium "Orchemed" (Organic Chemistry and Medicine), which currently includes 11 Russian academic institutes working in the field of organic, medicinal and biological chemistry, and drug discovery. Previously, he was Head of ht Computational Chemistry Department at ChemDiv, Inc. Dr. Balakin is the author or coauthor of more than 90 peer reviewed research articles, reviews and book chapters. He is the principal development of the SmartMining and InformaGenesis software, tools, which are special programs for pharmaceutical multivariate data mining.

Table of Contents

Preface	p. ix
Acknowledgments	p. xi
Contributors	p. xiii
Data Mining in the Pharmaceutical Industry: A general overview	p. 1
A History of the Development of Data Mining in Pharmaceutical Research	p. 3
Drug Gold and Data Dragons: Myths and Realities of Data Mining in the Pharmaceutical Industry	p. 25
Application of Data Mining Algorithms in Pharmaceutical Research and Development	p. 87
Chemoinformatics-based Applications	p. 113
Data Mining Approaches for Compound Selection and Iterative Screening	p. 115
Prediction of Toxic Effects of Pharmaceutical Agents	p. 145
Chemogenomics-Based Design of GPCR-Targeted Libraries Using Data Mining Techniques	p. 175
Mining High-Throughput Screening Data by Novel Knowledge-Based Optimization Analysis	p. 205
Bioinformatics-based Applications	p. 235
Mining DNA Microarray Gene Expression Data	p. 237
Bioinformatics Approaches for Analysis of Protein-Ligand Interactions	p. 267
Analysis of Toxicogenomic Databases	p. 301
Bridging the Pharmaceutical Shortfall: Informatics Approaches to the Discovery of Vaccines, Antigens, Epitopes, and Adjuvants	p. 317
Data Mining methods in Clinical Development	p. 339
Data Mining in Pharmacovigilance	p. 341
Data Mining Methods as Tools for Predicting Individual Drug Response	p. 379
Data Mining Methods in Pharmaceutical Formulation	p. 401
Data Mining Algorithms and Technologies	p. 423
Dimensionality Reduction Techniques for Pharmaceutical Data Mining	p. 425
Advanced Artificial Intelligence Methods Used in the Design of Pharmaceutical Agents	p. 457
Databases for Chemical and Biological Information	p. 491
Mining Chemical Structural Information from the Literature	p. 521
Index	p. 545
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