Pharmaceutical Data Mining (eBook)

Approaches and Applications for Drug Discovery

Konstantin V. Balakin (Autor)

eBook Download: PDF

2009
John Wiley & Sons (Verlag)
978-0-470-56761-6 (ISBN)

Infos

Leading experts illustrate how sophisticated computational data mining techniques can impact contemporary drug discovery and development

In the era of post-genomic drug development, extracting and applying knowledge from chemical, biological, and clinical data is one of the greatest challenges facing the pharmaceutical industry. Pharmaceutical Data Mining brings together contributions from leading academic and industrial scientists, who address both the implementation of new data mining technologies and application issues in the industry. This accessible, comprehensive collection discusses important theoretical and practical aspects of pharmaceutical data mining, focusing on diverse approaches for drug discovery—including chemogenomics, toxicogenomics, and individual drug response prediction. The five main sections of this volume cover:

• A general overview of the discipline, from its foundations to contemporary industrial applications
• Chemoinformatics-based applications
• Bioinformatics-based applications
• Data mining methods in clinical development
• Data mining algorithms, technologies, and software tools, with emphasis on advanced algorithms and software that are currently used in the industry or represent promising approaches

In one concentrated reference, Pharmaceutical Data Mining reveals the role and possibilities of these sophisticated techniques in contemporary drug discovery and development. It is ideal for graduate-level courses covering pharmaceutical science, computational chemistry, and bioinformatics. In addition, it provides insight to pharmaceutical scientists, principal investigators, principal scientists, research directors, and all scientists working in the field of drug discovery and development and associated industries.

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 Sciences. 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 the 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 developer of the SmartMining and InformaGenesis software tools, which are special programs for pharmaceutical multivariate data mining.

Inhalt

PHARMACEUTICAL DATA MINING 3
CONTENTS 7
PREFACE 11
ACKNOWLEDGMENTS 13
CONTRIBUTORS 15
PART I DATA MINING IN THE PHARMACEUTICAL INDUSTRY: A GENERAL OVERVIEW 19
1 A History of the Development of Data Mining in Pharmaceutical Research 21
2 Drug Gold and Data Dragons: Myths and Realities of Data Mining in the Pharmaceutical Industry 43
3 Application of Data Mining Algorithms in Pharmaceutical Research and Development 105
PART II CHEMOINFORMATICS-BASED APPLICATIONS 131
4 Data Mining Approaches for Compound Selection and Iterative Screening 133
5 Prediction of Toxic Effects of Pharmaceutical Agents 163
6 Chemogenomics-Based Design of GPCR-Targeted Libraries Using Data Mining Techniques 193
7 Mining High-Throughput Screening Data by Novel Knowledge-Based Optimization Analysis 223
PART III BIOINFORMATICS-BASED APPLICATIONS 253
8 Mining DNA Microarray Gene Expression Data 255
9 Bioinformatics Approaches for Analysis of Protein–Ligand Interactions 285
10 Analysis of Toxicogenomic Databases 319
11 Bridging the Pharmaceutical Shortfall: Informatics Approaches to the Discovery of Vaccines, Antigens, Epitopes, and Adjuvants 335
PART IV DATA MINING METHODS IN CLINICAL DEVELOPMENT 357
12 Data Mining in Pharmacovigilance 359
13 Data Mining Methods as Tools for Predicting Individual Drug Response 397
14 Data Mining Methods in Pharmaceutical Formulation 419
PART V DATA MINING ALGORITHMS AND TECHNOLOGIES 441
15 Dimensionality Reduction Techniques for Pharmaceutical Data Mining 443
16 Advanced Artificial Intelligence Methods Used in the Design of Pharmaceutical Agents 475
17 Databases for Chemical and Biological Information 509
18 Mining Chemical Structural Information from the Literature 539
INDEX 563

Rezensionen

"Its strength is that it gives beginners a good impression of our
contemporary data jungle." (ChemMedChem, 2010)

Produkt-Details

• Erscheint lt. Verlag: 19.11.2009
• Reihe/Serie: Wiley Series on Technologies for the Pharmaceutical
• Reihe/Serie: Wiley Series on Technologies for the Pharmaceutical
• Reihe/Serie: Wiley Series on Technologies for the Pharmaceutical Industry
• Mitarbeit: Herausgeber (Serie): Sean Ekins
• Sprache: englisch
• Themenwelt: Medizin / Pharmazie ► Gesundheitsfachberufe
• Themenwelt: Medizin / Pharmazie ► Medizinische Fachgebiete ► Pharmakologie / Pharmakotherapie
• Themenwelt: Naturwissenschaften ► Chemie
• Themenwelt: Technik
• Schlagworte: academic • application • Arzneimittelentwicklung • Bioinformatics & Computational Biology • Bioinformatik • Bioinformatik u. Computersimulationen in der Biowissenschaften • Biowissenschaften • Brings • challenges • Chemical • Chemie • Chemistry • Computational • Computational Chemistry & Molecular Modeling • Computational Chemistry u. Molecular Modeling • Contemporary • Contributions • Data • Drug • Drug Discovery & Development • ERA • Experts • Greatest • illustrate • Industry • Knowledge • Life Sciences • Pharmaceutical • Pharmazeutische Chemie • scientists • sophisticated • techniques • Wirkstoffforschung u. -entwicklung
• ISBN-10: 0-470-56761-9 / 0470567619
• ISBN-13: 978-0-470-56761-6 / 9780470567616