Pharmaceutical Data Mining: Approaches and Applications for Drug Discovery / Edition 1

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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 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, form its foundations to contemporary industrial applications

Chemoinformatics-based applications

Bioinformatic-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.

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Editorial Reviews

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

Meet the Author

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.

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Table of Contents

Preface ix

Acknowledgments xi

Contributors xiii

Part I Data Mining in the Pharmaceutical Industry: A general overview 1

1 A History of the Development of Data Mining in Pharmaceutical Research David J. Livingstone John Bradshaw 3

2 Drug Gold and Data Dragons: Myths and Realities of Data Mining in the Pharmaceutical Industry Barry Robson John Bradshaw 25

3 Application of Data Mining Algorithms in Pharmaceutical Research and Development Konstantin V. Balakin Nikolay R Savchuk 87

Part II Chemoinformatics-based Applications 113

4 Data Mining Approaches for Compound Selection and Iterative Screening Martin Vogt J?rgen Bajorath 115

5 Prediction of Toxic Effects of Pharmaceutical Agents Andreas Maunz Christoph Helma 145

6 Chemogenomics-Based Design of GPCR-Targeted Libraries Using Data Mining Techniques Konstantin V. Balakin Elena V. Bovina 175

7 Mining High-Throughput Screening Data by Novel Knowledge-Based Optimization Analysis S. Frank Yan Frederick J. King Sumit K. Chanda Jeremy S. Caldwell Elizabeth A. Winzeler Yingyao Zhou 205

Part III Bioinformatics-based Applications 235

8 Mining DNA Microarray Gene Expression Data Paolo Magni 237

9 Bioinformatics Approaches for Analysis of Protein-Ligand Interactions Munazah Andrabi Chioko Nagao Kenji Mizuguchi Shandar Ahmad 267

10 Analysis of Toxicogenomic Databases Lyle D. Burgoon 301

11 Bridging the Pharmaceutical Shortfall: Informatics Approaches to the Discovery of Vaccines, Antigens, Epitopes, and Adjuvants Matthew N. Davies Darren R. Flower 317

Part IV Data Mining methods in Clinical Development 339

12 Data Mining in Pharmacovigilance Manfred Hauben Andrew Bate 341

13 Data Mining Methods as Tools for Predicting Individual Drug Response Audrey Sabbagh Pierre Darlu 379

14 Data Mining Methods in Pharmaceutical Formulation Raymond C. Rowe Elizabeth A Colbourn 401

Part V Data Mining Algorithms and Technologies 423

15 Dimensionality Reduction Techniques for Pharmaceutical Data Mining Igor V. Pletnev Yan A. Ivanenkov Alexey V. Tarasov 425

16 Advanced Artificial Intelligence Methods Used in the Design of Pharmaceutical Agents Yan A. Ivanenkov Ludmila M. Khandarova 457

17 Databases for Chemical and Biological Information Tudor I Oprea Liliana Ostopovici-Halip Ramona Rad-Curpan 491

18 Mining Chemical Structural Information from the Literature Debra L. Banville 521

Index 545

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