Konstantin V. Balakin 
Pharmaceutical Data Mining 
Approaches and Applications for Drug Discovery

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.

Cuprins

Preface.

Acknowledgments.

Contributors.

PART I: DATA MINING IN THE PHARMACEUTICAL INDUSTRY: A GENERAL
OVERVIEW.

1 A History of the development of Data Mining in Pharmaceutical
Research ( David J. Livingstone and John Bradshaw).

2 Drug Gold and Data Dragons: Myths and Realities of Data Mining
in the Pharmaceutical Industry (Barry Robson and Andy
Vaithiligam).

3 Application of Data Mining Algorithms in Pharmaceutical
Research and Development (Konstantin V. Balakin and Nikolay P.
Savchuk).

PART II: CHEMOINFORMATICS-BASED APPLICATIONS.

4 Data Mining Approaches for Compound Selection and Iterative
Screening (Martin Vogt and Jurgen Bajorath).

5 Prediction of Toxic Effects of Pharmaceutical Agents (Andreas
Maunz and Christoph Helma).

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

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, and Yingyao
Zhou).

PART III: BIOINFORMATICS-BASED APPLICATIONS.

8 Mining DNA Microarray Gene Expression Data (Paolo Magni).

9 Bioinformatics Approaches for Analysis of Protein-Ligand
Interactions (Munazah Andrabi, Chioko Nagao, Kenji Mizuguchi, and
Shandar Ahmad).

10 Analysis of Toxicogenomic Databases (Lyle D. Burgoon).

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

PART IV: DATA MINING METHODS IN CLINICAL DEVELOPMENT.

12 Data Mining in Pharmacovigilance (Manfred Hauben and Andrew
Bate).

13 Data Mining Methods as Tools for Predicting Individual Drug
Response (Audrey Sabbagh and Pierre Darlu).

14 Data Mining Methods in Pharmaceutical Formulation (Raymond C.
Rowe and Elizabeth A Colbourn).

PART V: DATA MINING ALGORITHMS AND TECHNOLOGIES.

15 Dimensionality Reduction Techniques for Pharmaceutical Data
Mining (Igor V. Pletnev, Yan A. Ivanenkov, and Alexey V.
Tarasov).

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

17 Databases for Chemical and Biological Information (Tudor I.
Oprea, Liliana Ostopovici-Halip, and Ramona Rad-Curpan).

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

Index.

Despre autor

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 Chem Div, 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 Smart Mining and Informa Genesis software tools, which are special programs for pharmaceutical multivariate data mining.