Length 114 pages

Date published July 2009

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Data Mining in Drug Development and Translational Medicine Table of Contents

 

Author: Hermann Mucke, PhD

Chapter 1
THE NEED FOR DATA MINING IN DRUG DEVELOPMENT: NATURE AND OBJECTIVES
1.1. The Exponential Growth of Humankind's Data Volume
1.2. Making Sense of Data: Ascent to the “Grand Picture”
Learning About the Unexpected: Exploratory Data Analyses for Hypothesis Generation
Seeking Specific Signatures: Data Mining for Hypothesis Testing
1.3. Who Mines Data Today…And For What?
Strategic Marketing
Financial Services and Tax Offices
Military and Security Assessments
Other Users of Data Mining Solutions
1.4. The Challenge of Life Science's Own Data Avalanche
Literature and Patent Texts
Cheminformatics
Sequence and Biomarker Information
Modeling of Market Dynamics and Competitor Behavior

Chapter 2
TECHNIQUES, TECHNOLOGY, AND SOFTWARE
2.1. Capturing Data and Knowing Their Bias
Experimental and External Data
2.2. Building Data Warehouses from Disparate Sources
2.3. Text Mining: Semantics and Artificial Intelligence
2.4. Structure Searches in Digital Chemical Libraries
2.5. Image Mining: The Greatest Challenge
2.6. Machine Learning with Pharmaceutical and Biological Data
2.7. Visualization of Results: The Challenge of Meaningful Reporting
2.8. Standardization and Regulatory Compliance: CDISC's SDTM and SEND

Chapter 3
DATA MINING FOR EARLY PRECLINICAL SAFETY ASSESSMENTS
3.1. A Close Look at Text Data: Literature, Patents, and Databases
3.2. “Pathway Mining” for Model Building and Matching
3.3. High-Content Screening as a Data Feed
3.4. Seeking Signatures of Toxicity in Animal Data
Behavioral Data: From Automated Counts to Video Mining
Biomarker Response Assessments in Animal Studies
Seeking Out and Interpreting Digital Pathology Data

Chapter 4
DATA MINING IN CLINICAL TRIALS
4.1. The Clinical Trial Database: Much More Than Meets the Eye

The “E-Trial”: The Key to Patient Record Mining in Near-Real Time
Retrospective Mining of Completed Trials: The “Paper Legacy”
Case Study: Statins and Amyotrophic Lateral Sclerosis
4.2. Mining for Safety Signals in Clinical Trials
Premarket Safety Data Mining by Regulatory Agencies
Hepatotoxicity
QT Interval Prolongation
4.3. Clinical Trial Data Mining for Drug Response Signatures
Genotype versus Phenotype: Identifying Potential Responders
Image Registration: Mining Imaging Data for Response Signatures
4.4. Detection of Data Bias and Fraud
4.5. Correcting for Non-Compliance in Outpatient Trials
4.6. Mining the Clinical Literature for Optimizing Scientific Approaches and Business Development

Chapter 5
DATA MINING IN PHARMACOVIGILANCE
5.1. The Challenges of Assessing Post-Marketing Drug Performance
5.2. Databases Supporting the Push for Post-Market Safety Evaluation

AERS and VAERS: The FDA Adverse Event Reporting System
VigiBase: The WHO Drug Safety Database
The EudraVigilance Post-Authorization Module
Prescription-Event Monitoring Databases
Corporate Pharmacovigilance Databases
5.3. Mining Adverse Event Databases
Basic Types of Mining Algorithms
The Influence of Coding Terms and Direct Patient Reporting
Case Studies and Promising Objectives
Oseltamivir and Hallucinations
Antipsychotics and Diabetic Events: An Effect of Chemical Structure?
Statins and Psychiatry: A Confusing Story with a Long History
Bisphosphonate Drugs and Osteonecrosis of the Jaw
5.4. Developments Shaping the Data Mining Environment in Pharmacovigilance
The FDA's Sentinel Initiative and the Reagan-Udall Foundation
PROTECT – Method Development for Pharmacovigilance in Europe
Electronic Health Records: A Future Key Factor for Data Collection

Chapter 6
BUSINESS MODELS AND SOLUTIONS IN DRUG DEVELOPMENT BIOINFORMATICS
6.1. Phase Forward
6.2. ProSanos
6.3. AltraBio
6.4. ID Business Solutions (IDBS)
6.5. Strand Life Sciences
6.6. SPSS
6.7. PointCross
6.8. Aperio Technologies
6.9. Molecular Devices
6.10. Cambridge Cell Networks (CCNet)
6.11. InforSense
6.12. SAS Institute
6.13. Temis
6.14. Search Technology
6.15. TIBCO Software
6.16. Salford Systems

References

Company Index with Web Addresses