Overview
Key Features
Includes detailed and standardized information about the techniques and tools used in translational medicine
Provides specific industry case scenarios
Explains how to use translational medicine tools and techniques to plan and improve infrastructures and capabilities while reducing cost and optimizing resources
Description
Translational Medicine: Tools and Techniques provides a standardized path from basic research to the clinic and brings together various policy and practice issues to simplify the broad interdisciplinary field. With discussions from academic and industry leaders at international institutions who have successfully implemented translational medicine techniques and tools in various settings, readers will be guided through implementation strategies relevant to their own needs and institutions. The book also addresses regulatory processes in USA, EU, Japan and China. By providing details on omics sciences techniques, biomarkers, data mining and management approaches, case reports from industry, and tools to assess the value of different technologies and techniques, this book is the first to provide a user-friendly go-to guide for key opinion leaders (KOLs), industry administrators, faculty members, clinicians, researchers, and students interested in translational medicine.
Readership
practitioners and researchers working in biomedical research, health center administrators, health professions associations, life sciences industry professionals in pharma, biotech, medical instruments, diagnostic companies, CROs, research reagent Suppliers, IT service providers, data management companies, senior to junior level academic faculty members, post graduate students and scholars, public health professionals, regulatory affairs professionals
Content List
- Chapter 1. New Developments in the Use of Biomarkers in Translational Medicine
- Introduction
- Biomarkers as Part of a Translational Strategy
- New Types of Biomarkers
- New Ways of Analyzing Biomarker Data
- Biomarker Documentation
- Promising Applications
- Conclusions
- Chapter 2. Advancements in Data Management and Data Mining Approaches
- Introduction
- Challenges of Managing and Mining Big Biomedical Data
- Data Management Framework
- Data Management Platforms
- Data Mining in Translational Medicine
- Data Mining Techniques and Methods
- Big Data and Data Mining
- Applications of Data Mining in Translational Medicine
- Conclusion
- Chapter 3. Modeling and Simulation Applications in Drug Development Process
- Introduction
- The Role of Modeling and Simulation in Translational Research in Drug Development
- Next Level of Contribution from Modeling and Simulation
- Chapter 4. Advancements in Omics Sciences
- Introduction
- Genomics
- Epigenomics
- Transcriptomics
- Proteomics
- Metabolomics
- Bioinformatics
- Conclusions
- Glossary
- List of Acronyms and Abbreviations
- Chapter 5. Regulatory Process in the United States of America, Europe, China, and Japan
- Section 1: Regulatory Process in the United States of America
- Section 2: Regulatory Process in Europe, China, and Japan
- Chapter 6. Translational Medicine Case Studies and Reports
- Introduction
- Conclusions
- Glossary
- List of Acronyms and Abbreviations
- Chapter 7. Translational Approaches in Alzheimer’s Disease
- Alzheimer Disease and the Role of Amyloid
- Therapeutic Approaches
- Clinical Trials and Biomarkers
- Concluding Comments and Future Directions
