Principles of Translational Science in Medicine

Principles of Translational Science in Medicine: From Bench to Bedside, Third Edition, provides an update on major achievements in the translation of research into medically relevant results and therapeutics. The book presents a thorough discussion of biomarkers, early human trials, and networking models, and includes institutional and industrial support systems. It also covers algorithms that have influenced all major areas of biomedical research in recent years, resulting in an increasing number of new chemical/biological entities (NCEs or NBEs) as shown in FDA statistics.

New chapters include: Translation in Oncology, Biologicals, and Orphan Drugs. The book is ideal for use as a guide for biomedical scientists to establish a systematic approach to translational medicine and is written by worldwide experts in their respective fields.

• Includes state-of-the-art principles, tools such as biomarkers and early clinical trials, algorithms of translational science in medicine
• Provides in-depth description of special translational aspects in the currently most successful areas of clinical translation, namely oncology and immunology
• Covers status of institutionalization of translational medicine, networking structures and outcomes at the level of marketing authorization

All biomedical researchers from preclinical to clinical scientists need to understand and apply translational science in medicine, which applies to scientists in pharmaceutical industry though almost all principles are applicable to device development. Additionally, academic researchers will need the book, as well

1. Introduction and Definitions
2. What Is Translational Medicine?
3. Tools
4. Biomarkers
5. Early Clinical Trial Design
6. Pharmaceutical Toxicology
7. Translational Science Biostatistics
8. Intellectual Property Rights in Translation
9. Translational research in the Elderly
10.The View of Big Pharma
11. Translational Science in Medicine: Putting the Pieces Together
12. Biomarkers, Early Human Trials, Networking, Translatability Assessment
13. Learning by Experience: Examples of Translational Processes in the Cardiovascular Field