Table of Contents
Section 1: Why Does the Industry Need a Change? 1. Why is our industry struggling? 2. What are the current main obstacles to reach drug approval? 3. Japan: An opportunity to learn? 4. The "Clinical Trial App"
Section 2: What Does Our Industry and What Do Others Do 5. What does "re-engineering" mean in our industry? 6. How can the Innovative Medicines Initiative help to make drug development more efficient? 7. Experiences with Lean and Shopfloor Management in R&D in other branches 8. Well-known methodologies, but not in our world: FMEA
Section 3: Where to Start: The Protocol 9. No patients, no data: Patient recruitment in the 21st century 10. The impact of bad protocols 11. Data mining for better protocols 12. It is all in the literature 13. What makes a good protocol better? 14. The Clinical Trial Site
Section 4: Alternative Study Designs 15. Do we need new endpoints? Surrogate and bio-marker 16. On the measurement of the disease status in clinical trials: lessons from MS 17. Generating evidence from historical data using “robust prognostic matching: Experience from Multiple Sclerosis 18. Studies with fewer patients involved: the Adaptive Trial 19. Studies with less site involvement: the Hyper Trial 20. Studies without sites: the Virtual Trial
Section 5: From Data to Decisions 21. Data standards against data overload 22. Data management 2.0 23. What do Sites Want? 24. From data to information and decision: ICONIK 25. Knowledge Management 26. Taking Control of Ever Increasing Volumes of Unstructured Data 27. Share the Knowledge based on quality data
Section 6: You Need Processes, Systems and People 28. It's all about the people (and their competencies) 29. Manage the Change 30. How Key Performance Indicators help to manage the change
Conclusions