
Re-Engineering Clinical Trials
Best Practices for Streamlining the Development Process
- 2nd Edition - March 2, 2029
- Latest edition
- Editors: Peter Schueler, Brendan Buckley
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 2 0 4 8 9 - 4
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 8 4 2 4 - 9
Re-Engineering Clinical Trials: Best Practices for Streamlining the Development Process, Second Edition evaluates the trends and challenges associated with the current drug develo… Read more
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- Highlights the latest paradigm-shifts and innovation advances in clinical research
- Offers easy-to-find best practice sections, lists of current literature, resources for further reading and useful solutions to day-to-day problems in current drug development
- Includes new sections on important topics such as patient centricity, machine learning, Bayesian statistics, disruption in R&D, wearable technologies, virtual trials, real world evidence, operational analytics as well as completely updated chapters
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
- Edition: 2
- Latest edition
- Published: March 2, 2029
- Language: English
PS
Peter Schueler
BB