1. Use of Prior Information (Clinical, Pre-clinical and Models) to Improve Efficiency and the Efficacy Estimates
Roseann M. White, MA
Director of Clinical Trial Statistics
Duke Clinical Research Institute

2. Disclosure Statement of Financial Interest
Within the past 12 months, I or my spouse/partner have had a financial interest/arrangement or affiliation with the organization(s) listed below.
Affiliation/Financial Relationship
Company
Employee
Consulting Fees/Honoraria
Other Financial Benefit
Duke Clinical Research Institute
Claret
Abbott, Abbvie

3. Acknowledgements Dawn Bardot, Ph.D., VP, MDIC
Dan Schwartz, M.S., PM, MDIC
Tarek Haddad, Ph. D., Director, MDT
Mitchell Krucoff, M.D., F.A.C.C., DCRI/VA

4. Those who fail to learn from history are doomed to repeat it
Winston Churchill
modifying a quote from George Santayana

5. Agenda
Quick review of exchangeability
clinical examples
Conclusion

6. former executive, president, and chair of Hewlett-Packard Co.
The goal is to turn data into information, and information into insight.
Carly Fiorina
former executive, president, and chair of Hewlett-Packard Co.

7. Strategy Planning Stage: Regulatory, Science, Statistics agree on
This type of planning can happen at any time during the development process – its never too early or too late
Strategy
Planning Stage: Regulatory, Science, Statistics agree on
your labeling about the product about safety, efficacy and effectiveness
Before you begin a non-clinical or clinical study, Regulatory, Science, Statistics agree on
How the data collected in this study will fit into a coherent body of evidence about the product safety, efficacy and effectiveness
Aggregating data from several similar studies will help to turn the data into information and insight about the product but it needs to be considered before the study is run.

8. Statistical Methods for Aggregating Data
Underlying assumption for all data aggregation methods: exchangeability
One is sampling from the same underlying population (patients, animals, materials, etc.)

9. Bayesian Methods
Bayesian methods of data aggregation are processes where continuum of data sets with the outcome being studied are combined to improve estimates

10. Aggregating Using Bayesian Methods
Historical
Historical
Historical
Current
Current
Current

11. Non-clinical Study Examples

12. Non-clinical Stability Studies
From Stan Altan, Senior Director and Fellow, Janssen R&D, presentation at Rutgers, 2009 on the use of Bayesian methods for stability studies
Are the regulatory guidelines reflective of current technology and statistical practice?
This is the right time to question the pooling paradigm
Are we stuck in a Hypothesis Testing /Equivalence Testing rut?
Bayesian approach
Provides mechanism to include prior information to the statistical analysis of current data and to update model parameter estimates as new data are collected
A more natural way to approach to CMC decision making in terms of a posterior predictive distribution

13. Clinical Study Examples

14. Approval of Stents
MULTI-LINK TETRA(tm) Coronary Stent System approval was based on the use of bayesian priors from DUET and Multilink
Approved using 100 pts in-hospital outcomes
6 months from start of enrollment to submission
Boston Scientific ION stent Paclitaxel-Eluting Platinum Chromium Coronary Stent System
1/3 of patients were contributed from the TAXUS IV RCT

15. Conclusion
Rather than just submitting individual studies on a particular topic, aggregating the results to improve the accuracy and precision of the results will provide FDA with that coherency
Data aggregation methods can be applied to both non-clinical and clinical studies
However it requires close collaboration among, science statistics and regulatory during the entire product development life cyle